The Effect of Bye Weeks on Injury Event Rates in the Canadian Football League.

OBJECTIVE: To determine the effect of bye weeks (no practices or games) on the injury event rate in the Canadian Football League (CFL). DESIGN: Historical (retrospective) cohort study. SETTING: CFL. PARTICIPANTS: CFL athletes between 2011 and 2018. INTERVENTION: CFL pseudorandom assignment of bye weeks each season (2011-2013: 1; 2014-2017: 2; 2018: 3). MAIN OUTCOME MEASURES: Game injury incident rate ratio (IRR) in the week following a bye week compared with non-bye weeks. Sensitivity analyses: IRR for the 2 and 3 weeks following a bye week. We conducted exploratory analyses for combined game and practice injury events because we did not have the number of players exposed during practice. RESULTS: The IRR was 0.96 (0.87-1.05), suggesting no meaningful effect of a bye week on the post-bye week game injury event rate. We obtained similar results for cumulative game injury events for subsequent weeks: IRR was 1.02 (0.95-1.10) for the 2 weeks following the bye week and 1.00 (0.93-1.06) for the 3 weeks following the bye week. The results were similar with 1, 2, or 3 bye weeks. However, the combined game and practice injury event rate was increased following the bye week [IRR = 1.14 (1.05-1.23)]. These results are expected if the break period results in medical clearance for preexisting injuries; increasing pain in these locations following the bye week would now be considered new injuries instead of "exacerbations." CONCLUSIONS: Bye weeks do not appear to meaningfully reduce the injury event rate. Furthermore, there was no injury reduction when adding additional bye weeks to the schedule.

Predicting Injury Risk Over Changes in Physical Activity in Children Using the Acute:Chronic Workload Ratio.

Limited research exists on the relationship between changes in physical activity levels and injury in children. In this study, we investigated the prognostic relationship between changes in activity, measured by the acute:chronic workload ratio (ACWR), and injury in children. We used data from the Childhood Health, Activity, and Motor Performance School Study Denmark (2008-2014), a prospective cohort study of 1,660 children aged 6-17 years. We modeled the relationship between the uncoupled 5-week ACWR and injury, defined as patient-reported musculoskeletal pain, using generalized additive mixed models. These methods accounted for repeated measures, and they improved model fit and precision compared with previous studies that used logistic models. The prognostic model predicted an injury risk of approximately 3% between decreases in activity level of up to 60% and increases of up to 30%. Predicted risk was lower when activity decreased by more than 60% (minimum of 0.5% with no recreational activity). Predicted risk was higher when activity increased by more than 30% (4.5% with a 3-fold increase in activity). Girls were at significantly higher risk of injury than boys. We observed similar patterns but lower absolute risks when we restricted the outcome to clinician-diagnosed injury. Predicted increases in injury risk with increasing activity were much lower than those of previous studies carried out in adults.

Observed Injury Rates Did Not Follow Theoretically Predicted Injury Risk Patterns in Professional Human Circus Artists.

OBJECTIVE: Identifying which types of athletes have increased injury risk (ie, predictive risk factors) should help develop cost-effective selective injury prevention strategies. Our objective was to compare a theoretical injury risk classification system developed by coaches and rehabilitation therapists, with observed injury rates in human circus acts across dimensions of physical stressors, acrobatic complexity, qualifications, and residual risks. DESIGN: Descriptive epidemiological study. SETTING: professional circus company. PATIENTS OR OTHER PARTICIPANTS: Human circus artists performing in routine roles between 2007 and 2017. ASSESSMENT OF RISK FACTORS: Characteristics of circus acts categorized according to 4 different dimensions. MAIN OUTCOME MEASURES: Medical attention injury rates (injury requiring a visit to the therapist), time-loss injury rates (TL-1; injury resulting in at least one missed performance), and time-loss 15 injury rates (TL-15; injury resulting in at least 15 missed performances). RESULTS: Among 962 artists with 1 373 572 performances, 89.4% (860/962) incurred at least one medical attention injury, 74.2% (714/962) incurred at least one TL-1 injury, and 50.8% (489/962) incurred at least one TL-15 injury. There were important inconsistencies between theoretical and observed injury risk patterns in each of the 4 dimensions for all injury definitions (medical attention, TL-1, and TL-15). CONCLUSIONS: Although theoretical classifications are the only option when no data are available, observed risk patterns based on injury surveillance programs can help identify artists who have a high (or low) theoretical risk but are nonetheless actually at low (or high) risk of injury, given their current roles. This will help develop more cost-effective selective injury prevention programs.

Effect of preschool childcare on school-aged children's adiposity in Quebec, Canada.

BACKGROUND: Regulated public childcare must follow nutrition and physical activity guidelines, but the impact of public childcare on childhood adiposity is unclear. OBJECTIVES: To estimate the effects of universal preschool childcare on children's BMI in elementary school in Quebec, Canada, and whether the effects differed in children from more or less advantaged families. METHODS: For 1657 children enrolled in the Quebec Longitudinal Study of Child Development (1998-2010), BMI z-scores (BMIz) from 6 to 13 years were regressed on the childcare used from 2 to 5 years, adjusted for pre-childcare variables. Average treatment effects were estimated using the Bayesian multilevel linear regression and g-computation for four childcare profiles: 1) parental care or full-time care (35 hours/week) in a 2) centre-based, 3) regulated home-based or 4) unregulated home-based arrangement. RESULTS: Had all participants attended centre-based care, mean BMIz in kindergarten would have been 0.38 (95% credible interval [CrI] 0.23, 0.52), which was 0.40 (95% CrI 0.14, 0.65) SD higher than regulated home-based, 0.20 (95% CrI -0.04, 0.43) SD higher than unregulated home-based and 0.36 (95% CrI 0.11, 0.60) SD higher than parental care. By 12 years, mean BMIz had increased for all childcare profiles, but differences between childcare profiles had diminished. CONCLUSIONS: Although centre-based childcare was associated with an earlier rise in BMI, compared with informal care, it had no large, enduring effect, overall, or for less advantaged children, in particular.

The Influence of Time of Season on Injury Rates and the Epidemiology of Canadian Football Injuries.

OBJECTIVE: To describe injury rates and injury patterns in the Canadian Football League (CFL) according to time during the season, player position, injury type, and injury location. DESIGN: Prospective, cohort study. SETTING AND PARTICIPANTS: Eight seasons from CFL injury surveillance database. INDEPENDENT VARIABLES: Depending on the analysis, time of season (preseason, regular, and playoffs), player position, injury type, and injury location. MAIN OUTCOME MEASURES: Medical attention and time-loss injury rates per 100 athletes at risk (AAR), and prevalence of time-loss injuries per week. RESULTS: The average game injury rate was 45.2/100 AAR medical attention injuries and 30.7/100 AAR time-loss injuries. Injury rates declined by 1% per week over the season for both medical attention (rate ratio = 0.99) and time-loss (rate ratio = 0.99) injuries, with a substantial decline during the playoffs compared with preseason (rate ratio = 0.70-0.77). The number of ongoing time-loss injuries increased over the course of the regular season. Quarterbacks, offensive backs, and linebackers had the highest game injury rates. Joint/ligament and muscle/tendon injuries were the most common injury types for games and practices, respectively. The lower extremity was the most commonly affected area, specifically the lower leg/ankle/foot and hip/groin/thigh. CONCLUSIONS: There was a 1% decline in injury rate per week during the season and a 30% decline during the playoffs. The number of ongoing time-loss injuries increased over the regular season. Current results can aid league officials and medical staff in making evidence-based decisions concerning player safety and health.

The semiparametric accelerated trend-renewal process for recurrent event data.

Recurrent event data arise in many biomedical longitudinal studies when health-related events can occur repeatedly for each subject during the follow-up time. In this article, we examine the gap times between recurrent events. We propose a new semiparametric accelerated gap time model based on the trend-renewal process which contains trend and renewal components that allow for the intensity function to vary between successive events. We use the Buckley-James imputation approach to deal with censored transformed gap times. The proposed estimators are shown to be consistent and asymptotically normal. Model diagnostic plots of residuals and a method for predicting number of recurrent events given specified covariates and follow-up time are also presented. Simulation studies are conducted to assess finite sample performance of the proposed method. The proposed technique is demonstrated through an application to two real data sets.

Association between immunosuppressive therapy and course of mild interstitial lung disease in systemic sclerosis.

OBJECTIVE: Interstitial lung disease (ILD) is a leading cause of mortality in SSc. Little is known about the benefits of immunosuppressive drugs in mild ILD. Our aim was to determine whether use of CYC or MMF was associated with an improved ILD course in patients with normal or mildly impaired lung function. METHODS: A retrospective cohort of SSc subjects with ILD, disease duration below seven years and no exposure to CYC or MMF prior to the baseline visit was constructed from the Canadian Scleroderma Research Group registry. Subjects were categorized as having mild ILD if baseline forced vital capacity (FVC % predicted) was >85%. The primary exposure was any use of CYC or MMF at the baseline visit. FVC at one year was compared between exposed and unexposed subjects, using multivariate linear regression. RESULTS: Out of 294 eligible SSc-ILD subjects, 116 met criteria for mild ILD. In this subgroup, mean (s.d.) disease duration was 3.7 (2.0) years. Thirteen (11.2%) subjects were exposed to CYC or MMF at baseline. The one-year FVC was higher in exposed subjects compared with unexposed subjects, by a difference of 8.49% (95% CI: 0.01-16.98%). None of the exposed subjects experienced clinically meaningful progression over two years, whereas 24.6% of unexposed subjects did. CONCLUSION: In this real-world setting, CYC/MMF exposure at baseline was associated with higher FVC values and a lower risk of progression among subjects with mild ILD. These data suggest a window of opportunity to preserve lung function in SSc-ILD.

Doubly robust estimation and causal inference for recurrent event data.

Many longitudinal databases record the occurrence of recurrent events over time. In this article, we propose a new method to estimate the average causal effect of a binary treatment for recurrent event data in the presence of confounders. We propose a doubly robust semiparametric estimator based on a weighted version of the Nelson-Aalen estimator and a conditional regression estimator under an assumed semiparametric multiplicative rate model for recurrent event data. We show that the proposed doubly robust estimator is consistent and asymptotically normal. In addition, a model diagnostic plot of residuals is presented to assess the adequacy of our proposed semiparametric model. We then evaluate the finite sample behavior of the proposed estimators under a number of simulation scenarios. Finally, we illustrate the proposed methodology via a database of circus artist injuries.

Meta-analysis of the difference of medians.

We consider the problem of meta-analyzing two-group studies that report the median of the outcome. Often, these studies are excluded from meta-analysis because there are no well-established statistical methods to pool the difference of medians. To include these studies in meta-analysis, several authors have recently proposed methods to estimate the sample mean and standard deviation from the median, sample size, and several commonly reported measures of spread. Researchers frequently apply these methods to estimate the difference of means and its variance for each primary study and pool the difference of means using inverse variance weighting. In this work, we develop several methods to directly meta-analyze the difference of medians. We conduct a simulation study evaluating the performance of the proposed median-based methods and the competing transformation-based methods. The simulation results show that the median-based methods outperform the transformation-based methods when meta-analyzing studies that report the median of the outcome, especially when the outcome is skewed. Moreover, we illustrate the various methods on a real-life data set.

One-sample aggregate data meta-analysis of medians.

An aggregate data meta-analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (eg, the sample mean and its standard error). However, some studies may instead report the median along with various measures of spread. Recently, the task of incorporating medians in meta-analysis has been achieved by estimating the sample mean and its standard error from each study that reports a median in order to meta-analyze the means. In this paper, we propose two alternative approaches to meta-analyze data that instead rely on medians. We systematically compare these approaches via simulation study to each other and to methods that transform the study-specific medians and spread into sample means and their standard errors. We demonstrate that the proposed median-based approaches perform better than the transformation-based approaches, especially when applied to skewed data and data with high inter-study variance. Finally, we illustrate these approaches in a meta-analysis of patient delay in tuberculosis diagnosis.