Risk factors for superficial digital flexor tendinopathy in Thoroughbred racehorses in steeplechase starts in the United Kingdom (2001–2009)

The Veterinary Journal 195 (2013) 325–330

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Risk factors for superficial digital flexor tendinopathy in Thoroughbred racehorses in steeplechase starts in the United Kingdom (2001–2009) R.J.M. Reardon a,⇑, L.A. Boden a, D.J. Mellor a, S. Love a, J.R. Newton b, A.J. Stirk c, T.D.H. Parkin a a Boyd Orr Centre for Population and Ecosystem Health, School of Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, 464 Bearsden Road, Glasgow G61 1QH, UK b Animal Health Trust, Lanwades Park, Kentford, Newmarket, Suffolk CB8 7UU, UK c Equine Science and Welfare Department, British Horseracing Authority, 75 High Holborn, London WC1V 6LS, UK

a r t i c l e

i n f o

Article history: Accepted 23 June 2012

Keywords: Racehorse Superficial digital flexor tendinopathy Steeplechase racing

a b s t r a c t The objective of this study was to identify risk factors for superficial digital flexor (SDF) tendinopathy in Thoroughbred horses in steeplechase races in the United Kingdom. Potential risk factors for SDF tendinopathy were studied between 1st January 2001 and 31st December 2009 using a cohort study design with 648 injuries sustained in 102,894 starts. Potential risk factors were screened using univariable logistic regression prior to multivariable model building. In the final multivariable model, 12 statistically significant risk factors were identified. Variables that increased the odds of SDF tendinopathy included firmer going, increased horse age, and racing in the summer compared to other seasons. Variables that decreased the odds included having a higher official rating and the number of starts in the preceding days. Fewer and different risk factors were identified than in an equivalent model of SDF tendinopathy in hurdle racing, highlighting potential differences between these disciplines. Further collection of training and racecourse information would be beneficial and may help to explain further some of the associations identified in this study. The results will facilitate the development of strategies to improve overall safety of horses in UK steeplechase racing. Ó 2012 Elsevier Ltd. All rights reserved.

Introduction Tendon injuries are common in Thoroughbred racehorses (Thorpe et al., 2010), with the superficial digital flexor (SDF) tendon being the most commonly injured (Marr et al., 1993; Williams et al., 2001; Ely et al., 2004, 2009; Pinchbeck et al., 2004; Takahashi et al., 2004; Lam et al., 2007a; Avella et al., 2009). Whilst multiple studies have investigated risk factors for SDF tendinopathy (Mohammed et al., 1991, 1992; Cohen et al., 1997; Takahashi et al., 2004; Perkins et al., 2005a; Lam et al., 2007b; Reardon et al., 2012), the studies performed in the United Kingdom either were focussed on training related factors for relatively small cohorts of trainers and horses or were not focussed solely on steeplechase horses. Although steeplechase racing has been recognised as the racing discipline in which SDF tendinopathy occurs most frequently (Williams et al., 2001), no previous studies have looked specifically at the risks of sustaining the injury in this discipline.

⇑ Corresponding author. Tel.: +44 141 3308432. E-mail address: [email protected] (R.J.M. Reardon). 1090-0233/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tvjl.2012.06.033

In a previous study using similar methods (Reardon et al., 2012), multiple risk factors for SDF tendinopathy in hurdle racing were identified. Steeplechase racing is the other major form of jump racing in the UK and whereas this is also always on a turf surface, it involves larger jump obstacles and often longer race distances than hurdle racing. It is plausible, therefore, that different risk factors exist in this type of racing. The aim of the present study was to identify risk factors associated with steeplechase racing and to compare these with those identified in hurdle racing. Materials and methods Potential risk factors for SDF tendinopathy in steeplechase starts in the UK were assessed using a cohort study. In order to allow inclusion of horse, race and track as different levels in risk factor analysis, the study was conducted at the start level (a ‘start’ being a horse starting a race) and included 648 injuries sustained in 102,894 starts. Information from all horse injuries treated at the racecourses was available from between 1st January 2000 and 31st December 2009 from the British Horseracing Authority (BHA) database. Details from every horse and race were available for the same time period from Weatherbys, the providers of administrative services to the BHA. Because detailed race information was not available prior to 2000, it was decided to analyse data from 1st January 2001 to 31st December 2009 to allow a more complete analysis of potential associations between previous racing intensity and SDF tendinopathy.

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Injuries SDF tendinopathy was diagnosed by racecourse veterinary surgeons after a race and whilst the horse was still at the racecourse. Injuries were identified based on the findings of physical examination and recorded by attending BHA veterinary officers. All starts, including those made by horses which had previously been reported to have sustained an injury, were included in the analysis.

Risk factors Potential risk factors were identified from the literature and from a priori hypotheses. Risk factors associated with the horse, its racing history, the race, jockey and track were considered. The Weatherbys’ database was used as the major source of performance histories for all horses. Gender of the horse was categorised as male or female. Official ‘going reports’ were used to describe the racing surface (firm, good to firm, good, good to soft, soft, heavy). Official going was produced by the Clerk of each course, following assessment of the penetration and shear of a stick. Age was recorded as age in years at each start and was based on the convention that 1st January is the official birthday of Thoroughbred racehorses in the UK. Horse ‘years completed in racing’ were calculated by subtracting each horse’s age (in years) at first start from the horses age (in years) at each subsequent start. Run sequence referred to the race’s positions on the race card, with the card divided into thirds: early, middle and late. Number of starts in preceding time periods (3 months, 4–6 months, 7–9 months, 10–12 months and greater than 1 year) were calculated, as recommended at the Havermeyer Symposium (Parkin, 2007). In order to produce an overall guide to trainer and jockey success, three scores were produced from the 10 years of race data available: Percentage of trainer/jockey starts that finished first in a race; percentage of trainer/jockey starts that finished in the top three in a race; and the mean value of a score based on finish position in all starts made by horses sent out by each trainer or ridden by each jockey (30 points for finishing 1st, 20 points for finishing 2nd or 3rd, 10 points for finishing and 0 points for not finishing). Previous SDF injury was defined from all cases of SDF tendinopathy recorded in the BHA database from any type of race from the years 2000– 2009, such that horses running in steeplechase races that had previously sustained a SDF tendinopathy whilst running in flat, hurdle or national hunt flat races, were labelled as having had a previous tendon injury. A total of 122 variables for each start (32 horse-related variables, 50 prior racing history-related variables, 25 race related variables, 5 trainer-related variables, 5 jockey-related variables and 5 track-related variables) were available for analysis. Details of the 102,894 study starts and associated risk factor data were downloaded into an Excel spread sheet (Microsoft 2010).

individually from the model; these variables were then removed from the model if their odds ratios changed direction (i.e. changed from a positive to a negative association or vice versa), or if their P-values became >0.05. Biologically plausible interaction terms were created and assessed in the final model. Interaction terms with P values of <0.05 were retained in the final model. Clustering of starts was investigated within the horse, horse dam, horse sire, trainer, jockey, year, course and meet. Residual intra-class correlation coefficients (rho) were estimated for each level of clustering, using a latent variable approach (Snijders and Bosker, 1999), by including each hierarchical level as a random effect, one by one, in the final multivariable logistic regression model. Fit of the model and regression diagnostics The fit of the final multivariable model was assessed using the Hosmer–Lemeshow goodness-of-fit test (Hosmer and Lemeshow, 2000). Regression diagnostics were performed on the model. Covariate patterns with the greatest leverage, delta betas, delta chi-square and delta deviance values were identified. The individuals within these covariate patterns were then removed from the model and the change in the value of the coefficients was reassessed (Hosmer and Lemeshow, 2000). The predictive ability of the model was determined by generating a receiver operating characteristic (ROC) curve. Statistical analysis software All statistical analyses were performed using Stata 11 (S.E.) statistical software. Epi-Info 6 was used to calculate statistical power.

Results The 102,894 study starts were represented in the study population by 15,117 horses, 1328 jockeys, 2343 trainers and 44 racecourses. The study starts occurred in 12,003 races at 4347 race meets and on 2438 race dates. Six hundred and forty-eight SDF tendinopathies were recorded in 626 horses. One hundred and thirty-one horses started in at least one steeplechase race subsequent to SDF tendinopathy, and 40 of these (31%) sustained another SDF tendinopathy and two (5%) sustained a third SDF tendinopathy, whilst competing in steeplechase races. Univariable analysis

Power of the study The study had at least 80% power to identify odds ratios of 1.4 or more, with 95% confidence, when the prevalence of exposure in the population was between 11% and 82%.

Of the 122 variables screened at the univariable level 38 were submitted for analysis in the multivariable forward stepwise analysis. Details of these variables are shown in Appendix A. Multivariable analysis

Statistical analysis The relationship between each continuous variable and the outcome was examined by graphical representation of the log odds. If the relationship was nonlinear, categorical or alternative: binary, polytomous categorical (quartiles or quintiles) or quadratic and cubic terms were considered in the univariable and multivariable models in order to find the ‘best-fit’ for the model (Dohoo et al., 2003), using the lowest Akaike Information Criteria (AIC) value as a guide. Nominal and ordinal categorical variables were numerically coded sequentially. Univariable logistic regression was performed to identify potential risk factors from variables considered biologically plausible or supported by the literature. Variables with P-values <0.2 as well as any considered biologically plausible and any that had been reported as being significant in other studies, were considered for inclusion in the multivariable model. Variables were ordered by AIC and log likelihood values prior to sequential insertion into a single level multivariable regression model. Variables were retained in the multivariable model if likelihood ratio test P values were <0.05 (Hosmer and Lemeshow, 2000). The Wald test P value was used when comparing categories with the reference category. Potential confounders were evaluated by resubmitting all of the variables from the univariable analyses that were not included in the final model after the forward stepwise process of model building. The effect of each potential confounder on the estimates for variables in the final model was assessed by adding each one, one at a time into the final model. If addition of the potentially confounding variable altered odds ratios for statistically significant variables in the final model by more than 20% (Dohoo et al., 2003), confounding was considered to be present, the confounder was retained in the final model and adjusted odds ratios were reported for variables in the final model. Correlation coefficients were produced between all continuous variables in the multivariable model. Variables with correlation coefficients of >0.4 and < 0.4 were further examined by investigating the effect of removing them

In the final multivariable model 12 variables were found to be associated with SDF tendinopathy (Table 1). None of the interaction terms investigated was found to be statistically significant. Assessment of clustering Residual intra-class correlation coefficients (rho) were estimated for horse (rho 0.00002), horse dam (rho 0.00003), horse sire (rho 0.05), trainer (rho 0.04), jockey (rho 0.002), course (rho 0.009), race (0.10) and meet (rho 0.12). Changes in coefficients and standard errors were less than 10% for all assessed random effects compared with the single level model. Horse was retained as a random effect in the final model. Performance of the fixed-effects multivariable model The final single-level multivariable model was not affected by influential covariate patterns. There were sufficient injuries per coefficient to justify the complexity of the model (Bagley et al., 2001). The Hosmer–Lemeshow goodness-of-fit statistic was 8.16 (8 degrees of freedom, P value = 0.42). The area under the ROC curve was 0.73.

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Table 1 Results of multivariable logistic regression analysis of risk factors for superficial digital flexor (SDF) tendinopathy in horses undertaking steeplechase racing in the United Kingdom (2001–2009). Risk factor for SDF tendinopathy Track related variables Track going Heavy and soft Good to soft Good Good to firm Firm Race related variables Race distance (km) Season Spring, autumn or winter Summer Time of race Afternoon Morning or evening Race position in run sequence Early Middle or late Horse related variables Age (years) Horse had previous SDF tendinopathy No Yes Horse official rating 0–115 >115 % of career as flat (per 10%) Horse number of starts in the previous 3 months 0–1 2–4 >4 Horse number of starts in the previous 10–12 months 0 1–7 >7 Horse number of starts greater than 1 year previously 0–15 >15

Number of starts n = 10,2894

Number of injuries (%) n = 648

Incidence rate per 1000 starts

25,775 20,417 36,852 19,006 844

66 (10) 102 (16) 277(43) 194 (30) 9 (1)

2.56 5 7.52 10.2 10.66

102,894

648 (100)

6.3

90,739 12,155

517 (80) 131 (20)

5.7 10.78

93,061 9833

571 (88) 77 (12)

24,790 78,104

P-value

Odds ratio (OR)

95% Confidence interval

<0.001 <0.001 <0.001 <0.001

1 (REF) 1.98 2.77 3.42 3.53

1.45–2.7 2.11–3.63 2.55–4.58 1.74–7.14

<0.001

1.37

1.23–1.53

0.001

1 (REF) 1.42

1.16–1.75

6.29 7.83

0.013

1 (REF) 0.74

0.58–0.95

179 (28) 469 (72)

7.22 6

0.039

1 (REF) 0.82

0.69–0.99

102,894

648 (100)

6.3

<0.001

1.19

1.14–1.25

102,199 695

606 (93.5) 42 (6.5)

5.9 60.43

<0.001

1 (REF) 8.51

6.1–11.88

78,947 23,947 102,894

567 (84) 81 (16) 648 (100) 0.031 169 (26) 285 (44) 194 (30)

7.18 3.38 6.3

1 (REF) 0.65 1.22

0.51–0.83 1.16–1.28

7.27 5.64 6.66

1 (REF) 0.77 0.84

0.63–0.93 0.68–1.03

393 (60.7) 251 (38.7) 4 (0.6)

9 4.26 15.94

<0.001 0.17

1 (REF) 0.61 2.03

0.52–0.72 0.75–5.53

394 (61) 254 (39)

7.53 5.02

<0.001

1 (REF) 0.42

0.34–0.51

<0.001

23,258 50,493 29,143 <0.001 43,666 58,977 251 52,319 50,575

<0.001 <0.001 0.031 0.008 0.1 <0.001

Bolded P values are likelihood ratio test P values and un-bolded P values are Wald test P values. The odds ratios can be interpreted as in the following examples: The odds of SDF tendinopathy were two times higher (twice as likely) on a good to soft track than on a track with a going of either ‘soft’ or ‘heavy’. The odds of SDF tendinopathy were 0.43 times lower (just under half as likely) for horses which had made greater than 15 starts greater than 1 year previously, compared to horses that had not.

Discussion This paper reports the results of the first study to identify risk factors for SDF tendinopathy specific to steeplechase races in the UK. The analysis benefits from access to a large cohort with a large number of injuries, but is limited by the reliance on diagnosis of SDF tendinopathy at the racecourse, which is likely to have resulted in under estimation of number of true cases. Along with this, the previous history of SDF tendinopathy is reliant on the horse having had the condition diagnosed at the racecourse and does not take into account any lesions diagnosed whilst in training, or racing outside the UK. Increased firmness of ground (going), increased race distance, increased percentage of career in flat racing, racing in the summer season compared to the other seasons and having had a previous SDF tendinopathy were all observed to be associated with increased likelihood of SDF tendinopathy. These factors were all observed in the study of hurdle races (Reardon et al., 2012) and are thought likely to be the result of similar aetiology to those discussed in that paper.

Horse age was found to be a risk factor for SDF tendinopathy. The predisposition of older horses to suffer from the condition has been recognised before (Williams et al., 2001; Perkins et al., 2005b). A number of studies have demonstrated that increased cumulative exercise is a risk factor for the condition (Estberg et al., 1995, 1998; Lam et al., 2007b) and it is considered likely that older horses would have undergone a greater amount of exercise than younger ones. Although the association between SDF tendinopathy and increasing horse age was observed at the univariable level in the hurdle analysis (Reardon et al., 2012), it was not retained in the final multivariable model following the inclusion of age at first start. Conversely in the current study, whilst age at first start was found to be significant at the univariable level in steeplechase racing, it was not retained within the multivariable model once horse age was included. Whilst the inclusion of only one of these variables in each final model is most likely the result of correlation between them rather than a different causal relationship, this difference may also be the result of differences in racing careers or age groups between the two racing disciplines: The steeplechase horses were generally older: median age 8 years (5–16),

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compared to 6 years (3–16) in the hurdle group; of greater age at first start: median age at first start 4 years (2–13) compared to 3 years (2–13); and fewer horses competing in steeplechase races had run in flat races 29% (4311/15,117) compared to 46% (13,479/29,285) of horses competing in hurdle races. Horses with official ratings in the top quartile (of official ratings) were observed to have a reduced likelihood of SDF tendinopathy. This could be the result of a genetic or anatomical trait in these animals making them better athletes and less prone to injury or could simply be related to the fact that horses with (sub-clinical) injuries run less well and so obtain a lower official rating, a manifestation of the ‘healthy horse effect’. Horses that ran middle or late compared to early in the run sequence were less likely to sustain SDF tendinopathy. The reason for this is unclear, although could be related to an unmeasured track related variable; with the track conditions being most likely to cause SDF tendinopathy at the start of the racing day. Alternatively this could be related to the class of horses, with potentially lower quality horses running in the early races. This finding differs from that from hurdle racing, in which running late in the sequence resulted in a lower likelihood of SDF tendinopathy than running early or middle (Reardon et al., 2012). This difference could be explained by differences in the allocation of races between the two disciplines. A similar association with time of racing (with races in the morning or evening having a lower likelihood of tendinopathy than races in the afternoon) was observed in hurdle racing (Reardon et al., 2012), reasons for which remain unclear. Notably only 10% of races were classified as starting in the morning or evening, so any potential impact on the overall risk of tendon injury that may result from identifying the reason for this finding is likely to be small. When horses’ number of starts in various time periods (3 monthly blocks) prior to a start were analysed, there were a number of significant associations with the risk of SDF tendinopathy. These associations were not directly comparable with those identified in the previous study of hurdle racing (Reardon et al., 2012), and are not easy to explain. Further analysis focussed on the effect of previous training and racing histories would be warranted to better explain these associations.

Risk Factor for SDF tendinopathy

Number of starts n=102894

TRACK RELATED VARIABLES Track Going Heavy and Soft 25775 Good to Soft 20417 Good 36852 Good to Firm 19006 Firm 844 Starts at that race course over 10 years (2000-2009) 1 to 2785 and 3404 to 5244 75437 2786 to 3403 27457 Days since last steeplechase race at that track 0 to 15 53738 16 to 30 29712 > 30 19444 RACE RELATED VARIABLES Race Distance (km) 102894 Sell / Claim Race No 102016 Yes 878 Season

A number of variables identified in hurdle racing (Reardon et al., 2012) were not identified as significant risk factors in the final multivariable model for steeplechase races: running in a selling or claiming race; weight carried; change in race distance or type from previous race; first race type; number of runners in race; year and days since last race at that track. The reasons for these differences are difficult to explain but may, in part, be the result of the reduced statistical power associated with fewer injuries in the current study.

Conclusions Similar to the evaluation of risk factors in hurdle racing, it would appear from this study that firm ground, increased age and previous SDF tendinopathy injury are all risk factors for subsequent injury. The multiple risk factors identified provide information that can be used to help review current regulations and racecourse management techniques. Not all of the observed associations and differences between disciplines can be readily explained by the data currently available. As a result, further research investigating unmeasured factors at racecourses is currently underway.

Conflict of interest statement None of the authors of this paper has a financial or personal relationship with other people or organisations that could inappropriately influence or bias the content of the paper. Acknowledgements The authors wish to thank the staff at the British Horseracing Authority and Weatherbys Limited for assistance with data collection, and the Horserace Betting Levy Board for funding the research.

Appendix A

Number of injuries (%) n=648

Incidence rate per 1000 starts

66 (10) 102 (16) 277(43) 194 (30) 9 (1)

2.56 5 7.52 10.2 10.66

442 (68) 206 (32)

Wald P-value

Odds Ratio (OR)

95% Confidence Interval

<0.001 <0.001 <0.001 <0.001

1 (REF) 1.96 2.95 4.01 4.2

1.42-2.67 2.25-3.86 3.03-5.31 2.08-8.45

5.86 7.5

0.003

1 (REF) 1.28

1.09-1.51

344 (53) 177 (27) 127 (20)

6.4 5.96 6.53

0.435 0.846

1 (REF) 0.93 1.02

0.78-1.12 0.83-1.25

648 (100)

6.3

<0.001

1.31

1.18-1.44

643 (99) 5 (1)

6.3 5.69

0.821

1 (REF) 0.9

0.37-2.18

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Appendix A (continued) Risk Factor for SDF tendinopathy

Number of starts n=102894

Number of injuries (%) n=648

Spring, Autumn or Winter 90739 517 (80) Summer 12155 131 (20) Maiden Race No 100781 622 (96) Yes 2113 26 (4) Number of Runners 102894 648 (100) Race position in run sequence Early 24790 179 (28) Middle or Late 78104 469 (72) Time of race Afternoon 93061 571 (88) Morning or Evening 9833 77 (12) TRAINER RELATED VARIABLES Trainer Mean Score (compared to other trainers in study) Bottom 75% 78552 542 (84) Top 25% 24342 106 (16) Trainer % Placed 102894 648 (100) Trainer % First 102894 648 (100) JOCKEY RELATED VARIABLES Jockey Mean Score 102894 648 (100) Jockey % Placed 102894 648 (100) Jockey % First 102894 648 (100) Amateur Jockey No 89528 532 (82) Yes 13366 116 (18) HORSE RELATED VARIABLES Age (years) 102894 648 (100) Age First Race (years) 102894 648 (100) Career length (years) 0 to 4 68013 389 (60) >4 34881 259 (40) Sex Male 94538 602 (93) Female 8356 46 (7) Horse Had Previous SDF Tendinopathy No 102199 606 (93.5) Yes 695 42 (6.5) Risk Factor for SDF tendinopathy Number of starts n=102894 Number of injuries (%) n=648 Incidence rate Wald P-value per 1000 starts HORSE RELATED VARIABLES CONTINUED Weight Carried (0.45 kg (lbs)) 102894 648 (100) First Race Type Flat, Hurdle or NHF 80506 494 (76) Steeplechase 22388 154 (24) First race Flat No 75905 495 (76) Yes 26989 153 (24) Horse % of career as flat 102894 648 (100) Horse Change in running distance since previous race Same / Decreased 67585 408 (63) Increased 35309 240 (37) Change in running distance since 102894 648 (100) previous race (m) Race type different to previous one

Incidence rate per 1000 starts

Wald P-value

Odds Ratio (OR)

95% Confidence Interval

5.7 10.78

<0.001

1 (REF) 1.9

1.57-2.3

6.17 12.3 6.3

0.001 0.199

1 (REF) 2.01 1.01

1.35-2.98 0.99-1.03

7.22 6

0.035

1 (REF) 0.83

0.7-0.99

6.14 7.83

0.044

1 (REF) 1.28

1.0-1.62

6.9 4.35 6.3 6.3

<0.001 <0.001 <0.001

1 (REF) 0.63 0.98 0.97

0.51-0.78 0.97-0.99 0.95-0.98

6.3 6.3 6.3

<0.001 0.002 0.007

0.92 0.99 0.98

0.89-0.96 0.98-1.0 0.96-0.99

5.94 8.68

<0.001

1 (REF) 1.46

1.2-1.79

6.3 6.3

<0.001 <0.001

1.14 1.12

1.1-1.19 1.07-1.17

5.72 7.43

0.001

1 (REF) 1.3

1.11-1.52

6.37 5.5

0.34

1 (REF 0.86

0.64-1.17

5.93 60.43

0.001

1 (REF) 10.78

7.81-14.88

Odds Ratio (OR)

95% Confidence Interval

6.3

0.122

1.01

1-1.01

6.14 6.88

0.214

1 (REF) 1.12

0.93-1.34

6.52 5.67 6.3

0.129 0.021

1 (REF) 0.87 1.01

0.72-1.04 1.0-1.01

6.04 6.8 6.3

0.144 0.044

1 (REF) 1.13 1.0

0.96-1.32 1.0-1.0

(continued on next page)

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Appendix A (continued) Risk Factor for SDF tendinopathy

Number of starts n=102894

Number of injuries (%) n=648

No 85589 539 (83) Yes 17305 109 (17) Days since horse’s last 102894 648 (100) steeplechase race Days since horse’s last race of any 102894 648 (100) type Horse’s total previous number of starts in any races 0 to 12 26130 230 (35) 13 to 21 27339 175 (27) >21 49425 243 (38) Horse number of starts in the previous 3 months 0 to 1 23258 169 (26) 2 to 4 50493 285 (44) >4 29143 194 (30) Horse number of starts in the 102894 648 (100) previous 4 to 6 months Horse number of starts in the previous 7 to 9 months None 60692 435 (67) >0 42202 213 (33) Horse number of starts in the previous 10 to 12 months 0 43666 393 (60.7) 1 to 7 58977 251 (38.7) >7 251 4 (0.6) Horse number of starts greater than 1 year ago 0 to 15 52319 394 (61) > 15 50575 254 (39) Horse’s Official Rating 0-115 78947 567 (88) >115 23947 81 (12)

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Incidence rate per 1000 starts

Wald P-value

Odds Ratio (OR)

95% Confidence Interval

6.3 6.3 6.3

0.99 0.006

1 (REF) 1 1.0

0.81-1.23 1.0-1.0

6.3

0.009

1.0

1.0-1.0

8.8 6.4 4.92

0.001 <0.001

1 (REF) 0.73 0.56

0.6-0.88 0.46-0.67

7.27 5.64 6.66 6.3

0.009 0.403 0.653

1 (REF) 0.78 0.92 1.01

0.64-0.94 0.74-1.13 0.96-1.06

7.17 5.05

<0.001

0.7

0.6-0.83

9 4.26 15.94

<0.001 0.254

1 (REF) 0.47 1.78

0.4-0.55 0.66-4.81

7.53 5.02

<0.001

1 (REF) 0.67

0.57-0.78

7.18 3.38

<0.001

0.47

0.37-0.59

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