Veterinarians perform a vital role during equine endurance competitions by clinically evaluating horses before the start of the race, during the race, and following the race. These clinical examinations at specific checkpoints (ie, veterinary gates) identify horses that are unable to continue for various reasons. Early recognition of problems is essential to prevent serious injury to the equine athletes later in the ride.
Several studies have been undertaken to identify risk factors associated with the elimination of endurance horses from competition to identify at-risk animals before injuries develop.1–4 An increased elimination rate has been associated with the horses’ prior racing experience, distance of the race, footing of the race, riding speed, and the number of horses entered in the race.1–4 A number of clinical examination variables that are monitored by veterinarians during the ride have been associated with failure at later checkpoints. These variables include heart rate, gastrointestinal sounds, and lameness, but many of these criteria may not be applied uniformly across different rides.4 A continued search for objective variables to identify at-risk endurance horses is needed.
The electrolyte abnormalities commonly identified in competing endurance horses have been documented.5–7 Equine sweat is isotonic or hypertonic, compared with the osmolarity of normal horse plasma, and has particularly high concentrations of chloride and potassium with a mean + SE concentration ranging from 133 + 7 mmol/L to 269 + 98 mmol/L and 46 ± 3 mmol/L to 99.0 ± 49.6 mmol/L, respectively.8,9 Horses that sweat profusely deplete body water and electrolytes10; if these losses are not appropriately replaced by drinking, eating, or electrolyte supplementation, horses could be at higher risk for failure during endurance competition.
Until recently, there has been very little focus on the use of plasma electrolyte concentrations and laboratory hydration variables measured early in endurance competition to predict which horses are likely to fail. Trigo et al11 identified plasma protein and serum creatinine concentrations and serum muscle enzyme activities to be predictive of horses’ elimination later in the race; however, plasma electrolyte concentrations were not evaluated. Another study12 revealed similar findings, but also identified an association of lower serum chloride concentration with subsequent elimination. Likewise, a similar study13 of horses during an endurance competition in Australia identified decreased blood sodium, chloride, and ionized calcium concentrations as well as increased PCV as being associated with elimination from the competition. Some of these aforementioned studies had a small number of horses, and none of them compared results of laboratory testing with clinical examination findings.
With this new evidence to suggest that laboratory test results may be able to identify endurance horses at risk for failure, the value of this testing must be objectively assessed.11–13 Specifically, research is needed to compare the ability of laboratory testing with clinical examination variables to predict which endurance horses are at risk for failure. If laboratory testing offers no additional benefits over clinical examination, then the cost of testing is likely not warranted. The purpose of the study of this report was to identify rapid laboratory tests (completed within 5 minutes) that could provide data with which to identify competing endurance horses at risk for failure and to evaluate the usefulness of those data against standard clinical examination findings. The hypothesis was that a combination of PCV, plasma electrolyte and total protein concentrations, and clinical examination variables could be used to identify endurance horses at risk for elimination from a competition.
Materials and Methods
Horses were recruited in July 2013 at the Western States 160-km (100-mile) endurance ride (Tevis Cup). The study was approved by the Animal Care and Use Committee of the University of California-Davis, and client consent for inclusion of the horses in the study was obtained prior to the start of the race.
Of a total of 139 horses arriving at the 58-km checkpoint, 101 (73%) participated in the study. Entrance into the study was voluntary and based on recruitment prior to the start of the ride. Upon arrival at the checkpoint, horses were directed to the veterinary gate and met a heart rate criterion of 60 beats/min before blood sample collection and completion of the veterinary examination. The heart rate criterion was set by the management of the ride and was not a condition that was influenced by the study protocol. A blood sample was obtained from each of the 101 horses at the 58-km checkpoint. A 3-mL syringe containing heparin was used for collection of the blood sample via direct venipuncture from either jugular vein.
Immediately following collection, blood samples were analyzed with a commercially available point-of-care analyzer,a and pH, Pco2, base excess, anion gap, and whole blood concentrations of sodium, potassium, chloride, total carbon dioxide, BUN, glucose, and bicarbonate were recorded. Additionally, PCV was determined with the microhematocrit method, and plasma total protein concentration was determined via refractometry. To correct for the hydration status of the animal, corrected values for PCV and whole blood concentrations of sodium, potassium, chloride, and bicarbonate were calculated as follows:
where the original value is the plasma chloride concentration, plasma sodium concentration, plasma potassium concentration, plasma bicarbonate concentration, or PCV obtained from the analyzer. A similar protocol has been used to assess dehydration and electrolyte disorders in people.14 These values were also entered into the database for each horse.
In addition to the aforementioned laboratory variables, clinical examination findings from the veterinary card for each horse were also recorded. The examination variables of interest included heart rate, gastrointestinal sounds, mucous membrane color, capillary refill time, jugular refill time, skin tenting, anal tone, muscle tone, gait, overall impression of the horse, horse's attitude, impulsion, wounds, tack galls, and signs of back pain. With the exception of heart rate, veterinary examination variables were scored subjectively (as A, A−, B+, B, B−, C+, C, C−, and D); these scores were transformed to numeric values of 9, 8, 7, 6, 5, 4, 3, 2, and 1, respectively. An adjusted heart rate was also calculated on the basis of the time elapsed between entry into the veterinary checkpoint (ie, the entry time recorded on the veterinary card) and recording of the heart rate (ie, the time that the horse met the heart rate criterion [60 beats/min] at the veterinary gate). This heart rate adjustment was implemented to adjust for the variability in the interval between the arrival of each horse at the checkpoint and clinical examination (some horses waited longer before undergoing the clinical examination). A similar type of adjustment that accounts for the time elapsed between entry into the veterinary gate and measurement of the horses’ heart rate has been incorporated in another study.3 The equation used to determine the adjusted heart rate was as follows:
where HR is the heart rate recorded on the veterinary examination card and MIN is the time (in minutes) elapsed between entry into the veterinary checkpoint and the time that the heart rate was recorded.
In addition to laboratory and clinical examination variables, age and breed of each horse were recorded from the veterinary cards. Breed was entered as Arabian or non-Arabian; horses listed as Arabian cross were counted as non-Arabian. All information was entered into a database including whether the horse successfully completed the ride or was eliminated prior to ride completion. If the horse did not complete the ride, it was included in the overall elimination category, and the reason for failure (as noted on the veterinary card) was additionally categorized as lameness, metabolic, or other. The other category was used for all eliminations that were not coded in the lameness or metabolic categories and included overtime and rider option, for example.
Statistical analysis
Data were entered into a spreadsheet and then analyzed with a statistical software package.b Continuous data are reported as mean ± SD. Three forms of statistical analysis were used for each of the 4 outcome categories to relate the independent variables to a given outcome (ie, overall elimination or each of 3 other elimination categories [metabolic elimination, lameness elimination, and elimination for other reasons]). First, stepwise logistic regression was used to determine which of the measured variables were linear predictors of the log odds of a given outcome. Second, classification and regression tree analysis was used to determine which predictors and thresholds best distinguished horses that were likely to succeed from those likely to fail for a particular reason. Finally, GAMs evaluated previously identified predictors obtained from the first 2 models to determine a possible nonlinear relationship between a predictor and the odds of competition completion or a certain type of failure. The GAMs are reported for each of the 4 outcome categories. A value of P < 0.05 was used to determine significance.
Results
For the 101 horses entered in the study, the mean ± SD age was 12.5 ± 3.0 years. There were 34 mares, 65 geldings, and 2 stallions. Of the 101 horses, 40 (40%) were eliminated from the ride and 61 (60%) completed the ride. In comparison, for all 139 horses (101 enrolled and 38 not enrolled in the study) entering the checkpoint, the elimination rate was 46% (64 horses) and the completion rate was 54% (75 horses). Of the 40 study horses that were eliminated, 17 (43%) were assigned to the lameness elimination category, 11 (28%) were assigned to the metabolic elimination category, and the remaining 12 (30%) were assigned to the elimination for other reasons category (reasons included overtime and rider option). Of the 40 horses that were eliminated, 5 (13%) were eliminated at the 58-km checkpoint, 2 (5%) were eliminated at the 80-km checkpoint, (5%) were eliminated at the 151-km checkpoint, and 1 (3%) was eliminated at the 160-km checkpoint.
The values for all clinical examination variables of the competition finishers and nonfinishers were summarized (Table 1). The values for all laboratory variables of the competition finishers and nonfinishers were also summarized (Table 2). The significant predictors for the outcome category of overall elimination or each of 3 elimination categories (metabolic elimination, lameness elimination, and elimination for other reasons) were identified. In the model predicting overall elimination, the 2 most significant predictors of failure (corrected on the basis of plasma total protein concentration) were whole blood potassium concentration and adjusted heart rate (Table 3). Of the veterinary examination variables, only adjusted heart rate was a useful predictor of overall elimination from competition. For the category of metabolic elimination, predictors of elimination of horses from the competition included breed, total plasma protein concentration, and the veterinarian's evaluation of the horse's attitude. For the category of lameness elimination, predictors of elimination of horses from the competition included whole blood chloride concentration and the corrected PCV. For the category of elimination for other reasons, only corrected PCV was identified as a predictor of elimination.
Mean ± SD scores for clinical examination variables at the 58-km checkpoint for endurance horses participating in the 2013 Western States 160-km endurance competition that did or did not complete the ride.
| Variable | Finishers | Nonfinishers | No. of horses |
|---|---|---|---|
| Gastrointestinal sounds | 6.5 ± 1.4 | 6.3 ± 1.4 | 99 |
| Mucous membranes | 7.8 ± 1.4 | 7.6 ± 1.4 | 100 |
| Capillary refill | 8.0 ± 1.3 | 7.8 ± 1.3 | 100 |
| Heart rate | 52 ± 5 | 54 ± 4 | 100 |
| Heart rate (adjusted) | 57 ± 8 | 61 ± 7 | 98 |
| Jugular refill | 8.0 ± 1.2 | 7.8 ± 1.2 | 100 |
| Skin tenting | 7.2 ± 1.4 | 7.2 ± 1.4 | 100 |
| Anal tone | 8.8 ± 0.7 | 8.6 ± 0.8 | 100 |
| Muscle tone | 8.5 ± 0.9 | 8.3 ± 1.1 | 101 |
| Gait | 8.6 ± 0.8 | 8.5 ± 0.8 | 96 |
| Overall impression | 8.2 ± 1.0 | 7.7 ± 1.3 | 96 |
| Attitude | 8.7 ± 0.7 | 8.6 ± 0.8 | 97 |
| Impulsion | 8.2 ± 1.0 | 7.7 ± 1.4 | 97 |
| Wounds | 8.9 ± 0.4 | 8.7 ± 1.0 | 85 |
| Tack galls | 8.9 ± 0.6 | 9.0 ± 0.2 | 85 |
| Signs of back pain | 8.8 ± 0.8 | 8.7 ± 0.8 | 99 |
One hundred one horses were included in the study. Data were obtained to compare results of point-of-care laboratory testing with standard veterinary clinical examination findings at a single time point during endurance competition to identify horses at risk for elimination. Horses were directed to the veterinary gate and met a heart rate criterion of 60 beats/min before completion of the veterinary examination. With the exception of heart rate, veterinary examination variables were scored subjectively (as A, A−, B+, B, B−, C+, C, C−, and D); these scores were transformed to numeric values of 9, 8, 7, 6, 5, 4, 3, 2, and 1, respectively. An adjusted heart rate was calculated on the basis of the time elapsed between entry into the veterinary checkpoint (ie, the entry time recorded on the veterinary card) and recording of the heart rate (ie, the time that the horse met the heart rate criterion of 60 beats/min at the veterinary checkpoint).
Mean ± SD clinicopathologic variables at the 58-km checkpoint for the endurance horses in Table 1.
| Variable | Finishers | Nonfinishers | Reference range | No. of horses |
|---|---|---|---|---|
| Potassium (mmol/L) | 2.9 ± 0.5 | 2.7 ± 0.3 | 1.9–4.1 | 101 |
| Corrected potassium (mmol/L) | 2.5 ± 0.4 | 2.2 ± 0.3 | NA | 101 |
| Sodium (mmol/L) | 141 ± 3 | 142 ± 2 | 128–142 | 101 |
| Corrected sodium (mmol/L) | 121 ± 7 | 116 ± 9 | NA | 101 |
| Total protein (g/dL) | 7.0 ± 0.4 | 7.3 ± 0.5 | 5.2–7.9 | 101 |
| BUN (mg/dL) | 21 ± 3 | 22 ± 4 | 11–27 | 98 |
| Chloride (mmol/L) | 105 ± 3 | 103 ± 3 | 100–111 | 98 |
| Corrected chloride (mmol/L) | 89 ± 6 | 85 ± 7 | NA | 98 |
| Bicarbonate (mmol/L) | 28 ± 3 | 29 ± 3 | 24–30 | 101 |
| Corrected bicarbonate (mmol/L) | 24 ± 3 | 24 ± 3 | NA | 101 |
| PCV (%) | 45 ± 4 | 45 ± 4 | 32–53 | 101 |
| Corrected PCV (%) | 38 ± 3 | 37 ± 4 | NA | 101 |
| Glucose (mmol/L) | 76 ± 20 | 81 ± 18 | 62–134 | 101 |
| Pco2 (mm Hg) | 40.8 ± 3.5 | 41.1 ± 4.2 | 36–46 | 101 |
Horses were directed to the veterinary gate and met a heart rate criterion of 60 beats/min before blood sample collection. A 3-mL syringe containing heparin was used for collection of 1 blood sample via direct venipuncture from either jugular vein from each horse. Blood samples were immediately analyzed with a commercially available point-of-care analyzer Additionally, PCV was determined with the microhematocrit method and plasma total protein concentration was determined via refractometry. To correct for the hydration status of the animal, corrected value for PCV and whole blood concentrations of sodium, potassium, chloride, and bicarbonate were calculated as follows: corrected value = (6.0/plasma total protein concentration)•original value, where the original value is the whole blood chloride concentration, whole blood sodium concentration, whole blood potassium concentration, whole blood bicarbonate concentration, or PCV obtained from the analyzer.
NA = Not applicable.
Findings from GAMs to determine relationships between a predictor (determined by means of 2 other models) and the odds of competition completion or a certain type of failure (overall elimination, metabolic elimination, lameness elimination, or elimination for other reasons) as the outcome variable for the endurance horses in Tables 1 and 2.
| Elimination category | Variable | OR (95% CI) | P value | Relationship | Comment |
|---|---|---|---|---|---|
| Overall | Corrected whole blood potassium concentration | 0.05 (0.02–0.12) | 0.05 | Linear | Higher risk of elimination with decreasing potassium concentration |
|  | Adjusted heart rate | 1.11 (1.06–1.16) | 0.05 | Linear | Higher risk of elimination with increasing adjusted heart rate |
| Metabolic | Breed | 11.34 (5.17–24.85) | 0.01 | Linear | Higher risk of elimination for non-Arabian breeds vs Arabians |
|  | Plasma total protein concentration | 6.24 (2.61–14.92) | 0.05 | Linear | Higher risk of elimination with increasing total protein concentration |
|  | Attitude | 0.45 (0.31–0.65) | 0.05 | Linear | Higher risk of elimination with decreasing score for attitude |
| Lameness | Whole blood chloride concentration | 0.79 (0.71–0.87) | 0.05 | Linear | Higher risk of elimination with lower chloride concentration |
| Â | Corrected PCV | NA | 0.05 | Nonlinear | Failure more likely at very high values |
| Other | Corrected PCV | NA | 0.01 | Nonlinear | Failure more likely at values > 39% |
Any horse that did not complete the ride was included in the overall elimination category, and the reason for failure (as noted on the veterinary card) was additionally categorized as lameness, metabolic, or other. The other category was used for all eliminations that were not coded in the lameness or metabolic categories and included over time and rider option, for example. For each of the 4 outcome categories (overall elimination, metabolic elimination, lameness elimination, and elimination for other reasons), stepwise logistic regression was first used to determine which of the measured variables were predictive as linear predictors of the log odds of an outcome. Second, classification and regression tree analysis was used to determine which predictors and thresholds best distinguished horses that were likely to succeed from those likely to fail for a particular reason. Finally, GAMs were used to evaluate the previously identified predictors obtained from the first 2 models to determine a possible nonlinear relationship between a predictor and the odds of competition completion or a certain type of failure. A value of P < 0.05 was used to determine significance.
CI = Confidence interval.
See Tables 1 and 2 for remainder of key.
Discussion
In the present study, results of point-of-care laboratory testing were compared with standard veterinary clinical examination findings at a single time point during an endurance competition to identify horses at risk for elimination. One hundred one horses were evaluated in the study, of which 40% were eliminated and 60% completed the ride. In a model predicting overall elimination, corrected (on the basis of plasma total protein concentration) whole blood potassium concentration and adjusted heart rate were the 2 most significant predictors of failure. Heart rate or time to heart rate recovery was identified as a risk factor for ride failure in previous studies3,4 involving much larger numbers of endurance horses. The adjusted heart rate used in the present study accounted for the resting time spent by a horse at the veterinary checkpoint before the heart rate was assessed. It would seem logical that a horse with an increased heart rate despite a long period of rest would be at higher risk of competition failure than would a horse with a lower heart rate immediately upon arrival at the checkpoint.
Although corrected whole blood potassium concentration was identified as an independent predictor of failure among horses in the overall elimination category, the circulating potassium concentration (uncorrected) was not a significant predictor in 2 other studies.12,13 It is possible that correcting for hydration status by means of the total protein concentration might have yielded different results in these previous studies.12,13 In 1 report,6 the potassium concentration in horses requiring emergency treatment during an endurance ride was low, compared with that in horses that successfully completed the ride. Low potassium concentration has also been identified in competing endurance horses in another study; however, intraride values were not specifically linked to failure.15 It is also possible that study differences reflect differences in electrolyte supplementation and difficulty of the various rides.
Results of the present study differed from those of previous studies12,13 in which plasma chloride concentration was identified as a significant predictor of failure of horses during endurance competition. Although lower whole blood chloride concentration was associated with the specific category of lameness elimination in the present study, it was not identified as a significant predictor of failure for any other category. It is also possible that the use of later time points for blood sample collection in other studies resulted in different findings.
Except for the adjusted heart rate, no other veterinary examination variables were useful predictors of overall elimination of horses from competition in the present study. This was in contrast to results of a previous study4 wherein a veterinarian's overall impression of the animal and the scoring of gait were significantly associated with completion or failure. Compared with the study of this report, the previous study4 had a much larger number of horses across a much greater number of competitions, and these factors may account for the differences in findings.
For the category of metabolic elimination, predictors of elimination in the ride included breed, total plasma protein concentration, and the veterinarian's evaluation of the horse's attitude. Appaloosa, Missouri Fox Trotter, Quarter Horse, Thoroughbred, and Peruvian Paso were breeds associated with an increased risk of metabolic elimination, compared with that for Arabians, in a previous study.4 It was speculated that these physically larger (compared with Arabians) breeds may be more likely to overheat and dehydrate; however, additional controlled trials are needed to determine the reasons for the increased elimination rate among these non-Arabian breeds of horses. The number of horses in the present study was too small to draw any conclusions about breed-specific associations other than differentiating between Arabians and non-Arabians.
In the present study, plasma total protein concentration was an important predictor in the metabolic elimination category and indirectly affected corrected values for all other elimination categories. In a prior study by Barnes et al,13 plasma total protein concentration was not significantly associated with elimination, but the value increased in horses with metabolic elimination, compared with the value in horses that completed the competition successfully. A larger sample of horses might have identified a significant association in this prior study.
The veterinary examination variable of horse's attitude was associated with metabolic elimination in the present study. Horses with lower scores were more likely to be eliminated. This was not evident in a previous study4 that included rides of different distances and difficulty.
For the category of lameness elimination, predictors of elimination included the whole blood chloride concentration and the corrected PCV (Table 3). The association of whole blood chloride concentration and PCV with the lameness elimination was somewhat surprising. It is interesting to speculate that horses eliminated on the basis of lameness may have additional metabolic problems or conversely that electrolyte derangements and subsequent weakness might make a horse more prone to injury during competition. For example, hypokalemia has been associated with muscle weakness and fatigue in people, and similar clinical signs are likely to be present in hypokalemic horses.16 It is also possible that muscle disorders, which likely are affected by hydration and electrolyte status, may predispose horses to lameness. There is evidence that hypokalemia can lead to rhabdomyolysis in people under extreme circumstances.17
The data for horses in the category of elimination for other reasons were particularly difficult to interpret because many of these horses were eliminated for overtime or at the discretion of the rider (ie, not a result of veterinary medical concerns). Some horses were likely progressing comparatively slowly because of rider concerns about hydration or feed consumption. Corrected PCV was identified as a predictor of elimination for other reasons, and this could reflect dehydration that was perceived by the rider of the horse.
Although the electrolyte changes identified in the present and previous studies appear to be associated with horses’ failure to complete endurance rides, it is not clear whether these changes are a direct cause of elimination. It is possible that increased electrolyte supplementation, particularly with potassium and chloride, would improve a horse's chance for successful completion, but additional research is needed. It is possible that the electrolyte changes are merely markers for endurance horses that are compromised, rather than representing a cause of the failure.
It was surprising that the veterinary perception of lameness during the examination was not independently predictive of elimination. In a previous study,4 gait was a significant predictor of lameness elimination later in the ride. However, the previous study4 obtained data from a larger number of rides.
In the endurance competition on which the present study was centered, scoring of the veterinary examination variables was available to both veterinarians and riders. This could potentially introduce bias because a veterinarian who subsequently considers whether to eliminate a horse would have knowledge of the prior examination results. The act of subsequent elimination was therefore not entirely independent of the scores that were received at the 58-km checkpoint (used for analysis in this ride). However, it would be anticipated that the bias would favor a more significant association with clinical examination variables. The same bias does not exist for the laboratory variables. Neither the riders nor the veterinarians had any knowledge of the bloodwork results until after the competition was completed. Therefore, this model should accurately reflect the ability of laboratory variables to predict elimination of horses during endurance rides of similar distance and difficulty.
The present study was performed to evaluate variables that could be quickly assessed or for which results were available within the 1-hour hold time before the horse is released from the checkpoint. The benefit of this rapid testing is that horses could be held for recheck evaluation at the checkpoint before continuing onto the racecourse. Riders with horses identified as at risk could be asked to slow down or warned to be more careful.
One of the main limitations of the present study was that it evaluated only 1 competition. Although a study that incorporated multiple rides would be ideal, the course for each endurance ride is often very different. For example, some rides start at different times of the day or may have a more difficult section of the course earlier in the ride.13 Likewise, control checkpoint locations are not uniform among rides. In the study by Barnes et al,13 sodium concentrations at midride in the horses eliminated for metabolic reasons were lower than their values at the start of the ride and also lower than midride values in horses that successfully completed the ride. However, in that study,13 midride blood samples were obtained at approximately the 90-km point as opposed to approximately the 60-km point in the present study. This difference could explain why sodium concentration was not a useful abnormality to distinguish successful versus failed horses in the present study.
It is possible that each ride may have different laboratory variables as predictors of failure, depending on the checkpoint location and timing of the blood sample that is obtained. Horses may have hydration or electrolyte changes earlier in a specific ride, some of which then resolve with water and salt consumption as the ride progresses.
A second limitation of the present study was that a prerace blood sample was not obtained from the horses. It is possible that detection of changes in laboratory variables (prerace vs intrarace data) would be more useful than results of a single test performed during the ride. However, the present study was designed to evaluate a more practical single-test protocol that could be used without the expense of 2-sample testing. The expense of single-sample testing could range from $15 to $40, depending on the number of variables tested.
A third limitation of the study was that enrollment into the study was voluntary and did not include all horses in the ride. Reasons for refusal to enroll in the study could have included behavioral problems with blood collection or a rider's concern that sample collection would slow down the pace of the ride. Specific reasons for a rider's refusal to participate were not recorded.
To identify the optimal testing criteria, future studies should focus on evaluating horses at multiple checkpoints during a wider variety of rides. The major advantage of early checkpoint testing is that a larger number of horses are still participating in the ride and can be screened for problems. However, the difficulty with early testing is that water and electrolyte depletion may be more difficult to detect. Future studies could also focus on establishing the best cutoff criteria for given variables to optimize the elimination of horses at risk for morbidity.
Results of the present study indicated that laboratory testing of horses during this particular endurance competition appeared to significantly improve prediction of elimination, compared with the use of standard veterinary examination variables alone. More research is needed to determine how this information should be used to help protect competing horses and whether changes in ride strategy or electrolyte supplementation would be beneficial. Laboratory testing should be considered during endurance rides with high elimination rates to help identify earlier those horses that are at risk.
Acknowledgments
Supported by the Western States Trail Foundation.
The authors declare that there were no financial conflicts of interest.
ABBREVIATIONS
| GAM | Generalized additive model |
Footnotes
i-STAT handheld analyzer, Abbott Point of Care Inc, Princeton, NJ.
SAS, version 9.3, SAS Institute Inc, Cary, NC.
References
1. Nagy A, Murray JK, Dyson SJ. Horse-, rider-, venue- and environment-related risk factors for elimination from Fédération Equestre Internationale endurance rides due to lameness and metabolic reasons. Equine Vet J 2014;46: 294–299.
2. Nagy A, Murray JK, Dyson SJ. Descriptive epidemiology and risk factors for eliminations from Fédération Equestre Internationale endurance rides due to lameness and metabolic reasons (2008–2011). Equine Vet J 2014; 46:38-44.
3. Younes M, Robert C, Cottin F, et al. Speed and cardiac recovery variables predict the probability of elimination in equine endurance events. PLoS ONE 2015;10: e0137013.
4. Fielding CL, Meier CA, Balch OK, et al. Risk factors for the elimination of endurance horses from competition. J Am Vet Med Assoc 2011;239: 493–498.
5. Schott HC II, Marlin DJ, Geor RJ, et al. Changes in selected physiological and laboratory measurements in elite horses competing in a 160 km endurance ride. Equine Vet J Suppl 2006;36: 37–42.
6. Fielding CL, Magdesian KG, Rhodes DM, et al. Clinical and biochemical abnormalities in endurance horses eliminated from competition for medical complications and requiring emergency medical treatment: 30 cases (2005–2006). J Vet Emerg Crit Care (San Antonio) 2009; 19:473-478.
7. Carlson GP, Ocen PO, Harrold D. Clinicopathologic alterations in normal and exhausted endurance horses. Theriogenology 1976;6: 93–104.
8. Spooner HS, Nielsen BD, Schott HC II, et al. Sweat composition in Arabian horses performing endurance exercise on forage-based, low Na rations. Equine Vet J Suppl 2010;38: 382–386.
9. Hejłasz Z, Nicpon J, Czerw P. The role of sweat in maintaining the stimulation of effort homeostasis in horses. Arch Vet Pol 1994;34: 231–239.
10. McCutcheon LJ, Geor RJ, Ecker GL, et al. Equine sweating responses to submaximal exercise during 21 days of heat acclimation. J Appl Physiol 1999;87: 1843–1851.
11. Trigo P, Castejon F, Riber C, et al. Use of biochemical parameters to predict metabolic elimination in endurance rides. Equine Vet J Suppl 2010;38: 142–146.
12. Muñoz A, Riber C, Trigo P, et al. Dehydration, electrolyte imbalances and renin-angiotensin-aldosterone-vasopressin axis in successful and unsuccessful endurance horses. Equine Vet J Suppl 2010;38: 83–90.
13. Barnes A, Kingston J, Beetson S, et al. Endurance veterinarians detect physiologically compromised horses in a 160 km ride. Equine Vet J Suppl 2010;38: 6–11.
14. Shearer S. Dehydration and serum electrolyte changes in South African gold miners with heat disorders. Am J Ind Med 1990;17: 225–239.
15. Larsson J, Pilborg PH, Johansen M, et al. Physiological parameters of endurance horses pre- compared to post-race, correlated with performance: a two race study from Scandinavia. ISRN Vet Sci 2013;68: 43–53.
16. Weir MR, Espaillat R. Clinical perspectives on the rationale for potassium supplementation. Postgrad Med 2015;127: 539–548.
17. Luzardo L, Silvariño R, Boggia J, et al. Severe hypokalemic rhabdomyolysis. Report of six cases [in Spanish]. Rev Med Chil 2014;142: 651–655.
