Anticholinergics
Antihistamines
Beta-blockers
Diuretics
Methyldopa
Phenothiazines
Tricyclic antidepressants
Drugs of abuse
Alcohol
Examination. Examination of the collapsed athlete should include continued monitoring of the athlete's vital signs. Heart rate and blood pressure should be measured in both supine and erect postures. When the athlete stands, if heart rate increases by 20 beats per minute or systolic blood pressure falls by 20 mm Hg or diastolic blood pressure falls by 10 mm Hg, these changes suggest significant depletion of blood volume and probable dehydration. Keep in mind that most endurance athletes have very low resting hearts rates, and a resting pulse of 80 beats per minute may actually represent tachycardia (Mayers & Noakes, 2000; O'Conner et al., 2003). Athletes with diminished mental function should have their rectal temperatures measured to rule out heat stroke. (Measuring temperature in the ear or mouth does not give an accurate measure of core body temperature). A rectal temperature above 104o F (40o C) demands immediate cooling measures.
The athlete's state of hydration can be assessed by asking about thirst and the ability to spit (Holtzhause & Noakes, 1997; O'Conner et al., 2003). Athletes who are dehydrated will be thirsty, and they will have a difficult time producing spit if they are seriously dehydrated. Also, skin turgor may be diminished in seriously dehydrated athletes, i.e., their skin may seem loose, may feel doughy, and may resemble a miniature tent after being pinched (the "tenting" phenomenon).
Conversely, athletes who are over-hydrated may look and feel puffy. They may state that rings, watches, shoes, and race wristbands fit more tightly than before the race. In severe cases of fluid overload, pitting edema (swelling) in the legs may be noted. This is often associated with low levels of blood sodium (hyponatremia). Measuring body weight before and after competition is a helpful gauge of fluid status. A 2-5% loss of body weight indicates dehydration, whereas weight gain suggests fluid overload.
Laboratory Tests. Important laboratory evaluations in the collapsed athlete include measurements of blood glucose and sodium concentrations. Hyponatremia is the most common cause of severe collapse in the endurance athlete. The ability to quickly measure sodium levels is critical in diagnosing this condition and helping to guide appropriate treatment. Hypoglycemia, while less common, can produce dramatic alterations in the level of consciousness and even coma, which can be promptly corrected by administering oral or intravenous glucose.
The vast majority of athletes who collapse do so for benign reasons (Holtzhause & Noakes, 1997; Mayers & Noakes, 2000; Sandell et al., 1988). According to Bently (1996) and O'Conner et al. (2003), findings suggestive of a benign cause of collapse include:
The most common serious causes of collapse in the athlete include hyponatremia, hypoglycemia, heatstroke, cardiac arrest, and various other serious medical conditions, including seizures, brain hemorrhage, and diabetic coma. Bently (1996) and O'Conner et al. (2003) list the following findings suggestive of a more serious cause of collapse:
Postural Hypotension (Heat Exhaustion or Syncope). Postural hypotension (low blood pressure while standing) has been referred to as heat exhaustion or heat syncope and is one of the most common causes of collapse. The collapse typically occurs after the finish line and is rarely serious enough to warrant hospital admission. It is likely caused by blood pooling in dilated vessels of the skin and limbs, especially the legs, and loss of the muscle pumping action from the lower legs after cessation of exercise (Holtzhause & Noakes, 1997; O'Conner et al., 2003; Sandell et al., 1988).
Dehydration and a resultant decrease in circulating blood volume increase the risk for postural hypotension, but there is no evidence that postural hypotension will progress to heat stroke. Postural hypotension is the likely culprit if the rectal temperature is less than 104o F (40o C), the heart rate is less than 100 beats per minute, and the systolic blood pressure is greater than 100 mm Hg once the athlete has assumed the supine position.
Treatment involves elevating the feet and pelvis for 10-20 minutes until normal circulation has been re-established. Athletes should be given oral fluids as tolerated. Oral rehydration solutions or sports drinks that replace electrolytes and replenish carbohydrates are usually better than water. Some athletes may need intravenous fluid if there are signs of severe dehydration.
Muscle Cramps. Muscle cramps are common in virtually all strenuous sports activities. They can occur during or after repetitive exercise performed in the heat, cold, or in water. Cramps tend to be more common and severe when intense exercise is done in hot and humid environments. In certain individuals, severe and recurrent cramps are associated with sickle-cell trait and suggest a risk for exercise-related sudden death.
Current evidence supports two common etiologies for sports-related muscle cramping, i.e., muscle fatigue caused by overuse, and sodium depletion (Bently, 1996; Miles & Clarkson, 1994). Overuse-induced muscle fatigue usually causes less severe and more localized cramping. Salt loss, on the other hand, often causes more severe total-body cramping.
The initial treatment for sports-related muscle cramps is to keep the affected muscles in a stretched position. The application of ice and/or massage can be helpful in lessening the symptoms of an acute cramp. Cramps due to muscle fatigue tend to occur early in the competitive season when athletes are less physically fit or when they are involved in unusually strenuous activities. Increased salt intake can be very helpful in preventing cramps that are severe, involve the whole body, and recur frequently.
Dehydration. Dehydration can have a variety of deleterious effects on the athlete, all of which may impair performance and increase the likelihood of collapse (American College of Sports Medicine, 1996; Casa et al., 2000). Dehydration leads to a reduced blood volume, making the athlete more susceptible to postural hypotension and collapse. Low blood volume is also associated with a decreased cardiac stroke volume that results in a decreased blood flow to the skin, which adversely affects heat dissipation. Dehydrated athletes have higher rectal temperatures than normally hydrated athletes, and dehydration reduces the time that exercise can be sustained before heat-induced fatigue and eventual collapse. Signs and symptoms of serious dehydration include severe thirst, dry mouth, and difficulty producing spit. Findings on physical exam consistent with dehydration include increased heart rate, decreased blood pressure, weight loss and poor skin turgor (loose skin with tenting).
Treatment of the dehydrated athlete should begin with oral rehydration solutions or sports drinks if the athlete is not vomiting and has lost less than 5% of body weight. Intravenous fluid should be given if athletes cannot tolerate oral fluids or the level of dehydration is greater than 5%.
Hyponatremia of Exercise. Hyponatremia is the most common serious cause of exercise-associated collapse. It is usually caused by replacement of relatively hypertonic sweat with a hypotonic fluid that contains little or no sodium. It is most often seen in longer endurance races and is more common in females, slower runners, and those drinking water rather than sports drinks containing sodium (Noakes, 1998; Sandell et al., 1988; Speedy et al., 1999). Symptoms of hyponatremia depend on the severity of the sodium deficit. The normal concentration of sodium in blood serum ranges between 135 and 145 mEq/L, and the severity of hyponatremia can be graded as mild to severe:
Examination of an athlete with hyponatremia (as determined from a blood draw) generally reveals a rectal temperature of less than1030 F (39o C) along with stable blood pressure and heart rate. There is often a diminished level of consciousness when the hyponatremia is moderate to severe. Hyponatremia due to fluid overload may cause the athlete to look puffy, and rings, watches, shoes, and race wristbands are often tight. These athletes have often gained significant body weight during the competition. However, athletes with hyponatremia can sometimes be dehydrated and have a low blood volume, probably due to only partial replacement of sweat loss with hypotonic fluid. This hypovolemic type of hyponatremia seems to be more common in the faster finishers.
Experience suggests that one should assume hyponatremia if rectal temperature, blood pressure, and heart rate are normal in the collapsed athlete who exhibits a diminished level of consciousness (Holtzhause & Noakes, 1997, 1998; Mayers & Noakes, 2000). In athletes who appear fluid overloaded, administration of large volumes of intravenous fluid should be avoided because this treatment can lead to congestive heart failure and even death. In athletes who appear dehydrated and are suspected of having a low blood volume, intravenous administration of normal saline can replace both salt and water. In very severe cases, hypertonic saline (3-5%) can be infused at a slow rate (less than 50 ml/h) while closely monitoring the athlete's condition. Most athletes with even severe hyponatremia of exercise recover spontaneously after 1-3 hours of rest and supportive care. The voiding of copious amounts of clear urine often precedes their recovery. Heatstroke. Heatstroke is caused by failure of the body to regulate its temperature in the heat. It is a rare event and is easily treated when diagnosed early, but it has a very high morbidity and mortality when improperly managed or when the diagnosis is delayed. The hallmark symptom of heat stroke is a marked change in mental function, i.e., a loss or diminished level of consciousness or mental stimulation (Holtzhause & Noakes, 1997; Noakes, 1998). Athletes with heat stroke often collapse or act inappropriately. Eventually, they lapse into a coma and often develop rhabdomyolysis (breakdown of muscle tissue) and renal failure leading to death.
Athletes suffering heatstroke usually collapse prior to the finish of an event, often shorter races run at faster speeds. Heavier athletes are at greater risk.. Because athletes competing in long endurance events run at slower speeds, they usually store less body heat (if the humidity is relatively low) so heat stroke is less common. Predisposing factors include high heat and especially humidity, faster running speed, history of heat illness, greater body weight, and possibly dehydration with blood volume depletion. Vomiting and diarrhea are often symptomatic of the onset of heatstroke.
The hallmark exam finding with heatstroke is a rectal temp above104o F (40o C). In addition, athletes with heatstroke usually have high heart rates, fast breathing, and low blood pressure. With classic heatstroke, sweating often stops and the victim appears hot and dry, but in heat stroke associated with athletic activity, the victim is usually sweating profusely.
The treatment for heatstroke is active cooling as soon as possible. The survival rate is 90-95% when cooling is done rapidly. However, if cooling is delayed and the temperature rises above108o F (42o C), the mortality approaches 80% (Holtzhause & Noakes, 1997, 1998; Noakes, 1988). Heatstroke is a true emergency and can be thought of as a "heat attack," in which every minute of delay in treatment significantly reduces the chance of a good outcome for the athlete.
The most effective measure to achieve rapid cooling of an overheated athlete is immersion in ice water. This is most easily accomplished using a small plastic tub or pool filled with ice and water. Typically, immersion for 5-10 minutes is long enough to cool an athlete with heatstroke. Cooling should continue until the rectal temperature is below 101o F (38o C) or the athlete begins to shiver.
A less effective cooling alternative is to apply ice packs to neck, groin and underarms of the heatstroke victim. Applying a cold-water mist using spray bottles, combined with fanning, can be a useful adjunct. Additionally, cold intravenous fluids can help cool a heat-stroke victim.
Hypoglycemia. Hypoglycemia is a less frequent cause of exercise-associated collapse and occurs when the liver production of glucose decreases after its glycogen stores are depleted (Holtzhause & Noakes, 1997; Sandell et al., 1988). This is most commonly seen in distance events lasting more than four hours. Athletes who fail to eat and drink sufficient carbohydrate before and during an event are at risk. Hypoglycemia is most often seen in diabetic athletes and in those with eating disorders.
Symptoms of hypoglycemia include body tremors, weakness, anxiety, sweating, slurred speech, and eventually coma. Treatment is the administration of glucose (sports drinks, juice, hard candy, or glucose tablets), which gives immediate relief of symptoms. Hypoglycemic athletes who are unconscious or unresponsive should be given an intravenous glucose solution (D50) or a glucagon injection to immediately raise blood sugar levels.
Hypothermia. Hypothermia is an unusual cause of collapse in an athlete, but it can occur when an athlete remains too long in a cold environment and does not generate enough body heat to compensate for heat loss to the environment. Most cases are seen when the swim portion of a triathlon is done in cold water, when endurance events are held during cold and wet weather, or in cold-weather sports such as cross-country skiing.
The severity of the hypothermia is gauged by the rectal temperature. Mild hypothermia is defined as a rectal temperature between 90-95o F (32-35o C) and is often accompanied by mild confusion and intense shivering. Treatment should include protecting the athlete from the environment and removing wet clothing, followed by passive warming with blankets and drinking of hot liquids. When the rectal temperature drops below 90 F, shivering (which generates body heat) usually stops; if this happens, the athlete must be immediately transferred to a hospital for more active warming measures such as administration of warm intravenous fluids, warm oxygen, or peritoneal dialysis using warm fluids. Severely hypothermic athletes, i.e., rectal temperature less than 82o F) may appear dead, only to survive after re-warming.
Exercise-associated collapse is a relatively common occurrence in endurance events, especially those occurring in high heat and humidity. The cause is most often benign in athletes who collapse after finishing exercise with no loss of consciousness, normal vital signs, and normal mental status. A more serious cause should be suspected in athletes who collapse while exercising, have unstable vital signs, or an altered level of consciousness. Appropriate and early diagnosis is essential in athletes who collapse so that proper treatment can be initiated. Most cases can be managed with rest and oral fluids. On the other hand, more serious causes of collapse, e.g., when associated with hyponatremia and heatstroke, can lead to serious organ damage and even death if not treated quickly and appropriately,. It is essential that those providing medical care at endurance events or caring for these athletes be familiar with the appropriate management of the collapsed athlete to prevent a possible tragic outcome.
American College of Sports Medicine (1996). Position stand on exercise and fluid replacement. Med. Sci. Sports Exerc. 28(1):i-vii.
Bently, S (1996). Exercise-induced muscle cramps: proposed mechanisms and management. Sports Med. 21:409-420.
Casa, D.J., L.E. Armstrong, S.K. Hillman, S.J. Montain, R.V. Reiff, B.S.E. Rich, , W.O. Roberts, and J.A. Stone (2000). National Athletic Trainers Association position statement: Fluid replacement for athletes. J. Athl. Train. 35:212-224.
Holtzhause, L.M., and T.D. Noakes (1998). Planning emergency care for an ultra-endurance event. Trauma Emergency Med. June/July:19-26.
Holtzhause, L.M., and T.D. Noakes (1997). Collapsed ultra-endurance athlete: proposed mechanisms and an approach to management. Clin. J. Sport Med. 7:409-420.
Mayers, L.B., and T.D. Noakes (2000). A guide to treating Ironman Triathletes at the finish line. Phys. Sportsmed. 28(8):35-50.
Miles, M.P., and P.M. Clarkson (1994). Exercise-induced muscle pain, soreness and cramps. J. Sports Med. Phys. Fit. 34:203-216.
Noakes, T.D. (1998). Fluid and electrolyte disturbances in heat illness. Int. J. Sports Med. 19 (suppl 2):S146-S149.
O'Conner, F.G., S. Pyne, F.H. Brennan, and T. Adirim (2003). Exercise associated collapse: An algorithmic approach to race day management. Am. J. Med. Sports 5:212-217, 229.
Roberts, W.O. (1989). Exercise-associated collapse in endurance events: a classification system. Phys. Sportsmed. 17(5): 49-59.
Sandell, R.C., M.D. Pascoe, and T.D. Noakes (1988). Factors associated with collapse during and after ultramarathon foot races. Phys. Sportsmed. 16(19): 86-94.
Speedy, D.B., T.D. Noakes, I.R. Rodgers, J.M. Thompson, R.G. Campbell, J.A. Kuttner, D.R. Boswell, S. Wright, and M. Hamlin (1999). Hyponatremia in ultradistance triathletes. Med. Sci. Sports Exerc. 31:809-815.
Sports Science Exchange 94 VOLUME 17 (2004) NUMBER 4 SUPPLEMENT
It is relatively common to witness the collapse of athletes in endurance events, especially when the heat and humidity are high. If an athlete collapses after finishing an event and remains conscious with normal heart rate, blood pressure, breathing, and mental status, the condition is usually not serious and is probably brought on by exhaustion, moderate dehydration that contributes to a moderate fall in blood pressure while the athlete is standing, or muscle cramps. A more dangerous cause should be suspected in athletes who collapse during competition or training, have unstable vital signs, and/or become unconscious or exhibit inappropriate behaviors (Table S1).
TABLE S1. Common causes of collapse during exercise.
Non-Serious Causes
Serious Causes
Appropriate and early diagnosis is essential in athletes who collapse so that proper treatment can be initiated. Table S2 illustrates the common features of non-serious or benign collapse and potentially dangerous collapse. It is especially important that medical personnel be able to obtain quick laboratory reports on concentrations of blood glucose and serum sodium. Depending on how low the serum sodium concentration is, severe outcomes can result (Table S3).
TABLE S2. Severity classification for the collapsed athlete.
Appearance: Conscious and alert | Appearance: Unconscious or altered mental status |
Physical examination results: Rectal temperature <104o F (40o C) Systolic blood pressure >100 Heart rate <100 beats per minute Weight loss 0-5% | Physical examination results: Rectal temperature >104o F (40o C) Systolic blood pressure |
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This is an excerpt from waterlogged by timothy noakes..
Why Runners Collapse
Why would anyone expect the symptom of thirst to be present in collapsed runners? Thirst is such a powerful urge that any thirsty marathon runner suffering from dehydration during a race will simply stop at the next refreshment station and drink until her thirst is slaked. Simple.
The basis for the belief that collapsed runners were suffering from dehydration began with the explosive growth in the number of marathon runners after 1976 (figure 2 a , page xv). This produced a massive increase in the number of runners requiring medical care at the finish of those races. Logically, the collapse of an athlete after rather than during a sporting event cannot be due to dehydration, since dehydration, which allegedly impairs circulation, must cause the athlete to collapse during the race when the strain on the heart and circulation is the greatest. This cannot happen immediately after the exercise terminates when any stress on the heart and circulation is falling. But this simple logic was ignored. Instead, it was concluded that all these collapsed athletes were suffering from dehydration, and their symptoms were caused by that dreaded disease.
But the truth is that athletes who collapsed after endurance events develop very low blood pressure only when standing (exercise-associated postural hypertension, or EAPH). This is caused by physiological changes that begin the moment the athlete stops running or walking after exercise and to which dehydration does not contribute. We know this because the moment these collapsed athletes lie flat, or better, with their legs and pelvis elevated above the level of the heart (“head down”), their symptoms instantly disappear. 4 Thus, if the symptoms occur in athletes who are not thirsty and can be reversed instantly without fluid ingestion, the condition cannot be due to dehydration. Rather, EAPH must be due to the relocation of a large volume of blood from the veins in the chest and neck (which fill the heart and ensure its proper functioning) to the veins of the lower legs (which lie below the level of the heart) and therefore fill whenever an athlete stands.
One of the physiological costs of bipedalism is that it made it more difficult for exercising humans to regulate blood pressure when standing, because more than 60% of the blood in circulation is contained in large veins that are situated below the level of the heart. If this volume increases abruptly at any time, especially on cessation of exercise, it will cause EAPH to develop. Two factors cause this translocation immediately after the exercise terminates. First, the muscles in the calf, the contraction of which empties blood from the leg veins pumping it toward the heart, stop working. As a result, the action of this “second heart” is lost, causing blood to pool in the legs. Second, exercise impairs the bodily responses to any sudden reduction in blood pressure. This response requires the rapid activation of the sympathetic nervous system, which raises the blood pressure by increasing the resistance to blood flow in many organs, including the muscles of the legs. But endurance training reduces the sensitivity of the sympathetic nervous system to respond to such sudden stresses.
Those athletes who do not develop EAPH are able to prevent this relocation of blood volume from the center of the body to the legs, which begins the moment exercise terminates, in part because they activate an appropriate response of their sympathetic nervous system the moment they stop exercising.
The symptoms of EAPH are caused by this sudden onset of a falling blood pressure, which results in an inadequate blood supply to the brain (cerebral ischemia). The symptoms of cerebral ischemia are dizziness, nausea leading perhaps to vomiting, and a transient loss of consciousness (fainting). These symptoms persist until the blood flow to the brain is restored by an increase in blood pressure. Usually this occurs when the athlete falls to the ground and lies flat, thereby relocating a large volume of blood from the legs (and intestine) back to the center of the body. This sudden return of blood to the heart rapidly improves heart function and restores blood pressure to the appropriate postexercise value ( 100 to 120 / 60 to 80 mmHg), which is usually slightly lower than the accepted normal ( 110 to 140 / 60 to 90 mmHg) for resting humans who have not recently exercised.
The point is that dizziness, fainting, and nausea are the symptoms not of dehydration but of an inadequate blood supply to the brain. People who die from profound fluid loss when they are lost in the desert for three or more days without water also become confused. But this is not because of an inadequate blood supply to the brain—one of the body's most protected physiological functions—but because they develop multiple organ failure, including heart, kidney, and liver failure. The heart failure reduces blood flow to the brain, while kidney failure and liver failure cause the accumulation of certain toxic chemicals in the body that interfere with brain functioning, causing confusion and ultimately coma and death.
Experienced sport physicians are unable to determine the extent of dehydration (or volume of depletion) on the basis of the methods taught in medical school, that is, by examining the turgor of the skin, the state of hydration of the mucous membranes in the mouth, the presence of “sunken eyes,” the ability to spit, and the sensations of thirst (McGarvey, Thompson, et al., 2010). The only way accurately to determine the level of an athlete's state of hydration after prolonged exercise is to measure the body weight before and after exercise and, better, to measure the change in body water. The use of urine color, much promoted by some scientists, is of no value (Cheuvront, Ely, et al., 2010), because it is a measure of the brain and kidneys' response to changes in blood osmolality. It does not tell us exactly what the blood osmolality is and whether it is raised, lowered, or normal. As we will show, athletes with EAH typically excrete a dark urine even though they are severely overhydrated with blood osmolalities that are greatly reduced.
While serving as medical consultant at the 1998 Ironman Hawaii Triathlon, I attempted to introduce the concept of elevating the base of the bed to treat the low blood pressure (postural hypotension) that, in my opinion, is by far the most common cause of postrace collapse in athletes. Lifting the base of the bed cures the symptoms of postural hypotension and reduces the need to give intravenous fluids (inappropriately) for this condition.
This I showed at least to my own satisfaction in one elderly (>70-year-old) finisher whom I was called to see because he was deathly pale. The attending doctor could not detect a measurable pulse or blood pressure. I immediately lifted the base of the bed. Within seconds the patient's pulse became palpable, color returned to his face, and he was miraculously “cured.”
Years later, scientific papers written by some of the doctors I had interacted with showed that some lessons had been learned. Dr. Robert Sallis, who had been my close companion in the medical tent in 1998, wrote an article on the GSSI website acknowledging the value of this simple intervention. In that article he wrote, “The most common benign cause of collapse is low blood pressure due to blood pooling in the legs after cessation of exercise (as in postural hypotension, heat exhaustion, or syncope). This condition is treated by elevating the feet and pelvis until symptoms improve” (Sallis, 2004, p. 1). In the article, Dr. Sallis lists dehydration as a “non-serious” cause of collapse in athletes, which seems to conflict with the message of both the ACSM and the GSSI.
Read more from Waterlogged by Timothy Noakes.
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Research Article
Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing
* E-mail: [email protected]
Affiliation Insight SFI Research Centre for Data Analytics, School of Computer Science, University College Dublin, Dublin, Ireland
In the marathon, how runners pace and fuel their race can have a major impact on race outcome. The phenomenon known as hitting the wall (HTW) refers to the iconic hazard of the marathon distance, in which runners experience a significant slowing of pace late in the race, typically after the 20-mile mark, and usually because of a depletion of the body’s energy stores.
This work investigates the occurrence of significant late-race slowing among recreational marathoners, as a proxy for runners hitting the wall, to better understand the likelihood and nature of such slowdowns, and their effect on race performance.
Using pacing data from more than 4 million race records, we develop a pacing-based definition of hitting the wall, by identifying runners who experience a sustained period of slowing during the latter stages of the marathon. We calculate the cost of these slowdowns relative to estimates of the recent personal-best times of runners and compare slowdowns according to runner sex, age, and ability.
We find male runners more likely to slow significantly (hit the wall) than female runners; 28% of male runners hit the wall compared with 17% of female runners, χ 2 (1, N = 1, 928, 813) = 27, 693.35, p < 0.01, OR = 1.43. Such slowdowns are more frequent in the 3 years immediately before and after a recent personal-best (PB) time; for example, 36% of all runners hit the wall in the 3 years before a recent PB compared with just 23% in earlier years, χ 2 (1, N = 509, 444) = 8, 120.74, p < 0.01, OR = 1.31. When runners hit the wall, males slow more than females: a relative slowdown of 0.40 vs. 0.37 is noted, for male and female runners, when comparing their pace when they hit the wall to their earlier race (5km-20km) pace, with t (475, 199) = 60.19, p < 0.01, d = 0.15. And male runners slow over longer distances than female runners: 10.7km vs. 9.6km, respectively, t (475, 199) = 68.44, p < 0.01, d = 0.17. Although, notably the effect size of these differences is small. We also find the finish-time costs of hitting the wall (lost minutes) to increase with ability; r 2 (7) = 0.91, p < 0.01 r 2 (7) = 0.81, p < 0.01 for male and female runners, respectively.
While the findings from this study are consistent with qualitative results from earlier single-race or smaller-scale studies, the new insights into the risk and nature of slowdowns, based on the runner sex, age, and ability, have the potential to help runners and coaches to better understand and calibrate the risk/reward trade-offs that exist as they plan for future races.
Citation: Smyth B (2021) How recreational marathon runners hit the wall: A large-scale data analysis of late-race pacing collapse in the marathon. PLoS ONE 16(5): e0251513. https://doi.org/10.1371/journal.pone.0251513
Editor: Maria Francesca Piacentini, University of Rome, ITALY
Received: December 1, 2020; Accepted: April 28, 2021; Published: May 19, 2021
Copyright: © 2021 Barry Smyth. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All of the data used in this research is publicly available on marathon websites. The data has been collected from a variety of different marathon result archives, the URLs of which have been provided as a table in the Supporting information .
Funding: BS is supported by Science Foundation Ireland under grant 12/RC/2289P2. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
In the marathon, terms such as “hitting the wall” (HTW), “bonking”, or “blowing up” refer to the sudden onset of debilitating fatigue that can occur late in the race. At best, this can temporarily slow even the most accomplished and experienced runners, but it can also render a runner unable to muster much more than a walking pace for the remainder of the race and may prevent some from finishing. While most marathon runners are familiar with the notion of hitting the wall—many even claim to have experienced it in person [ 1 , 2 ]—it should be recognised that truly hitting the wall is not the same as the feeling of generalized fatigue and discomfort that is part and parcel of running the marathon distance [ 3 – 5 ]. The conventional wisdom is that runners hit the wall when their glycogen stores become depleted, usually as a result of poor race nutrition [ 6 – 9 ], which can be exacerbated by aggressive pacing [ 7 , 10 , 11 ], and there is thought to be an important cognitive component too [ 12 , 13 ]. While experienced marathoners understand how to avoid hitting the wall, it remains a significant risk among recreational marathoners, especially novices and first-timers.
The central objective of this work is to explore the nature of these slowdowns by analysing more that 4 million race-day records; the scale of this study distinguishes it from much of the work on hitting the wall that has come before [ 1 , 2 , 11 , 14 , 15 ]. We identify runners who suffer significant and sustained slowing during the latter stages of the marathon, and examine the characteristics of these slowdowns (frequency, start, duration, degree, finish-time cost) in relation to sex, age, and ability.
We find male runners to be much more likely than female runners to hit the wall [ 11 , 14 ], regardless of age or ability, and we find that slowdowns occur more frequently in the years immediately before and after a recent personal best. Moreover, when males hit the wall, they slow more than female runners, and over longer distances. Although the costs of these slowdowns (lost minutes) are broadly similar between males and females, they tend to increase with ability, with faster runners experiencing a greater finish-time cost than slower runners.
The phenomenon of hitting the wall is perhaps the most iconic hazard of the marathon distance, but a similar effect can be found in other endurance events too, including ultra-marathons, adventure races, cycling and the triathlon. Fortunately, the most catastrophic examples of hitting the wall remain relatively rare, but the phenomenon continues to impede many marathoners, especially less experienced recreational runners. And despite the significance of the phenomenon, consensus has yet to be reached on a precise conceptual or operational definition; see [ 15 , 16 ]. It is usually framed as a fatigue and fueling problem [ 7 , 17 , 18 ]: simply put, if an athlete runs out of the energy they need to fuel their remaining race, then they will have to slow or even stop. However, the relationship between fatigue and performance is not a straightforward one, and the topic continues to be a source of debate in the literature. In what follows, we review related work on fatigue, pacing and performance, as it relates to the phenomenon of hitting the wall in the marathon, in order to frame the work presented in this study.
Historically, fatigue can mean different things to different disciplines [ 17 , 18 ]: a physiologist might view fatigue as the failure of a specific physiological system [ 19 ]; biomechanists may view it in terms of a decrease in the force output of muscles [ 20 , 21 ]; while a sports psychologist will typically view fatigue as the ‘feeling’ of tiredness [ 22 , 23 ]. It is not surprising, therefore, that research into fatigue-induced changes in exercise performance involves several different disciplines and perspectives, and has led to the development of several different models to explain the fatigue response that arises from prolonged exercise.
For example, Noakes [ 17 ] and Green [ 19 ] discuss how the cardiovascular/anaerobic model assumes that fatigue occurs when the cardiovascular system is no longer able to supply the necessary oxygen to, or remove waste products from, the working muscles; see also [ 24 ]. A related model is the energy supply/energy depletion model [ 17 , 19 , 25 ], which proposes that fatigue is the result of two mechanisms: (1) a failure to provide sufficient ATP to the working muscles, via the various metabolic pathways; and (2) a fueling problem, due to the depletion of fuel substrates, namely muscle and liver glycogen, blood glucose and phosphocreatine [ 8 , 9 ].
Alternatively, the neuromuscular fatigue model links fatigue with a diminished muscular response to electrical stimulus as a result of prolonged exercise [ 17 , 20 , 25 – 27 ], while the muscle trauma model proposes that fatigue is a consequence of the type of muscle damage [ 28 , 29 ] that commonly occurs during prolonged exercise (muscle swelling and stiffness, or the tearing of muscle fibres etc.). The motivational model of fatigue is based on a lack of interest in exercise performance, akin to losing the will to perform [ 22 , 30 , 31 ]. While it is often incorporated into the neromuscular model of fatigue and the central governor model (see below), the motivational model uniquely holds that neuromuscular function is intentionally down-regulated, rather than subconsciously altered.
In the central governor model Noakes [ 32 ], Noakes et al. [ 33 ], and Ulmer [ 34 ] argue that exercise performance is controlled by a governor located in the central nervous system, which uses signals and feedback from muscles and other organs to regulate exercise performance, in order to protect vital organs from injury or damage. More recently, Lambert et al. [ 13 ] and Gibson & Noakes [ 35 ] have extended the central governor model by proposing the complex systems model of fatigue. This model integrates a variety of peripheral signals and sources of feedback, in a non-linear manner, in order to regulate activity to allow for the completion of a given bout of exercise. Accordingly, fatigue is a subconscious sensation that reflects the underlying state of this integrative process.
In marathon running, the phenomenon of hitting the wall is associated with the rapid onset of debilitating fatigue and, as the above viewpoints suggest, it may arise from a combination of factors including inadequate fueling, a lack of training, or a diminished intentional state. Recently Rapoport’s energy model [ 7 ] has been developed with marathon running in mind, and it offers an opportunity to predict when a runner will become fatigued based on their energy stores and pace. The model is based on the premise that it takes approximately 1 calorie to move a runner per kilo of body mass and per kilometer of running, regardless of pace [ 36 , 37 ]. Rapoport’s model extends this by considering: (a) the source of energy—fat vs. carbohydrates—with per-km energy expenditure varying, not by pace, but by the source of the energy; and (b) the amount of carbohydrates available. Romijn et al. [ 38 ] discuss how faster runs are fueled by a greater proportion of carbohydrates than fat. Whether a runner will hit the wall depends on how quickly their glycogen stores deplete, which Rapaport found depends on a combination of a runner’s aerobic capacity (or VO 2 max ), the density of muscle glycogen, and the relative mass of their leg musculature. Hagen et al. [ 39 ] report that a higher aerobic capacity leads to a faster marathon, provided there are adequate glycogen stores, while Fairchild et al. [ 40 ] note that larger leg muscles, relative to body mass, are associated with a higher percentage of VO 2 max that can be sustained, because a lower body mass means a lower running energy cost, and larger leg muscles mean more room to store glycogen. The utility of this model is that it can be used to estimate the distance at which runners will exhaust their glycogen stores as a function of pace, thereby providing a basis for optimising the performance of endurance runners and predicting mid-race fueling needs.
In conclusion, fatigue is an inevitable consequence of the marathon distance, and the need for in-race fueling is a necessary response to the natural limits of the human body’s energy stores. Together, fatigue and depleting energy reserves can conspire to dramatically slow even the swiftest runner, when they hit the wall, and, in what follows, we will consider the further implications of this for pacing and performance.
Pacing in endurance events is an important research topic, particularly when it comes to understanding the optimal pacing strategy for a given event type. For example, Tucker et al. [ 41 ] examined the pacing strategies of male runners in world-record performances to show how pacing strategies varied with distance. Shorter events were characterised by fast starts, followed by progressive slowing, while 5,000m and 10,000m events were associated with fast starts and fast finishes, with a period of slower running during the middle of the race. March et al. [ 42 ] conclude that more even pacing tends to be associated with faster finish-times in the marathon, with females associated with more consistent pacing than males, even when the effects of ability and age were controlled for [ 43 – 46 ]. Tucker & Noakes [ 47 ] emphasise how pacing can be impacted by many different factors. For instance, the work of Trubee [ 48 ] found that pacing difference between the sexes increased with temperature; see also the work of Cuk et al. [ 49 ].
Smyth [ 10 ] examined more than one million marathon race records, of mostly recreational runners, to explore the relationship between starting and finishing paces, and overall race performance, in the marathon. The conventional wisdom is that starting too fast can create pacing problems later in the race—including hitting the wall—but, equally, finishing too fast may signal that a runner has paced too conservatively. Starting or finishing too fast was found to be associated with slower overall finish-times, as partly predicted by Denison [ 50 ]. Indeed, fast starts were found to be especially injurious to performance, in part because they increased the likelihood that a runner would go on to hit the wall later in the race.
More recently, the work of Oficial-Casado et al. [ 51 ] considered differences in pacing profiles in four big-city marathons (Valencia, Chicago, London, and Tokyo) to find that differences between corresponding sections of these races tended to increase with finish-time increases. In particular, the pacing of the first 5km of the races analysed differed significantly, with London having the fastest first 5km and also the greatest difference in relative speed between the first and second half of the race. These results, underscore pacing differences that can exist between races and highlight the importance of accounting for race pacing characteristics when selecting a marathon and a suitable pacing strategy.
Despite what is known about how runners pace their races, the related phenomenon of hitting the wall appears to be less well understood. One reason for this might be because the phenomenon remains relatively rare among elite runners—the usual targets of performance studies—even though many recreational marathoners do confront it at some stage in their marathon history [ 1 , 2 , 12 ].
Some of the literature that does exist focuses on the perceptions, expectations, and cognitive orientations of runners who hit the wall. For example, one early study by Summers et al. [ 2 ] surveyed 363 middle-aged, recreational, first-time marathoners to evaluate their reasons for attempting the marathon, their perceived outcomes from the event, and their experiences during the race. Overall, 56% of respondents reported hitting the wall, with just over 73% of them experiencing it after the 19 mile (30km) mark. In related work by Stevinson & Biddle [ 1 ], the focus was on the relationship between a recreational runner’s cognitive orientation and hitting the wall. The 66 participants (56 males and 10 females) in this study were all entrants into the 1996 London marathon, and the sample included 35 marathon first-timers. Of the 53% who reported hitting the wall—more males than females—they were much more likely to adopt a cognitive orientation of ‘inward distraction’ and a sense of internal disassociation as they attempted to distance themselves from the task at hand.
Buman et al. [ 11 ] produced a more in-depth study of the phenomenologcial characteristics of hitting the wall, based on a survey of 315 runners, to assess whether they felt they had hit the wall and, if so, their perceptions of 24 different characteristics linked to the experience. Once again, a high proportion (43%) of respondents reported hitting the wall and the study concluded that four characteristics—generalised fatigue, unintentional slowing, a desire to walk, and a shifting focus on survival—were especially salient. However, surprisingly, only 70% of those who reported hitting the wall also reported a concomitant slowdown. In related work, Buman et al. [ 14 ] looked at the relationship between the risk profile of runners and when they are likely to hit the wall, in order to describe the overall functional form of risk over the course of a marathon. The sex of a runner, their training volume, and their race expectations were found to play important roles in predicting whether someone would be likely to hit the wall, with the risk peaking at mile 21 followed by a steep subsequent decline; see also [ 1 , 12 ].
These studies provide useful reference rates for hitting the wall among recreational runners, although it seems unwise to conclude that more than 40–50% of all recreational runners will actually hit the wall in a given race, in practice. It is more likely that the methodology used by these studies might elicit an over-reporting of the phenomenon, especially if many less experienced runners conflated the usual late-race feelings of fatigue, and a natural slowdown, with the idea of hitting the wall. If there was no material deterioration in pace for up to 30% of those who claimed to have hit the wall as per Buman et al. [ 11 ], then it seems doubtful that they actually did experience the phenomenon. Indeed, if hitting the wall is seen as a rite of passage for marathoners, then using the phenomenon to justify a disappointing performance may prove to be all too tempting and common. An alternative explanation for the lack of a reported slowdown could be that some respondents simply did not report the unintentional slowing of pace as a major factor, even though it did occur. Either way, the potential objectivity shortcomings of these self-reporting studies speak to the additional value that may be provided by a more evidence-based pacing study, such as the one presented here.
This study is based on an original dataset of marathon race records. All of the data is publicly available from the corresponding marathon websites and a complete list of URLs of these web-sites is provided in S1 Table in the supporting information to this article. The research was approved as being exempt from a full ethical review by the Human Research Ethics Committee (Sciences) at University College Dublin on the grounds that it involves the anonymous analysis of public data. This section describes this dataset in detail, explains the approach used to determine when a runner hits the wall, and discusses how this can be used to compare runners who hit the wall based on their sex, age, and ability.
The data for this study was incrementally collected between 2015 and 2019. The resulting dataset includes 4,183,362 race records for an estimated 2,743,322 unique runners, from 270 races that took place in 38 cities during the period from 2005 to 2019. Each race record is associated with a runner name, age information, and an indication of whether a runner was male or female. We refer to this as the original dataset. For reasons discussed below, the main analysis in this study is conducted on a subset of this original dataset, by focusing on runners who are associated with multiple race records. We refer to these as repeat runners and to their data subset as the repeaters dataset. This subset contains 2,179,221 race records (approximately 52% of the race records from the original dataset) for 717,940 unique runners (approximately 26% of the original dataset’s unique runners).
The original dataset includes marathons that provide timing data for 5km race segments (0–5km, 5–10km, …, 35–40km, plus the final 40–42.195km segment); the requirement for 5km segments is based on the need to track changes in pacing during different stages of the marathon. Note that we refer to each 5km segment by its end-point, thus the 10–15km segment is the 15km segment; the exception is the shorter 40–42.195km segment, which is called the final segment. This means that each complete race record includes 9 separate segment times.
The type of age information provided varies from marathon to marathon. Sometimes precise age (or year of birth) information is included, but often it is limited to age ranges or categories. To maximise the availability of age information across the entire dataset, in this study we rely on the following age ranges, 20–39, 40–44, 45–49, 50–54, 55–59, 60+, which are either directly available from, or can be derived for, all of the race records in the original dataset.
Summary details of this original dataset are presented in Table 1 for each marathon, showing the number of participants, the percentage of female participation, the mean and standard deviation of finish-times (mins), and the percentage of participants who are deemed to have hit the wall, based on the definition developed below. In addition, a further summary table is provided by Table 2 showing similar data based on age group.
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The repeaters dataset is summarised in a similar manner in Table 3 . It includes runners with more than one race record in the original dataset. The reason for this is that our analysis of how runners hit the wall relies on an estimate of their ability and we use an estimate of their recent personal-best time for this. As above, Table 4 shows these statistics based on age group.
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We identify repeaters by matching race records based on a combination of a runner’s name identifier, sex, and age. Precise age information (or year of birth) is used when available, otherwise age ranges are used. Infrequently, this approach incorrectly matches runners with the same name, age, and sex, who are competing in a single race and such ambiguous matches are excluded. This approach is estimated to be sufficient to identify a large fraction of legitimate repeaters from the original dataset.
For the purpose of this study, we determine a runner to have hit the wall if they experience significant slowing for an extended period during the second half of the race; this is similar to the pacing-based definition of hitting the wall developed by Berndsen et al. [ 15 ]. Obviously, this is an imperfect measure of whether a runner truly hits the wall. It will both overestimate and underestimate the true number who hit the wall; for example, some runners will slow due to injury or lack of training/fitness, rather than because they genuinely hit the wall, while others may hit the wall too late in the race to be identified. Nevertheless, this approach should be sufficient to provide an estimate that is good enough to use at scale in this analysis.
To better understand the relationship between the fraction of runners hitting the wall, according to this definition, and the DoS and LoS thresholds, we conduct a sensitivity analysis to evaluate different ranges for these parameters. We use the full original dataset for this particular analysis, since it does not rely on repeat runners, and the results inform the selection of suitable DoS and LoS values to use in the remainder of our analysis.
It is important to note that this estimate of a runner’s recent PB time may not be their true recent PB time, if their PB race is missing from our dataset; we discuss this further when we consider the limitations of this study. These recent PB times are also used to estimate the cost of hitting the wall ( Eq 6 ), by calculating the difference between a runner’s finish-time, when they hit the wall ( HTW Time ), and their recent PB Time ; see Eq 5 . For example, if a runner achieves a finish-time of 275 minutes when they hit the wall, and if their recent PB is 235 minutes, then we estimate the cost of hitting the wall to be 40 minutes, or a relative cost of 0.17 indicating a 17% finish-time loss; see Eq 7 .
Using the repeaters dataset, we compare runners based on their sex, age range, and ability level (estimated PB time in 30-minute intervals), to answer the following research questions, using the metrics defined above:
We use a combination of unequal variance t tests and χ 2 tests of proportions to evaluate the significance of the differences observed between male and female runners (within a given age group or ability level) and to evaluate the significance of the differences observed for male and female runners for successive age groups and ability levels. In each case a significance threshold of p < 0.01 is used to determine significance with Cohen’s d used to measure effect size for t tests and the odds ratio ( OR ) for χ 2 tests. Where relevant, we will also use a Wald test with t-distribution as the test statistic, to evaluate if the slope of a linear regression line is different from 0—to evaluate a trend—using a significance threshold of p < 0.01 with r 2 as the corresponding effect size. In Figs 2–6 the statistical significance of the results is encoded in the following ways:
The raw data for each result graph and the corresponding statistical analysis results are available as S1 Datasets .
The sensitivity analysis results in Fig 1 show how the proportion of runners hitting the wall changes in a predictable manner for different DoS and LoS thresholds. As expected, larger slowdowns over longer distances correspond to smaller proportions of runners hitting the wall. For the purpose of this study we define hitting the wall using a slowdown ( DoS ) threshold of 0.25 and a minimum distance ( LoS ) threshold of 5km—that is, runners must slow by at least 25% for at least 5km—which corresponds to 34% of runners in the original dataset hitting the wall, as indicated in Fig 1 . These thresholds are comparable with similar thresholds reported by Berndsen et al. [ 15 ] where slowdowns of approximately 17% over more than 5km were proposed to identify runners hitting the wall.
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This proportion of runners hitting the wall also conforms with reasonable expectations about how many marathoners hit the wall in practice. Although this is lower than the proportions (40–50%) reported by [ 1 , 2 , 11 ] using self-reported, post-hoc surveys of runners, as we shall see in the following section, the proportion of runners hitting the wall depends on ability and more than 40% of male runners with slower PBs do hit the wall based on the definition used here.
Finally, it is worth noting that minor changes in these thresholds do not substantially change the nature of the results. Later, in a discussion of the limitations of this analysis, we will discuss this aspect in more detail and supporting evidence is available in S1 – S14 Figs.
Fig 2 shows the proportion of runners hitting the wall based on sex, age group, and ability level. Overall 28% of male runners hit the wall compared with only 17% of female runners, χ 2 (1, N = 1, 928, 813) = 27, 693.34, p < 0.01, OR = 1.43, and while ability level clearly influences the proportion hitting the wall, age plays a more modest role.
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In Fig 2(a) there is evidence that younger runners are more likely to hit the wall, with HTW Proportions reaching a low-point for the 45–49 age group. The effect size associated with the differences between males and females remain high for each age group, 1.79 ≤ OR ≤ 2.0, while the effect size between successive age groups for males and females is more modest, 0.93 ≤ OR ≤ 1.17.
Fig 2(b) shows how the proportion of runners hitting the wall increases steadily with recent PB times between 3 and 5–5.5 hours. All of the differences between males and females, for each ability level, are significant with p < 0.01 and 1.9 ≤ OR ≤ 3.14 and a majority of the differences between successive (within-sex) ability levels are also statistically significant with p < 0.01 and 0.61 ≤ OR ≤ 1.69 for males and 0.65 ≤ OR ≤ 1.38 for females.
It is also interesting to see how HTW proportions vary in the years before and after a runner achieves their overall PB; note, here we are using a runner’s overall fastest finish-time in our dataset, rather than the recent (3-year) PB, used to determine current ability. In Fig 3(a) , races are aligned so that runners achieve their (overall) PB in year 0 and then we calculate the HTW proportions for up to 9 years before and after this PB year; there are of course fewer runners available the farther we move from their PB year, and some runners with more distant races (>9 years from PB) are obviously not included. The results indicate that, in the three years before or after a runner achieves their PB, they are significantly more likely to hit the wall, compared with earlier or later years, respectively.
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This is summarised in Fig 3(b) , as the aggregate proportion of male and female runners hitting the wall in the 3 years before and after a PB, compared to 4–9 years before and after a PB. For example, 1–3 years before achieving an overall PB, 40% of male runners hit the wall, compared to just under 26% in the 4–9 year period before achieving the PB, χ 2 (1, N = 338, 057) = 6, 165.03, p < 0.01, OR = 1.25. Likewise, 28% of female runners hit the wall in the 3 years before a PB compared with 16% in earlier years, χ 2 (1, N = 171, 387) = 2, 503.39, p < 0.01, OR = 1.50. A similar result is observed for male and female runners in the years after achieving a PB too.
It is also worth noting that the differences between the proportions of male or female runners who hit the wall in the 1–3 years before their PB (40% and 28% for males and females, respectively) is significantly larger that the corresponding proportion of runners hitting the wall in the 1–3 years after their PB (32% and 21% for males and females, respectively) with χ 2 (1, N = 494, 211) = 3, 626.53, p < 0.01, OR = 1.10 for males and χ 2 (1, N = 260, 747) = 1, 835.09, p < 0.01, OR = 1.22 for females.
Thus, proximity to a PB represents a significant risk factor in terms of hitting the wall for male and female runners, and the risk is higher just before achieving a PB than it is just after a PB. This is likely due to more runners adopting more aggressive pacing as they attempt to secure a new PB and we will consider this further in the discussion section of this paper.
For completeness, Fig 4 groups runners based on their age (<40 vs. ≥40) and overall PB times (<4 hours vs. ≥4 hours), to explore whether there is an age or ability effect, when it comes to HTW risk in the years before and after a PB. Similar spikes in HTW Proportion are evident in all 4 groupings. Younger (<40 years-old) and slower (≥4 hour finishes) runners are the most at risk in close proximity to a PB; for example, more than 50% of younger and slower male runners hit the wall the year before their PB as per Fig 4(c) . On the other hand, older (≥40 years-old) runners with <4 hour finish-times are the least at risk, with the proportion of HTWs peaking at just over 30% for males; see Fig 4(b) . Once again we observe a similar pattern of statistically significant differences: (i) a greater proportion of males hit the wall than females in each cohort; (ii) the proportion of runners hitting the wall increases significantly in proximity to a PB; and (iii) the proportion of runners hitting the wall is higher in the 3 years before a PB than in the 3 years after. The full dataset for these results is available in S1 Datasets .
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Fig 5a–5f show the dimensions of the wall in terms of the start of the slowdown ( HTW Start ), the duration or distance ( HTW Distance ) of the slowdown, and degree of the slowdown ( HTW Slowdown ), and how they relate to age and ability for male and female runners. On average male runners begin their slowdown slightly later (29.6km) than female runners (29.3km), t (475, 199) = 20.03, p <.01, d = 0.05. Males sustain their slowdown for longer than females (10.72km vs. 9.61km, respectively), t (475, 199) = 68.44, p <.01, d = 0.17. And, and on average the degree of slowdown for males is 0.40 compared with 0.37 for females, t (475, 199) = 60.20, p <.01, d = 0.15. However, although these are statistically significant differences the effect size is modest ( d < 0.2).
HTW Start refers to the average distance at which runners begin the slowdown that corresponds to their hitting the wall. HTW Distance refers to the length of this slowdown and HTW Slowdown refers to the degree of this slowdown, relative to their base-pace (that is, their average pace during the 5–20km portion of the marathon).
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Fig 5a, 5c and 5e show that age plays a very minor role in terms of the start, distance, and degree of slowdown, but there is a stronger relationship between these metrics and ability. A Wald test confirms a non-zero slope of the regression line between these metrics and estimated PB time, for male and female runners, r 2 (7)>0.69, p < 0.01, except in the case of the degree of slowdown of female runners ( p = 0.31). The differences between male and female runners for each ability level are, generally speaking, statistically significant based on Welch’s t test ( p < 0.01) but the mean effect size for HTW Start is very small ( d = 0.10±0.11) compared with d = 0.35±0.09 for HTW Distance and d = 0.20±0.08 for HTW Slowdown .
Thus, we can conclude that while a runner’s ability and sex influences how they hit the wall (the start, duration, and degree of slowdown) the differences observed are generally small, with males slowing by a little more, and for slightly longer distances, than females. It is worth noting that this longer distance for males implies that females are more likely to recover from their slowdown before the end of the race, which is consistent with results reported by Smyth [ 10 ] showing that females are more likely to finish faster than their mean race-pace than males.
While it is straightforward to evaluate the finish-time of a runner when they hit the wall, it is less clear what their finish-time would have been had they not. We cannot replay the race without them hitting the wall, for example, but we can at least estimate their lost minutes ( HTW Cost ) by calculating the difference between their finish-times when they do hit the wall ( HTW Time ) and their recent estimated PB times, as in Eqs 6 and 7 .
Not surprisingly, the mean HTW Time of males (277.44 minutes) is significantly faster than for females (307.28 minutes), as indicated by the horizontal mean lines in Fig 6a and 6b ; t (475, 199) = −179.76, p < 0.01, d = 0.44. In Fig 6(a) we can see that this difference is preserved across all age groups ( d = 0.65±.08 for these age groups) and how HTW Time tends to increase with age, and more noticeably for older runners.
HTW Time refers to the finish-time in minutes when a runner hits the wall. HTW Cost refers to the difference between a runner’s HTW Time and their estimated PB time. Rel HTW Cost refers to a runner’s HTW Cost as a fraction of their PB time.
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However, these sex differences are less apparent when we group runners by ability (recent PB times) as shown in Fig 6(b) ; note how the slower mean finish-times of females is accounted for by an increasing number of runners in the slower PB ranges. As expected, HTW times increase monotonically with recent PB times and runners of a given ability tend to experience a similar HTW time when they hit the wall; there continues to be a modest but statistically significant difference between males and females, for each ability level, but the effect size is trivial, d = 0.09±0.11.
The cost implications of hitting the wall are shown in Fig 6c–6f . Overall, males suffer from a smaller average finish-time cost than females, 31.50 minutes vs 33.20 minutes, respectively— t (475, 199) = −19.78, p < 0.01, d = 0.05 —but the effect size is clearly very small. However, there is a strong linear relationship between HTW Cost and ability; see Fig 6(d) . Using a Wald test to confirm a non-zero slope for the linear regression lines we find r 2 (7) = 0.91, p < 0.01 for males and r 2 (7) = 0.81, p < 0.01 for females. The relationship is even stronger when we account for the cost of hitting the wall as a fraction of PB time in Fig 6(f) , r 2 (7) = 0.93, p < 0.01 for males and r 2 (7) = 0.99, p < 0.01 for females.
Thus, faster runners tend to experience a greater finish-time cost than slower runners. However, it must be recognised that this does not mean that faster runners slow by more or for longer than slower runners when they hit the wall. We know from the previous section that slower runners tend to begin slowing earlier and for longer than faster runners, and they slow down by a greater degree too. Thus, the greater finish-time cost experienced by faster runners is due to their proportionally faster PB races, compared with the PBs of slower runners.
It is also worth remarking on the fact that male runners experience a greater relative cost than female runners, for a given age group— Fig 6(e) —yet this is not the case when we compare them based on ability, as in Fig 6(f) . This is likely due to physiological differences between male and female runners, which are responsible for faster finish-times for the former. It means, for example, that a female runner with a 3-hour PB time is not equivalent to a male runner with a 3-hour PB time; all other things being equal the female runner will be achieving a higher level of relative performance than the male runner. In the past, some researchers have compensated for this by reducing female finish-times [ 46 ]. When we apply a 30-minute adjustment—that is, by reducing female times by 30 minutes—then the relative HTW costs for females drop below those of males, as indicated by the dashed line in Fig 6(f) ; the differences between males and these adjusted female values remain statistically significant. Thus, while there is some evidence to suggest that females experience a greater finish-time cost than males, when they hit the wall, the effect size is very small and complicated by confounding physiological differences between male and female runners.
The results presented here show that male runners are significantly more at risk of hitting the wall than females. This is consistent with the existing literature on pacing differences between male and female runners [ 43 , 45 , 52 ] and on the literature about hitting the wall itself [ 1 , 14 ]. It can be explained, in part at least, by the tendency of males to take more pacing risks; see for example recent work by Hubble et al. [ 53 ], in which male runners were found to consistently overestimate their marathon abilities, leading to more aggressive and risky pacing strategies.
The finding that runners are much more likely to hit the wall in the years directly before a PB appears to be a novel one, and may also be explained by risk-taking behaviour and sub-optimal pacing decisions when runners are chasing a PB . This is also consistent with the similar spike in the proportion of runners hitting the wall in the 3 years directly after achieving a PB, as some runners continue to try to improve their PB time, perhaps encouraged by their recent PB success. However, the fact that the post-PB spike is significantly less than the pre-PB spike suggests that at least some runners are satisfied to return to safer pacing patterns having achieved a new PB. This highlights the delicate balance that exists between racing hard (to secure a PB) and avoiding pacing problems later in a race, and is consistent with other work on the risks associated with starting a marathon too fast, as reported by Smyth [ 10 ], and recent work by Deaner et al. [ 54 ] showing aggressive pacing to be a strong predictor of subsequent slowing. That the increased risk of hitting the wall, in the years before and after a PB is greater among male runners is also consistent with the tendency of males to engage in more risky pacing as reported by Hubble et al. [ 53 ]. Of course pacing may also be impacted by the topology and conditions of a particular course and event. Recent work by Oficial-Casado et al. [ 51 ] shows that the pacing profiles associated with different marathons differ based on finish-time categories and it is plausible to conclude that some courses may be more susceptible to runners hitting the wall than others.
A second novel contribution of this work concerns the finish-time costs associated with hitting the wall. The existing literature remains largely silent on this feature of the phenomenon, perhaps because of the difficultly in determining what might have been a reasonable finish-time for a runner had they not hit the wall. Also, many past studies have focused on incidents of hitting the wall in isolated races or a small set of races [ 1 , 11 , 14 , 16 ], rather than by tracking the performance of runners over an extended series of races. The scale of the dataset used in this study makes it feasible to consider a runner’s (partial) marathon history and, as such, provides an opportunity to use an estimate of runner’s recent PB as a benchmark against which to evaluate the cost of their hitting the wall. Finding that faster runners experience a greater HTW Cost is surprising at first, because it suggests faster runners slow more when they hit the wall. However, since HTW Distance and HTW Slowdown increase with PB time ( Fig 5d and 5f ), this means that the higher HTW costs for faster runners must be due to proportionally faster PB times rather than slower HTW times. This is consistent with research highlighting sub-optimal pacing by slower runners [ 42 ] in general, and may indicate that, all other things being equal, the PBs of slower runners are less optimal than the PBs of faster runners, even allowing for ability differences.
Although this paper highlights a well-known disparity between the proportion of male and female runners hitting the wall, the results also show that, when runners hit the wall, they do so in a broadly similar manner with similar consequences. This of course speaks to a common mechanism underpinning the phenomenon, while the different proportions of male and females hitting the wall emphasises critical differences in their risk-taking behaviours, when it comes to pacing. In this regard at least, runners and coaches have the potential impose some level of control on whether a runner will hit the wall, by focusing on making better pacing decisions and by being aware of the increased pacing risk that exists, for males in particular, and for all runners when they are pursing a PB.
As with any study of this nature, there are a number of assumptions and limitations worth discussing. First and foremost, this work relies on a particular definition of hitting the wall that is purely based on in-race pacing. In reality, hitting the wall is a multi-factorial phenomenon, which reflects a complex set of interactions between training, fitness, pacing, nutrition, and race-day conditions, and, as such, the model used here cannot capture the full complexity of the phenomenon. Nevertheless, we propose that it is reasonable and useful to consider significant late-race slowing as a proxy for hitting the wall, as others have done [ 15 ]. Although not every single slowdown can be explained by the runner hitting the wall (e.g. under-training, injury, or simply “giving up” can provide alternative explanations), runners who do hit the wall can be expected to slow significantly. Certainly, this model can be improved by incorporating additional sources of data, such as heart-rate data, for example, which may facilitate more accurate judgements about whether a runner has hit the wall. Although such data was not available in our dataset, the increasingly widespread adoption of mobile devices, smart-watches, and wearable sensors [ 55 , 56 ] has the capacity to generate large volumes of additional data (heart-rate, cadence, and power), which may be useful in this regard in the future [ 57 , 58 ]. Already, the availability of such diverse sources of data is enabling several new types of health and fitness applications [ 59 – 63 ] and the emergence of powerful new machine learning techniques has been used to support a variety of related prediction and planning tasks in several sporting domains [ 64 – 73 ]
It is also worth noting that the model of the wall analysed here is defined by a pair of parameters—degree of slowdown and length of slowdown—with specific values—0.25 and 5km, respectively—and it is reasonable to question whether the results would be different if different values had been chosen. We have considered several alternative sets of values and, within reasonable levels of tolerance, there is no material change to the nature of the results as presented. These additional results are available as S1 – S14 Figs.
Another limitation of the approach is that, although we have collected a large corpus of race records, it does not provide a complete account of the marathon history for many, if not most, runners. This undermines our estimation of runner ability, because it relies on the fastest available finish-time for a runner during a recent race as their recent PB time estimate. Their true recent PB time may be associated with a race that is not in our dataset and thus we can expect our PB estimates to underestimate (be slower than) a runner’s true PB. Thus our estimates of the cost of hitting the wall may also underestimate the true cost of hitting the wall. However, because the dataset used in this study is based on many of the largest marathons in the world we propose that it is likely to provide a reasonably accurate estimate of the PB times of runners, because runners are more likely to train for, target, and achieve PBs at these landmark races. Even if the PBs used here are not always true PBs, it is likely that they will correlate closely with true PBs and, as such, the trends observed, and the relative differences found, can be expected to be reasonable.
The dataset is also limited in terms of the pacing precision that it provides. For instance, the availability of 5km segment times/pacing limits the granularity with which we can explore the nature of the wall. Using more fine-grained pacing data, such as that collected by smartwatches or GPS apps, it will be possible to provide much more fine-grained insights into what it means when runners hit the wall; see for example [ 15 ]. A similar lack of precision exists for much of the age data that is provided. Although some marathons provide access to precise age (or year of birth) data, most use age ranges. This limits the precision of our age-related analyses. Nevertheless, the results suggest that, when it comes to hitting the wall, age is less important than sex or ability and, as such, it is unlikely that more fine-grained age data would reveal results that are significantly different from those reported.
We have described the results of a large-scale data analysis, focused on the marathon race records of recreational runners in big-city marathons, in order to better understand when and how runners hit the wall. The key findings include:
Despite the limitations inherent in this work—a purely pacing-based definition of the wall with limited pacing precision (5km splits) and age precision (age ranges) and a finite and incomplete dataset of race records—the work is expected to be of interest to sport scientists, coaches, and runners alike, especially in the area of recreational marathon running.
S1 table. list of marathon data sources..
A table containing all of the URLs of the marathon web-sites used as a source of data for this study. Typically marathons maintain an archive of past race results either accessible directly via a web interface linked to from the main marathon website, or accessible via the websites of third-party timing services. A minority of marathons provide access to data which can be downloaded in bulk, while a majority provide access to their results via a search-based interface and in a page-based format. The data obtained used in this study were obtained directly from result archives between 2015 to 2019.
https://doi.org/10.1371/journal.pone.0251513.s001
Each individual result graph is associated with 4 different comma-separated files: (i) Raw —the (anonymised) raw data behind the means and standard deviations used for a particular result graph; (ii) Paired —the paired statistical significance results; (iii) Successive Male —the statistical significance results to compare successive groups (age and ability) for male runners; and (iv) Successive Female —the corresponding results for the statistical significance tests to compare successive groups (age and ability) of female runners.
https://doi.org/10.1371/journal.pone.0251513.s002
https://doi.org/10.1371/journal.pone.0251513.s003
https://doi.org/10.1371/journal.pone.0251513.s004
https://doi.org/10.1371/journal.pone.0251513.s005
https://doi.org/10.1371/journal.pone.0251513.s006
https://doi.org/10.1371/journal.pone.0251513.s007
https://doi.org/10.1371/journal.pone.0251513.s008
https://doi.org/10.1371/journal.pone.0251513.s009
https://doi.org/10.1371/journal.pone.0251513.s010
https://doi.org/10.1371/journal.pone.0251513.s011
https://doi.org/10.1371/journal.pone.0251513.s012
https://doi.org/10.1371/journal.pone.0251513.s013
https://doi.org/10.1371/journal.pone.0251513.s014
https://doi.org/10.1371/journal.pone.0251513.s015
https://doi.org/10.1371/journal.pone.0251513.s016
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Amir khorram-manesh.
1 Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, 413 45 Gothenburg, Sweden
2 Research and Development Unit, Swedish Armed Forces Defense Medicine Centre, 426 05 Gothenburg, Sweden
3 Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
4 Department of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
5 Department of Food, Nutrition and Sport Science, Sahlgrenska University Hospital, 405 30 Gothenburg, Sweden
6 Department of Environmental and Life Sciences, Karlstad University, 651 88 Karlstad, Sweden
7 Department of Earth Sciences, University of Gothenburg, 405 30 Gothenburg, Sweden
Eric carlström.
8 Institute of Health and Care Sciences, Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
9 School of Business, University of Southeast Norway, 3679 Notodden, Norway
Among several serious medical conditions, arrhythmia and heat stroke are two important causes of death during endurance races. Clinically, collapsing might be the first sign of these serious conditions and may mimic the more common and benign exercise-associated collapse. Several risk factors have been reported in the literature. We aimed to conduct a qualitative study to find a perceived risk profile among runners who collapsed and who were transported by ambulances to the nearest hospital during Gothenburg’s half marathon (2010–2017). Collapsing runners seem to lack the ability to make a decision to withdraw from the contest despite being exhausted. They feel the pain, but are unable to put meaning to their feeling, to adjust their pacing, and to handle other influences. Consequently, they do not overcome the problem or assess the situation. These individual mental characteristics may indicate a unique profile for collapsing runners. Pre-race health control and educational initiatives aiming at mental preparedness and information before endurance races might be a necessary step to avoid life-threatening complications.
Although most people begin running to improve their physical fitness, personal challenges have proven to be the main reason for taking part in a running contest [ 1 , 2 ]. Running a half or full marathon can be enjoyable and raises the feeling of self-satisfaction; however, it may also contribute to medical encounters with adverse outcomes [ 2 , 3 , 4 , 5 ]. Among many serious and life-threatening medical complications such as ischemic heart disease; serious metabolic complications; serious heat-related disorders; and serious fluid, electrolyte or acid–base abnormalities, arrhythmia and heat stroke are two less common causes of death during endurance races [ 3 , 4 , 5 ]. Clinically, collapsing might be the first sign of these serious conditions and may mimic the more common and benign exercise-associated collapse (EAC) [ 3 , 5 ], which is believed to be the result of a combination of postural hypotension and blunted reflex activity [ 6 ]. Several individual or environmental factors can influence EAC.
Running technique or pacing is the ability of the athletes to distribute their energy equally throughout the long-distance race and can vary depending on the individual [ 7 , 8 ]. Previous studies have shown that this ability is more developed among the experienced athletes, who can also adjust their energy use before their body temperature rises to high levels [ 8 , 9 , 10 ]. Many factors such as knowledge about the length of the race, ambient air temperature, and topography can influence runners’ pacing and consequently the energy distribution. Wrong pacing can result in a collapse [ 10 , 11 ]. Another component of the running technique is training load. Previous studies have shown that at least 30 km training load per week before a marathon race decreases the risk for injuries [ 11 ]. There is, however, no information about the amount of training load needed to avoid a collapse.
Health conditions such as chronic diseases and viral infections influence the individual runner’s ability to complete a race [ 12 , 13 , 14 , 15 ]. Coxsackievirus with cold symptoms can result in myocarditis [ 16 , 17 ]. Rhinovirus influences the runner’s step, making the steps longer and slower and probably increases the risks for injuries, but it has not proven to affect the lung capacity and runners’ performance [ 12 , 13 , 14 , 15 ].
Several publications emphasize the importance of nutrition and carbohydrates intake days before endurance races and an extra load 2–4 h before the race to increase the performance [ 18 , 19 , 20 , 21 ]. Fluids, on the other hand, are necessary to compensate for the losses due to perspiration [ 19 , 21 , 22 , 23 , 24 ]. Many factors may influence the perspiration mechanism such as genetic predisposition, the ability to adjust to the heat, the intensity of physical activity, and the temperature itself [ 20 , 23 ]. Some studies recommend substitution of up to 50–80% of the total loss due to sweat [ 20 ]. However, intake of a more considerable amount of fluids may also have side effects such as gastrointestinal issues, and hypo- or hypernatremia [ 23 , 24 ].
Recent studies from Gothenburg show a significant correlation between air temperature and number of collapses, number of ambulance transportations due to collapses, and the number of runners who could not finish the race (Non-finishers = NF). These studies used a “physiologic equivalent temperature (PET)” index to estimate the impact of heat [ 25 , 26 , 27 ]. The PET index models the thermal conditions of the human body in a physiologically relevant way and includes all meteorological variables relevant for heat exchange between the body and its environment, i.e., air temperature, wind speed, atmospheric pressure, and mean radiant temperature. The latter describes the environmental radiative load on a person and is one of the essential meteorological variables governing the human energy balance and thermal comfort [ 25 , 26 , 27 , 28 ]. An increase in PET of one degree is correlated with an increase in the number of collapses of 1.8 times and the number of NF with 66% [ 25 ]. Another recent study indicated the possibility of predicting the location of collapses, based on the grade of exhaustion experienced by runners. The localization of ambulance pickups was correlated with the areas where runners experienced maximal exhaustion and collapsed [ 29 ].
Although several partly unexplained risk factors have been associated with EAC, qualitative studies dealing with this issue are scarce. Defining a runner profile or identifying specific risk factors may prevent medical encounters, and open up new research fields, thus contributing to a better understanding of collapses during endurance races; furthermore, it can enable future pre-race tests and education. We aimed to conduct a qualitative study to find a perceived risk profile among runners who collapsed and who were transported by ambulance to the nearest hospital during Gothenburg’s half marathon (2010–2017).
2.1. general information.
Gothenburg’s half marathon (Göteborgsvarvet = GV), is the world’s largest half marathon with over 45,000 competitors [ 29 ]. Although the number of participants may vary, around 450 to 2250 medical encounters can be expected during the contest, with the variation strongly dependent on weather-related factors. Most of these medical encounters (>90%) are moderate and can be treated on-site by the organizer’s medical crew. Around 59–85% of these cases are EACs, which typically occur once the athlete stops running. However, 2–4% of all medical cases requires ambulance transportation and care at the hospitals due to their serious nature [ 30 , 31 ].
The Gothenburg Ambulance Journal was used to identify all runners picked up by ambulance due to collapse (n = 164) [ 32 ]. Runners with incomplete journals, wrong address, or information were excluded (n = 80). Remaining 84 received the template by post, but only 30 answered. Of 54 who did not reply, 40% were unknown to the local post office, 40% have moved to other areas without leaving a forwarding address, and in 20%, no reason was found. Two out of 30 individuals were excluded later since their participation was confirmed to be before the study period. The remaining 28 were included and analyzed in this study. The results of the questionnaire were completed with semi-structured telephone interviews. Of 28 participants, 15 were excluded due to sickness or unwillingness to participate in the interview. Remaining 13 participants were interviewed.
A questionnaire was developed using the following keywords in a literature study: marathon, half marathon, risk factors, medical encounters, collapses, runners’ profiles, requiring ambulance. A group of multidisciplinary professionals (n = 7) with medical (sports medicine, surgery, prehospital care and physiotherapist) and non-medical backgrounds (urban climate, human thermal comfort, and crowd management) evaluated and edited the questionnaire. Free comments were allowed and categorized under the main topics. The final version of the questionnaire was approved and was sent out to all included participants. It included the following parts ( Supplementary material ):
In order to compensate for potential shortcomings in the questionnaire, to evaluate the response given by each participant, and to obtain spoken accounts, each responding runner was asked to take part in an interview. Exclusion criteria for interviews were (1) severe ongoing disease (defined as a medical condition that does not allow the patients to participate in an interview (one person with psychological disorder, and one with brain damage after cardiac arrest)); or (2) refusal to participate. The obtained information was transcribed and analyzed verbatim. The process of analysis was based on systematic text condensation and divided into two parts: analysis of the incident and analysis of influencing factors [ 34 ].
The ethical committee approved the study (No. 177-16). Each participant received information regarding the study, its aims, and the use of data upon participation. All participants signed a letter of consent before the interviews. They also received verbal information. In both cases, they were informed that their participation was voluntary and withdrawal from the study was possible whenever they desired.
3.1.1. personal information.
Convenient training air temperature for each runner (n = 28).
Shows the frequency and percent of hereditary diseases in the investigated population.
Hereditary | ||
---|---|---|
Hereditary Diseases | Frequency | Percent |
High blood pressure with or without medication | 7 | 41.2 |
Early myocardial infarction or stroke (<60 years of age) and other heart diseases | 3 + 1 | 23.5 |
Systematic diseases (Myelofibrosis, SLE, MS) | 1 + 1 + 1 | 17.7 |
Diabetes | 1 | 5.9 |
Pulmonary diseases, including asthma | 1 | 5.9 |
Regular medication for other diseases | 1 | 5.9 |
Total | 17 | 100.0 |
Six of 28 runners (21%) were transported and hospitalized. Two runners stayed one night and three stayed two nights at the hospital. Four of these runners had a sick leave of 2 to 3 days. One 30-year old runner suffered a cardiac arrest and brain injury and was treated at the intensive care unit followed by long-term neuro-rehabilitation. Two runners did not answer the question.
The interviews aimed to get a broader insight into some of the statements from the questionnaire. The runners had the opportunity to expand their narratives and report more in detail about their experiences. Each interview took around 40 min. The results were categorized as: the incident, runners’ characteristics and the perceived influencing factors leading to collapses ( Figure 2 ). Thirteen runners were included in the interviews, whose age, gender, and education were comparable with the larger population who replied to our questionnaire.
Shows most important factors influencing collapses, based on the questionnaire and interviews.
We aimed to conduct a qualitative study to find a perceived risk profile among runners, who collapsed, and who were transported by ambulance to the nearest hospital during Gothenburg’s half marathon (2010–2017). The most important influencing factors found in this study were mental status and the high demands on individual performance placed on each collapsed runner. Another result was the number of participants (36%) who had experienced collapses during running contests before the study and the number of participants (43%) who reported hereditary issues.
Runners’ tendency to collapse might indicate other mechanisms behind collapses than diseases and physical conditions. The interviewed participants claimed they continued the contest although their body signaled exhaustion. Although most of the runners who collapsed in our study were amateurs, they all had experiences of running contests. Most of them were well educated and highly confident about their capabilities. This population is similar to another study documenting the characteristics of 161 km ultra-marathoners, in which participants were mostly well- educated, middle-aged, married men who rarely missed work due to illness or injury, generally used vitamins and or supplements, and maintained appropriate body mass with ageing [ 35 ]. The participants described themselves similarly as stubborn, ambitious, disciplined and performance-oriented.
In another published study from 2016, ten runners volunteered to describe their experiences of withdrawal during an ultra-trail race underwent interviews to share common individual characteristics leading to withdrawal. Seven representative sequences were identified: feeling pain; putting meaning to those feelings; adjusting one’s running style; attempting to overcome the problem; other runners’ influences; assessing the situation; and deciding to withdraw [ 36 ]. Consequently, our results, as well as those represented in Hoffman’s reports, may indicate that runners with specific characteristics may lack the control mechanism to maintain these representative sequences. Thus, they feel the pain and have symptoms such as tiredness and dizziness, but cannot put meaning to the feeling, and have difficulties to adjust their running style (pacing), while trying to overcome their problems. Influenced by other factors such as other runners’ performance while passing by, and magnified by extrinsic factors such as public cheers and behavior, and air temperature and humidity [ 25 , 26 , 27 , 29 , 37 , 38 ], they may have difficulties in assessing the situation, continuing to run instead of quitting the race, and collapse [ 29 , 35 , 36 ].
Endurance races are still associated with morbidity and mortality [ 4 , 39 , 40 , 41 , 42 ]. Although the absolute risk of sudden death for the participants in an endurance race is low (0.5–1.5 cases/100,000 runners), the tragedy itself is magnified due to the involvement of younger runners [ 3 , 4 , 5 ]. In a study published in 2012, the median age among deaths was 41.5 years. Half of the deaths (14/28) occurred in runners under the age of 45. The most common cause of death was cardiac arrest due to inherited/congenital heart disease [ 40 ]. The main reasons for death among runners older than 45 years (93%) was myocardial infarction (n = 13) and atherosclerotic heart disease (n = 14). In our study, over 40% of participants had high blood pressure with or without medication, and an additional 25% had Cerebrovascular Disease (CVD). This constitutes a significant risk factor and higher morbidity and mortality rate since history of CVD together with other possible risk factors such as chronic diseases, chronic prescription medication, and history of collapse during a race, have all proven to be alarming signals. Consequently, the idea of risk assessment and pre-participations’ screening has emerged to capture runners view on their health condition [ 43 , 44 ].
Runners’ views on their symptoms and their medical history are important factors in preventing medical encounters in endurance races [ 29 , 45 ]. In one study, the authors evaluated the efficacy and feasibility of an online pre-race medical screening and an educational intervention program to reduce medical complications in long-distance races. They found that all medical encounters (including life-threatening encounters) were significantly lower after the introduction of the program, which also was feasible to perform [ 45 ]. Educational interventions do not necessarily need to deal with medical information. Knowledge about other factors such as the impacts of diseases, personal characteristics at risk, as presented in our study may be part of intervention programs in order to reduce medical complications. Existing and hereditary diseases, and unexpected medical conditions, found in our study, despite its size, are in accordance with earlier reports and confirm the need for a pre-race screening test before endurance contests.
It is shown that with an increasing air temperature above an optimum, performance decreases. The optimal air temperature can vary between runners due to the level of physical readiness. Higher air temperature has shown to be associated with a higher rate of runners withdrawing from the race and increased medical complications. The acceptable upper limit for many races is based on WBGT (wet bulb globe temperature) of 28 °C; however, the WBGT is an empirically-based index, which does not provide any detailed examination of the meteorological variables contributing to thermal stress and is consequently of limited diagnostic value [ 21 , 22 ].
One main limitation of this study was the low response rate in the questionnaire study, which was due to wrong or incomplete information. We have, however, been informed that registered runners can offer their start positions to other participants if they cannot take part in the race due to sickness or other private reasons. This change should be reported to the organizers at least 48 hours before the contest. Missing this mandatory task may result in names with no address or addresses with no names; an organizational problem that should be addressed.
Nevertheless, as an effect of the low response rate to the questionnaire and the qualitative characteristics of the study, no statistically significant data can be reported. There is a need for larger number of participants, ideally compared to a control group to determine the relative importance of a range of risk factors. The study, however, opens up new research fields and confirms the need for both quantitative and qualitative studies in this field.
Qualitative studies have the shortcoming of not being able to generalize to a population, but the results may be transferable and can provide researchers with new angles in front of a quantitative study. Considering the scale of the studied half-marathon (45,000 competitors and six years of data but only 164 runners picked up by ambulance due to collapse) a quantitative study will be extensive. It may benefit from tentative results provided by studies such as this one to verify or falsify
Collapsing might be the first sign of severe medical conditions and clinically mimic the more common and benign exercise-associated collapse. Several risk factors associated with severe collapses have been reported. However, other individual and mental characteristics may indicate a unique profile for runners who collapse. Pre-race health check-ups and educational initiatives aiming at mental evaluation, preparedness and information before endurance races might be a necessary step to avoid life threatening complications.
The following are available online at https://www.mdpi.com/2075-4663/8/1/2/s1 , Swedish questionnaire.
All authors were involved in planning of the study. A.K.-M., T.L. and E.C. collected data for this study. All authors read and analyzed the data and contributed to the conclusions. All authors have read and agreed to the published version of the manuscript.
This research received no external funding.
The authors declare no conflict of interest.
Exercise-associated collapse (EAC) commonly occurs after the completion of endurance running events. EAC is a collapse in conscious athletes who are unable to stand or walk unaided as a result of light headedness, faintness and dizziness or syncope causing a collapse that occurs after completion of an exertional event. Although EAC is perhaps the most common aetiology confronted by the medical provider attending to collapsed athletes in a finish-line tent, providers must first maintain vigilance for other potential life-threatening aetiologies that cause collapse, such as cardiac arrest, exertional heat stroke or exercise-associated hyponatraemia. Previously, it has been believed that dehydration and hyperthermia were primary causes of EAC. On review of the evidence, EAC is now believed to be principally the result of transient postural hypotension caused by lower extremity pooling of blood once the athlete stops running and the resultant impairment of cardiac baroreflexes. Once life-threatening aetiologies are ruled out, treatment of EAC is symptomatic and involves oral hydration and a Trendelenburg position – total body cooling, intravenous hydration or advanced therapies is generally not needed.
https://doi.org/10.1136/bjsports-2011-090378
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Endurance sports are increasingly popular with over 500 000 participants in marathon running events in 2010. 1 After marathon running events, one study demonstrated that an estimated 25 of every 1000 finishers seek medical attention; however, this number can be highly dependent on environmental conditions. 2 3 Of those runners seeking medical attention, exercise-associated collapse (EAC) is the most common condition seen in the medical tent, comprising 59–85% of all visits after marathons and ultramarathons. 2 4 The mechanism of EAC is multifactorial and has previously been attributed to hyperthermia or dehydration. 5 , – , 7 Currently, however, EAC is believed to be principally the result of transient postural hypotension caused by lower extremity pooling of blood once the athlete stops running and the resultant impairment of cardiac baroreflexes. 8 9 The purpose of this article is to review the available evidence to better elucidate the mechanisms of EAC to ensure the best treatment modalities and to provide clinicians with an evidence-based algorithm to guide race day management.
Medline, limited to human subjects and English language, was searched using the following terms: ‘exercise-associated collapse’, ‘exercise-associated postural hypotension’, ‘postexercise collapse’ and ‘exercise and orthostatic intolerance’, which resulted in 86 articles, of which 26 were review articles. The abstracts of the articles were reviewed, and the references from the review articles were also reviewed, and a total of 34 studies deemed appropriate. Evidence was graded using the Oxford Centre for Evidence-Based Medicine 2011 Levels of Evidence. 10
Exercise-associated collapse.
Collapse in conscious athletes who are unable to stand or walk unaided as a result of light headedness, faintness and dizziness or syncope causing a collapse that occurs after completion of an exertional event or stopping exercise. 11
Postexercise symptoms caused by a decline in systolic blood pressure by at least 20 mm Hg below supine values on assuming the upright posture. 4
Symptoms caused by orthostatic hypotension, which is a sustained reduction of systolic blood pressure of at least 20 mm Hg or diastolic blood pressure of 10 mm Hg within 3 min of standing. 12
Although EAC, exercise-associated postural hypotension (EAPH) and orthostatic intolerance (OI) all describe potential causes of syncope or presyncope, EAC and EAPH are specific to exercise. EAPH is differentiated from EAC in that blood pressures have been measured and found to be different in a supine and standing position. However, both EAPH and EAC describe collapse in athletes after exertion.
Exertional heat stroke (EHS) is characterised by central nervous system dysfunction, which may manifest as collapse or syncope, associated with an increased core body temperature (>40°C), which is induced by exercise. 13 14 Exercise-associated hyponatraemia (EAH) is a potentially life-threatening condition characterised by a decrease in serum sodium (<135 mmol/L) and mental status changes. Athletes with EAH may have true syncope, confusion or disorientation but will have alteration in serum sodium. 15
Although EHS and EAH can be causes of collapse in endurance sporting activities, they are associated with abnormal vital signs and symptoms and should be considered and ruled out before considering a diagnosis of EAC. The focus of this review is EAC, its mechanism and treatment; therefore, EHS and EAH will not be discussed further in this review.
Endurance training is associated with an increased cardiac output and volume load on the left and right ventricles, causing the endurance-trained heart to a dilatation of the left ventricle combined with a mild-to-moderate increase in left ventricular wall thickness. This training-induced increase in cardiac output allows trained athletes to have a lower resting heart rate compared with the non-trained athletes. Furthermore, during exercise, the active muscles of the lower extremities require increased blood flow, and therefore, peripheral vascular resistance decreases to accommodate this need. To generate this large cardiac output, and to counter the resting decrease in heart rate secondary to training effect, athletes must increase their stroke volume and vascular resistance. Working skeletal muscle functions as a ‘second heart’, ensuring cardiac return to the heart from the dilated lower extremity vasculature. On cessation of activity, the second heart effect no longer assists venous return, and large volumes of blood may pool in the lower extremities and contribute to EAC. Therefore, the very adaptations that contribute to successful completion of endurance activities are also a large factor in the increased OI found in endurance athletes.
Evidence supports this increased susceptibility to OI in exercise-trained athletes. Studies support the concept of increase in calf and lower extremity compliance and increased diastolic chamber compliance and distensibility as contributors to OI in athletes. 16 , – , 18 Endurance athletes have larger increases in left ventricular end-diastolic volume compared with non-athletes, which allow them to generate the necessary larger stroke volume. 19 Trained athletes also demonstrated a decreased ventricular untwisting rate compared with non-trained athletes, demonstrating the trained heart's ability to adapt to maintain cardiac output. 20 Training-related expansion of vascular volume is associated with decreased heart rate response to baroreceptor stimulation. 21 In addition, this exercise-induced change in cardiac filling volume and output may lead to a resetting of the cardiopulmonary baroreflex. 22 Because of this reset baroreflex, trained individuals may depend more on maintenance of venous return to maintain upright body position after exercise. 23 Finally, a critical review supports the exercise-induced increase in stroke volume as a compensatory mechanism against OI 24 ( table 1 ).
Although dehydration leading to hyperthermia has been postulated as a primary factor for EAC, 5 , – , 7 there is no evidence to support its overall responsibility for OI or EAC in endurance athletes. 25 Evidence, however, supports both heat stress and increased skin temperature as contributing factors in OI. Heat stress results in the reduction of baroreflex control in response to an orthostatic challenge. 26 Heat stress has also been postulated to impair aerobic exercise performance, primarily through increased cardiovascular strain. 27 In addition, increasing body temperature may increase cerebral vascular resistance, reducing the cerebral threshold for neurogenic collapse. 28
Two small studies found that laboratory-induced hypovolemia may lead to changes in baroreflex control of blood pressure in certain individuals, which may increase susceptibility to EAC. 22 29 However, a larger clinical trial following the body composition of 31 runners completing an ultramarathon event found that the collapsed runners did not have a higher body temperature than those who did not collapse, and all the runners were dehydrated, but this level of dehydration was unrelated to the degree of postural hypotension after the event 30 ( table 2 ). Therefore, although heat and dehydration have not been found to be true causes of EAC or OI in endurance running events, they may possibly be risk factors for EAC or contribute by impairing peripheral vasoconstriction leading to the orthostatic state.
Dehydration/heat
Baroreflex modulation
Pooling of blood in the lower extremities at the cessation of exercise has been implicated as a mechanism of EAC; if the systemic vascular resistance, which is reduced during exercise, is not triggered by an intact baroreflex to increase after stopping exercise, a lower body negative pressure (LBNP) situation develops and postural hypotension may occur. LBNP is a widely used technique to study the cardiovascular response to this orthostatic stress. Many studies on the effect of LBNP have shown this altered baroreflex to be a primary mechanism of OI after exercise.
Reduction in baroreflex control has been implicated in the diminished orthostatic response after exercise. 31 A controlled trial of exercising men found that baroreflex control is altered after dynamic exercise. 32 Furthermore, in a clinical trial of 51 finishers of a mountain marathon, it was found that a diminished orthostatic response of resistance vessels was the likely aetiology in the OI in these runners after exercise. 33
In a clinical trial of experienced male runners, systolic blood pressure decreases after exercise secondary to a reduction in peripheral vascular resistance leading to a decreased filling volume. 34 Women, however, may respond differently to exercise than do men. A controlled clinical trial of both women and men showed that the mechanism of OI in women is likely caused by reduced cardiac filling rather than impaired baroreflex 35 ( table 3 ).
There is strong evidence to support an attenuated baroreflex response as a responsible mechanism of OI and EAC. It has been seen that heat may contribute to this response. However, there are several other factors that have been studied, which may also exacerbate this response.
Hypoglycaemia has been found to attenuate baroreflex sensitivity, which may be important because serum glucose levels will decrease as length of exercise increases, which may make endurance and ultraendurance athletes more susceptible to EAC. 36 Pushing the pace or aiming for a time goal has also been implicated in EAC. 30 As the respiratory rate of athletes increases as they try to attain a cutoff or time goal, their level of carbon dioxide will decrease as a result. Studies have shown that hypercarbia may be protective, 37 and this resultant hypocapnia may further attenuate the baroreflex response. 38
Medications may also affect response to LBNP – antidepressant medications have been shown to lead to a significant impairment in cardiovascular reflex response after exercise, which may implicate neurochemicals as possible factors in EAC. 39 In addition, in two separate randomised controlled clinical trials H1 and H2 receptor antagonist medications may blunt the body's postexercise hypotension, suggesting that histamine may also play a role in EAC 40 41 ( table 4 ).
The evidence points towards a lower extremity pooling of blood with an attenuated baroreflex response as the primary mechanism of EAC; therefore, treatment options should be directed primarily at correcting these deficits. Because there is no good evidence to support hyperthermia or dehydration as the primary aetiologies of EAC, total body cooling and intravenous fluids should not have a role in the initial treatment of EAC.
In a randomised controlled trial, it has been shown that lower body positive pressure, such as what occurs in the Trendelenburg positions, promoted restoration of normal haemodynamics. 42 43 Studies also suggest that oral hydration may be preventive against EAC and may also be used as an effective treatment for EAC. 43 44 A randomised controlled trial and two smaller trials suggest that skin surface cooling may act towards directing peripheral blood flow centrally and decreasing cardiovascular strain, thus treating EAC. 45 , – , 47 Finally, the results of a study of compression stockings in runners suggest that runners who are prone to OI after exercise may benefit from wearing compression hose while running. 48 Those prone to EAC may also potentially benefit from taking H1 or H2 blocking medications, skin surface cooling along the course and ensuring adequate glucose levels during participation ( table 5 ).
Using the evidence for aetiology, mechanism and treatment, we propose an algorithm, which is currently used at the Marine Corps Marathon, 49 50 as a clinical framework for the treatment of EAC in endurance athletes ( figure 1 ). The key to using the EAC algorithm is to approach a collapsed athlete with a wide differential that includes potential life-threatening causes such as EAH or EHS and ruling those out with a concise physical examination evaluating mental status and body temperature before proceeding down the EAC algorithm.
Exertional collapse algorithm.
EAC is a common occurrence in medical tents after endurance sporting activities, which is typically characterised by collapse after completion of the event in the absence of neurological, biochemical or thermal abnormalities. Although EAC is perhaps the most common aetiology confronted by the medical provider attending to collapsed athletes in a finish-line tent, the provider needs to be reminded that EAC is a diagnosis of exclusion and that he or she needs to be vigilant for other aetiologies that cause collapse. There is no evidence to support the previous idea that EAC is caused primarily by dehydration or heat stroke. These factors, however, along with medications, hypocapnia and hypoglycaemia, may be contributory to EAC. Evidence currently supports that postural hypotension caused by pooling of blood in the lower extremities, secondary to decreased vascular resistance in the face of an attenuated baroreflex response, as the principal mechanism of EAC. Women may sustain EAC more from decreased cardiac filling than from altered baroreflex. Treatment of EAC is usually symptomatic and involves oral hydration and a Trendelenburg position – total body cooling, intravenous hydration or advanced therapies are generally not needed.
The authors thank Benjamin D Levine, MD for collaboration and suggestions for improving the manuscript.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.
This chapter provides a discussion of the specific challenges facing the emergency physician dealing with a patient presenting with a collapse after marathon running. It describes an overview of the range of heat-related presentations, the monitoring required, and the subsequent electrolyte disturbances and the acute management strategies required.
It examines the evidence base for three key clinical questions:a consideration of whether standard tympanic temperature measurement is accurate and adequate; an analysis of how patients with exertional heat stroke should be best cooled; and discussion around whether standard antipyretic treatments have a role in lowering temperatures and alleviating symptoms.
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It was an unseasonably warm day for the NYC Marathon this past November, but Daniel Gottesmann had been training 26.2-mile run for three months and he felt confident the heat wouldn't be a problem. As he ran, he began to feel “extremely thirsty.” At mile 11, he collapsed. Lucky for him, New York Firefighter Ryan Dillon was watching the marathon nearby.
“He started going in and out of consciousness,” Dillion, 31, of Brooklyn, tells TODAY.com. “When I saw him go out, I just immediately started pumping.” Thanks to Dillion’s quick efforts, Gottesmann survived. They two reconnected at the bar near where Gottesmann collapsed.
“Upon meeting Daniel, I was extremely nervous,” Dillon says. “You don’t really get to meet the people you make a difference in their lives.”
Last year, Gottesmann, 33, of Brooklyn ran a marathon in the Hamptons and has run several half marathons. Leading up to the NYC Marathon, which he ran with his wife, Gottesmann ran almost every day and even had some long training runs exceeding 11 miles. He felt healthy as he trained.
“I felt well,” he tells TODAY.com. “I never felt anything like I was feeling during the marathon itself.”
As Gottesmann started running he noticed it felt “a little bit tougher.”
“I felt like I’m not getting into my rhythm that I usually get after three or four miles,” he explains. “I felt like I was putting in more effort to keep the pace that I wanted to keep during the run.”
He also felt parched and wondered if the heat and the fact that he didn’t have a water bottle on him contributed to this.
“In training usually, I run with a bottle of water,” Gottesmann says. “Every water station that I got through I had to drink two cups of water. I felt extremely thirsty and felt like I’m going to need to put more effort into keeping my typical pace.”
Each mile felt harder to Gottesmann. Miles eight, nine and 10 became harder and harder for him.
“It didn’t concern me from a health perspective,” he says. “I didn’t feel like I was about to faint.”
By mile 10, Gottesmann couldn’t remember anything. He just remembers entering Williamsburg, where Dillon and his wife were watching the race outside a bar. They were looking for one of Dillion’s coworkers to run by when someone told Dillon that a runner had collapsed.
“I ran over there and I saw Daniel. They had got him in a chair, and I ran down the block to go find medical help,” Dillon says. “When I came back up the block he was in the chair, basically in and out of consciousness.”
It looked like Gottesmann started choking on his saliva, so Dillon laid him on the ground.
“He started turning blue and I’m like, ‘Wait a minute, I think he’s choking on something,’” Dillon recalls. “I turn him over to his side and gave him a pat on the back. He throws up and he opened his eyes.”
Gottesmann soon lapsed back into unconsciousness and Dillon began CPR compressions.
“When I saw him close his eyes and go out, I just started pumping,” Dillon says. “I didn’t have any medical equipment.”
Even though Dillon is trained to help in emergencies, it felt tougher without his equipment with him. The 30 minute wait for EMS felt grueling for the firefighter.
“We kept him warm because he was a little cold because he was in shock,” Dillon says. “We just waited for EMS to show up and kept him conscious, at least somewhat.”
Gottesmann remembers none of this. He does recall waking in an ambulance and wondering what happened. He didn’t have his phone with him so he couldn’t call his wife or anyone to let them know what happened. While she was running, they were at difference paces and she was unaware he collapsed.
“I just arrived at the hospital. The first two, three, four hours, I was as weak as it gets. It didn’t feel good to move my body or open my eyes or absorb information,” Gottesmann says. “After being connected to an IV for a couple hours. I started to feel better.”
Doctors ran a slew of tests to understand what happened to Gottesmann. When his wife finished the marathon in three and a half hours, she noticed her husband hadn’t finished and called her dad. He was the couple’s emergency contact and knew that Gottesmann was in the hospital and she came to visit him. Gottesmann stayed for a week because doctors wanted to make sure that his health stabilized.
“Some of the things you can find in bloodwork or blood stream … were elevated and the doctor is wanting to see them come down,” he says. “It was mostly things involving the liver and heart.”
Doctors suspected that Gottesmann experienced rhabdomyolysis, also known simply as rhabdo, according to the U.S. Centers for Disease Control and Prevention . This potentially fatal condition occurs when damaged muscles discharge proteins and electrolytes into the blood, which can lead to kidney and heart problems. While anyone can develop rhabdo, it occurs more often when people are exercising or engaging in strenuous tasks in the heat. It often affects firefighters, military members, construction worker and athletes, according to the CDC.
The CDC says symptoms include:
Doctors diagnosed it by taking a blood test to look for creatine kinase or creatine phosphokinase.
“The body needs to work extra time to get ride of those proteins mostly that were there now in the blood,” Gottesmann says. “Once the values got to a point where the doctors felt good, they sent me home.”
He’s had several follow-up appointments to make sure he’s still healthy.
“I’m feeling good today,” he says.
Dillon continued watching the marathon, hoping that the paramedics effectively treated the stranger he helped. He had no idea that Gottesmann needed to spend so much time in the hospital to recover. Though, as a firefighter he often doesn’t hear what happens to people he helps.
“I didn’t specially know about Ryan until my wife and I went to the bar next to where I collapsed,” Gottesmann says. “Only then we learned that some guy helped me.”
He wanted to thank that person and asked the bartender if she could help find him.
“The bartender contacted my wife,” Dillon says. “She was like, ‘That guy from the marathon was looking for you guys. He got out of the hospital.’ We were like, ‘What?’”
Dillon felt shocked that Gottesmann was in the hospital for so long and he agreed to meet him. The two felt anxious before the meeting.
“I was kind of nervous but more excited to meet Ryan,” Gottesmann says. “He’s so humble and such a decent good human being.”
Dillon also didn’t know what to expect.
“I did everything that I could until the actual health professionals got there and you can do everything right, medically wise, and still come out with a loss. That’s why it’s nerve wracking,” Dillon says. “The whole thing was amazing.”
Gottesmann said this experience taught him to pay better attention to what his body’s telling him. He feels grateful for the kindness he received.
“I certainly don’t know what would have happened to me if it hadn’t been for Ryan,” he says.
As for Dillon, he thinks anyone can do what he did.
“Just (make) an effort to try to help,” he says. “Just be a decent person. (A) human life is the most valuable thing in the world. If you see somebody struggling and you aren’t, help them out.”
Meghan Holohan is a digital health reporter for TODAY.com and covers patient-centered stories, women’s health, disability and rare diseases.
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COMMENTS
But research suggests the runners who are most likely suffering from a serious problem tend to collapse during the race, and most of the runners who make it to the finish line before collapsing are going to be okay. Still, any collapsed runner needs medical attention right away.
Effective regulation of pace enables the majority of runners to complete competitive endurance events without mishap. However, some runners do experience exercise-induced collapse associated with postural hypotension, which in rare cases results from life-threatening conditions such as cardiac disorders, cerebral events, heat stroke and hyponatraemia. Despite the experience of either ...
Effective regulation of pace enables the majority of runners to complete competitive endurance events without mishap. However, some runners do experience exercise-induced collapse associated with postural hypotension, which in rare cases results from life-threatening conditions such as cardiac disor …
Here, we'll explore why do marathon runners collapse—or even suffer cardiac arrest—during marathons and other endurance events.
Why do marathon runners collapse and die? Some of the reasons why marathon runners often collapse near the finishing line is because the build-up of lactic acid in the blood during the run triggers abnormal heart rhythms and also exhaustion, emotional stress, dehydration and heat stroke.
Profiling Collapsing Half Marathon Runners-Emerging Risk Factors: Results from Gothenburg Half Marathon Article Full-text available Dec 2019 Amir Khorram-Manesh Therese Löf Mats Borjesson Eric ...
An athlete collapsing is paradoxical from the perspec-tive that there are robust regulatory mechanisms that enable the overwhelming majority to successfully complete their event [1, 28, 33].
The phenomenon of runners collapsing is a reminder of the incredible demands we place on our bodies during the pursuit of our running goals. By understanding the factors that can contribute to collapse - from dehydration and nutrition to overexertion and individual factors - we empower ourselves to run safely and make informed decisions ...
It is concluded that runners collapsing during the race are more likely to have a readily identifiable medical condition than runners collapsing after the finish line and runners collapse most frequently near cutoff times for medals and race closure times.
Collapse is perhaps the most dramatic of all medical problems affecting athletes. Though collapse can be seen in any athletic event requiring maximal exertion, it is most common in endurance events, such as marathons and triathlons. The incidence seems to increase as the race distance, temperature, and humidity increase (O'Conner et al., 2003 ...
Simple. The basis for the belief that collapsed runners were suffering from dehydration began with the explosive growth in the number of marathon runners after 1976 (figure 2a, page xv). This produced a massive increase in the number of runners requiring medical care at the finish of those races. Logically, the collapse of an athlete after ...
Introduction In the marathon, how runners pace and fuel their race can have a major impact on race outcome. The phenomenon known as hitting the wall (HTW) refers to the iconic hazard of the marathon distance, in which runners experience a significant slowing of pace late in the race, typically after the 20-mile mark, and usually because of a depletion of the body's energy stores. Aim This ...
We aimed to conduct a qualitative study to find a perceived risk profile among runners who collapsed and who were transported by ambulances to the nearest hospital during Gothenburg's half marathon (2010-2017). Collapsing runners seem to lack the ability to make a decision to withdraw from the contest despite being exhausted.
Predicting Initial Claim: Explain why the marathon runners are collapsing and possibly dying. (What is happening in their bodies...think different systems and different ways they could leave homeostasis)
Exercise-associated collapse (EAC) commonly occurs after the completion of endurance running events. EAC is a collapse in conscious athletes who are unable to stand or walk unaided as a result of light headedness, faintness and dizziness or syncope causing a collapse that occurs after completion of an exertional event. Although EAC is perhaps the most common aetiology confronted by the medical ...
Case history A previously fit and well 32-year-old man is brought into the ED by the ambulance service after collapsing at mile 21 of a city marathon. His running partners assure you that he has trained consistently for the race over the last few months and had taken on regular hypertonic fluids throughout the race until he collapsed.
During the NYC marathon, Daniel Gottesmann collapsed, stopped breathing. New York firefighter gave him chest compressions. The runner had rhabdomyolysis.
【Solved】Click here to get an answer to your question : Predicting Initial Hypothesis: Explain why the marathon runners are collapsing and possibly dying. (I think the marathon runners are collapsing and dy...