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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.

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Submitted genomic data for respiratory viruses reflect the emergence and spread of new variants. Although delays in submission limit the utility of these data for prospective surveillance, they may be useful for evaluating other surveillance sources. However, few studies have investigated the use of these data for evaluating aberration detection in surveillance systems. Our study used a Bayesian online change point detection algorithm (BOCP) to detect increases in the number of submitted genome samples as a means of establishing 'gold standard' dates of outbreak onset in multiple countries. We compared models using different data transformations and parameter values. BOCP detected change points that were not sensitive to different parameter settings. We also found data transformations were essential prior to change point detection. Our study presents a framework for using global genomic submission data to develop 'gold standard' dates about the onset of outbreaks due to new viral variants.

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In recent years, a large focus has been placed on managing training load for injury prevention. To minimise injuries, training recommendations should be based on research that examines causal relationships between load and injury risk. While observational studies can be used to estimate causal effects, conventional methods to study the relationship between load and injury are prone to bias. The target trial framework is a valuable tool that requires researchers to emulate a hypothetical randomised trial using observational data. This framework helps to explicitly define research questions and design studies in a way that estimates causal effects. This article provides an overview of the components of the target trial framework as applied to studies on load and injury and describes various considerations that should be made in study design and analyses to minimise bias.

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BACKGROUND: Musculoskeletal injuries are a common occurrence in sport. The goal of sport injury epidemiology is to study these injuries at a population level to inform their prevention and treatment. MAIN BODY: This review provides an overview of musculoskeletal sport injuries and the musculoskeletal system from a biological and epidemiologic perspective, including injury mechanism, categorizations and types of sport injuries, healing, and subsequent injuries. It is meant to provide a concise introductory substantive background of musculoskeletal sport injuries for epidemiologists who may not have formal training in the underlying anatomy and pathophysiology. CONCLUSION: An understanding of sport injuries is important for researchers in sport injury epidemiology when determining how to best define and assess their research questions and measures.

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OBJECTIVE: The interplay between dysphagia, cancer, and mortality in idiopathic inflammatory myopathies (IIM) has not been carefully studied. The aim of this study was to investigate possible effect modification of cancer on the association between dysphagia and mortality in early IIM. METHODS: A multi-center cohort of 230 adult IIM patients with dysphagia assessment within 6 months of disease onset was assembled. Crude mortality rates in IIM patients exposed or not to dysphagia were estimated for the 5-year period following cohort entry. To explore possible effect modification of cancer on the association between dysphagia and mortality, adjusted Cox models stratified on cancer status were performed as well as an interaction model. RESULTS: Mortality rates per 100 person-years for IIM patients exposed to dysphagia were 2.3 (95 %CI 1.0 to 4.5) in those without cancer compared to 33.3 (95 %CI 16.6 to 59.5) in those with cancer. In stratified Cox models, the main effect of dysphagia was HR 0.5 (95 %CI 0.2 to 1.5) in non-cancer and 3.1 (95 %CI 1.0 to 10.2) in cancer patients. In the interaction model, the combination of dysphagia and cancer yielded a HR of 6.4 (1.2 to 35.1). CONCLUSION: In this IIM cohort, dysphagia in non-cancer patients was not associated with increased mortality, while it was in presence of cancer, supporting effect modification of cancer on the association between dysphagia and mortality. This suggests that IIM patients with and without cancer differ and separate analyses for the two groups should be conducted when the outcome of interest is mortality.

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When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to incorporate primary studies reporting sample medians in meta-analysis, yet there are currently no comprehensive software tools implementing these methods. In this paper, we present the metamedian R package, a freely available and open-source software tool for meta-analyzing primary studies that report sample medians. We summarize the main features of the software and illustrate its application through real data examples involving risk factors for a severe course of COVID-19.

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Return-to-play decision making should be based on all the advantages and disadvantages of return to play for athletes, not just the risk of injury. For competitive athletes, this includes the effect of early versus delayed return to sport on performance. In this paper, we address the questions "How can I estimate the effect of injury on the individual's performance at return to play?" and "What is the effect of delaying return to sport on the individual's performance?". To address these questions, we describe (1) some foundational concepts, design and analytical challenges related to estimating the causal effect of return to play timing on performance in the athlete, (2) additional challenges if one is interested in the effects of delaying return to play and (3) differences when the questions relate to the team's performance. Although the analytical strategies described appear complicated, coaches and athletes make these judgements informally every day without explicitly stating their assumptions. Using a formal approach should help analysts provide the most valid answers to the questions asked by athletes and coaches. In brief, the choice of a comparison group depends on the research question and requires that one consider the hypothetical performance trajectory of the athlete had they never been injured. Thus, the optimal comparison group depends on the shape of the expected trajectory and the specific research question being asked.

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We consider the setting of an aggregate data meta-analysis of a continuous outcome of interest. When the distribution of the outcome is skewed, it is often the case that some primary studies report the sample mean and standard deviation of the outcome and other studies report the sample median along with the first and third quartiles and/or minimum and maximum values. To perform meta-analysis in this context, a number of approaches have recently been developed to impute the sample mean and standard deviation from studies reporting medians. Then, standard meta-analytic approaches with inverse-variance weighting are applied based on the (imputed) study-specific sample means and standard deviations. In this article, we illustrate how this common practice can severely underestimate the within-study standard errors, which results in poor coverage for the pooled mean in common effect meta-analyses and overestimation of between-study heterogeneity in random effects meta-analyses. We propose a straightforward bootstrap approach to estimate the standard errors of the imputed sample means. Our simulation study illustrates how the proposed approach can improve the estimation of the within-study standard errors and consequently improve coverage for the pooled mean in common effect meta-analyses and estimation of between-study heterogeneity in random effects meta-analyses. Moreover, we apply the proposed approach in a meta-analysis to identify risk factors of a severe course of COVID-19.

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Purpose: Researchers often use model-based multiple imputation to handle missing at random data to minimize bias. However, constraints within the data may sometimes result in implausible values, making model-based imputation infeasible. In these contexts, we illustrate how random hot deck imputation can allow for plausible multiple imputation in longitudinal studies. Patients and Methods: Our motivating example is the Childhood Health, Activity, and Motor Performance School Study Denmark (CHAMPS-DK), a prospective cohort study that measured weekly sports participation for 1700 Danish schoolchildren. Using observed data on 4 variables (pain, activity frequency, sport, sport counts), we created a gold-standard data set without missing data. We then created a synthetic data set by setting some variable values to missing based on a prediction model that mimicked real-data missingness patterns. To create 5 imputed data sets, we matched each record with missing data to several fully observed records, generated probabilities from matched records, and sampled from these records based on the probability of each occurring. We assessed variability and agreement (kappa) between the imputed data sets and the gold-standard data set. We compare results to common model-based imputation methods. Results: Variability across data sets appeared reasonable. The range of kappa for the random hot deck approach was moderate for activity frequency (0.65 to 0.71) and sport (0.59 to 0.85), and poor for common model-based approaches (range 0.00 to 0.11). The range of kappas for sport count was strong (0.87 to 0.97) for random hot deck imputation and weak to moderate (0.55 to 0.71) for common model-based imputation. Agreement was higher when more information was present, and when prevalence was higher for our binary variable sport. Conclusion: Random hot deck imputation should be considered as an alternative method when model-based approaches are infeasible, specifically where there are constraints within and between covariates.

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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.

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OBJECTIVES: To illustrate why the research question determines whether and how sport medicine investigators should adjust for workload when interested in interventions or causal risk factors for injury. DESIGN: Theoretical conceptualization. METHODS: We use current concepts of causal inference to demonstrate the advantages and disadvantages of adjusting for workload through different analytic approaches when evaluating causal effects on injury risk. RESULTS: When a risk factor of interest changes workload, including workload in the regression will cause bias. When workload represents time-at-risk (e.g. games played, minutes run), including workload as an offset in Poisson regression provides a comparison of injury rates (injuries per unit time). This is equivalent to including log(workload) as an independent variable with the coefficient fixed to 1. If workload is included as an independent variable instead of an offset, using log(workload) rather than workload is more consistent with theory. This practice is similar to the principles of allometric scaling. When workload represents a combination of both time-at-risk and intensity, such as with session ratings of perceived exertion, the optimal analytical strategy may require modeling time-at-risk and intensity separately rather than as one factor. CONCLUSIONS: Whether to account for recent workload or not, and how to account for recent workload, depends on the research question and the causal assumptions, both of which should be explicitly stated.

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Pulmonary hypertension (PH), a chronic and complex medical condition affecting 1% of the global population, requires clinical evaluation of right ventricular maladaptation patterns under various conditions. A particular challenge for clinicians is a proper quantitative assessment of the right ventricle (RV) owing to its intimate coupling to the left ventricle (LV). We, thus, proposed a patient-specific computational approach to simulate PH caused by left heart disease and its main adverse functional and structural effects on the whole heart. Information obtained from both prospective and retrospective studies of two patients with severe PH, a 72-year-old female and a 61-year-old male, is used to present patient-specific versions of the Living Heart Human Model (LHHM) for the pre-operative and post-operative cardiac surgery. Our findings suggest that before mitral and tricuspid valve repair, the patients were at risk of right ventricular dilatation which may progress to right ventricular failure secondary to their mitral valve disease and left ventricular dysfunction. Our analysis provides detailed evidence that mitral valve replacement and subsequent chamber pressure unloading are associated with a significant decrease in failure risk post-operatively in the context of pulmonary hypertension. In particular, right-sided strain markers, such as tricuspid annular plane systolic excursion (TAPSE) and circumferential and longitudinal strains, indicate a transition from a range representative of disease to within typical values after surgery. Furthermore, the wall stresses across the RV and the interventricular septum showed a notable decrease during the systolic phase after surgery, lessening the drive for further RV maladaptation and significantly reducing the risk of RV failure.

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Objective: The aim of this study was to determine the independent value of N-terminal pro b-type natriuretic peptide, high-sensitivity cardiac troponin T, and C-reactive protein to predict onset of cardiopulmonary disease in a large, multi-center systemic sclerosis cohort followed prospectively. Methods: Subjects from the Canadian Scleroderma Research Group registry with data on N-terminal pro b-type natriuretic peptide, high-sensitivity cardiac troponin T, and C-reactive protein were identified. Outcomes of interest were death, systolic dysfunction (left ventricular ejection fraction < 50% or medications for heart failure), pulmonary arterial hypertension by right heart catheterization, pulmonary hypertension by cardiac echocardiography (systolic pulmonary artery pressures ⩾ 45 mmHg), arrhythmias (pacemaker/implantable cardiac defibrillator or anti-arrhythmic medications), and interstitial lung disease. Multivariate Cox proportional hazard models were generated for each outcome. Results: A total of 675 subjects were included with a mean follow-up of 3.0 ± 1.8 years. Subjects were predominantly women (88.4%) with mean age of 58.2 ± 11.3 years and mean disease duration of 13.7 ± 9.1 years. One hundred and one (101, 15%) subjects died during follow-up, 37 (6.4 %) developed systolic dysfunction, 18 (2.9%) arrhythmias, 34 (5.1%) pulmonary arterial hypertension, 43 (7.3%) pulmonary hypertension, and 48 (12.3%) interstitial lung disease. In multivariate analyses, elevated levels of N-terminal pro b-type natriuretic peptide, high-sensitivity cardiac troponin T, and C-reactive protein were associated with increased risk of death, while elevated levels of N-terminal pro b-type natriuretic peptide and C-reactive protein were associated with increased risk of developing pulmonary hypertension. Conclusion: In systemic sclerosis, N-terminal pro b-type natriuretic peptide, high-sensitivity cardiac troponin T, and C-reactive protein have independent predictive value for death and pulmonary hypertension. A larger study would be required to determine the predictive value of these biomarkers for less common systemic sclerosis outcomes.

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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.

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Recent theoretical work in causal inference has explored an important class of variables which, when conditioned on, may further amplify existing unmeasured confounding bias (bias amplification). Despite this theoretical work, existing simulations of bias amplification in clinical settings have suggested bias amplification may not be as important in many practical cases as suggested in the theoretical literature. We resolve this tension by using tools from the semi-parametric regression literature leading to a general characterization in terms of the geometry of OLS estimators which allows us to extend current results to a larger class of DAGs, functional forms, and distributional assumptions. We further use these results to understand the limitations of current simulation approaches and to propose a new framework for performing causal simulation experiments to compare estimators. We then evaluate the challenges and benefits of extending this simulation approach to the context of a real clinical data set with a binary treatment, laying the groundwork for a principled approach to sensitivity analysis for bias amplification in the presence of unmeasured confounding.

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Herpes Simplex Virus (HSV) esophagitis is a relatively rare form of infectious esophagitis. Typically, patients with viral esophagitis are immunocompromised. HSV esophagitis in an immunocompetent patient is uncommonly reported. The objective of this case report is to discuss symptoms, investigations, imaging, and treatment of HSV esophagitis in a healthy adolescent male. A previously healthy 17-year-old male presented to the ED of our facility with a 5-day history of fever, odynophagia, lethargy, and 2 episodes of emesis that failed to resolve with antibiotic treatment. Investigations revealed a low platelet count, mild hyponatremia, hypochloremia, and an elevated AST and ALT. A respiratory infection panel as well as CMV IgG, HIV, Rickettsia, and EBV tests were negative. HSV-1 PCR was positive and upper endoscopy revealed a friable mucosa, erythema, and exudates in the lower esophagus and erythematous duodenopathy. The patient received a diagnosis of HSV esophagitis and was treated with a 14-day course of IV to PO acyclovir. There was a rapid improvement of his symptoms with antiviral therapy.

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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.

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OBJECTIVES: Although interstitial lung disease (ILD) occurs in over half of systemic sclerosis (SSc) patients and represents a leading cause of mortality, there are currently no preventative strategies. We evaluated if gastroprotective agents were associated with a lower incident risk of SSc-ILD. METHODS: An SSc cohort without clinically apparent ILD at baseline was constructed from the Canadian Scleroderma Research Group registry. The primary exposure was any use of gastroprotective agents. Treatment with promotility agents was assessed as a secondary exposure. Time to development of clinically apparent ILD was compared between exposed and unexposed person-time, using a multivariable marginal structural Cox model incorporating inverse probability of treatment weights to address time-varying confounding. RESULTS: In total, 798 subjects met inclusion criteria. At cohort entry, median disease duration was 7.6 (IQR 3.9-15.6) years. During a median 4.4 (IQR 2.6-7.2) years of follow-up, 158 new ILD cases were diagnosed, for a crude incidence of 4.4 (95% CI 3.8-5.1) events per 100 person-years. Most (2085, 73.4%) person-visits were exposed to gastroprotective agents, 579 (20.4%) were exposed to promotility agents, and 554 (19.5%) were exposed to both agents. The marginal structural weighted hazard ratio (HR) for incident ILD related to gastroprotective agents was 0.86 (95% CI 0.52-1.41). When exposure was defined as treatment with promotility agents, the weighted adjusted HR was 0.79 (95% CI: 0.35-1.77). CONCLUSION: In this large retrospective cohort study, we were unable to demonstrate a protective role for gastroprotective and promotility agents in preventing clinically apparent SSc-ILD.

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