Adding confidence to our injury burden estimates: is bootstrapping the solution?

Injury burden is a composite measure of injury incidence and mean severity that can be used to understand the overall impact of injuries and help identify priority areas for injury prevention. Injury burden has been used within rugby union epidemiological studies since the early 2000s, but it is now recognised and recommended within other sports, including the most recent International Olympic Committee consensus statement for the recording and reporting of epidemiological data on injury and illness. Injury burden is normally reported as athlete days absence per 1000 athletehours and is derived from the product of injury incidence (expressed as injuries sustained/1000 athlete-hours) and severity (expressed as the mean severity of injury in days). While the value of injury burden as an output measure from injury surveillance studies is evident, there appears to be some confusion in the literature regarding its calculation. For instance, some authors have used median severity to calculate injury burden rather than mean severity, as discussed in a recent critical review. In addition, there appears to be no clear guidance within the sports medicine literature regarding the most appropriate way to calculate confidence intervals (CIs) for this metric

More Than Just Adolescence: Differences in Fatigue Between Youth With Cerebral Palsy and Typically Developing Peers

Objective To quantify differences in fatigue and disordered sleep between adolescents with cerebral palsy (CP) and their typically developing peers. A secondary aim was to investigate the association between fatigue and disordered sleep in adolescents with CP. Methods A convenience sample of 36 youth with CP aged 10-18 years was matched for age and sex with 36 typically developing peers. The Fatigue Impact and Severity Self-Assessment (FISSA), the Patient-Reported Outcome Measurement Information System (PROMIS) fatigue profile, and the Sleep Disturbance Scale for Children (SDSC) were collected. Results Higher fatigue was reported in participants with CP than in their typically developing peers based on the FISSA total score (mean paired difference=19.06; 99% confidence interval [CI], 6.06-32.1), the FISSA impact subscale (mean paired difference=11.19; 99% CI, 3.96-18.4), and the FISSA Management and Activity Modification subscale (mean paired difference=7.86; 99% CI, 1.1-14.6). There were no differences between groups in the PROMIS fatigue profile (mean paired difference=1.63; 99% CI, -1.57-4.83) or the SDSC total score (mean paired difference=2.71; 99% CI, -2.93-8.35). Conclusion Youth with CP experienced significantly more fatigue than their peers as assessed by a comprehensive measure that considered both general and diagnosis-specific concerns. Sleep did not differ between youth with CP and their typically developing peers. These findings underscore the need to consider the clinical management of fatigue across the lifespan of individuals with CP to prevent the associated deterioration of functional abilities

The impact of concussion on cardiac autonomic function:a systematic review

<p><i>Primary objective</i>: To evaluate the evidence regarding the effect of concussion on cardiac autonomic function (CAF).</p> <p><i>Inclusion criteria</i>: Original research; available in English; included participants with concussion or mild traumatic brain injury (mTBI) and a comparison group; included measures of heart rate (HR) and/or heart rate variability (HRV) as outcomes. Studies of humans (greater than 6 years old) and animals were included.</p> <p><i>Critical appraisal tools</i>: The Downs and Black (DB) criteria and Structured Effectiveness Quality Evaluation Scale (SEQES).</p> <p><i>Results</i>: Nine full-length articles and four abstracts were identified. There is conflicting evidence regarding CAF at rest following concussion. There is evidence of elevated HR and reduced HRV with low-intensity, steady-state exercise up to 10 days following concussion. There was no significant difference in HRV during isometric handgrip testing or HR while performing cognitive tasks following concussion. The validity of current literature is limited by small sample sizes, lack of female or paediatric participants, methodological heterogeneity and lack of follow-up.</p> <p><i>Conclusions</i>: While there is some evidence to suggest CAF is altered during physical activity following concussion, methodological limitations highlight the need for further research. Understanding the effect of concussion on CAF will contribute to the development of more comprehensive concussion management strategies.</p

Higher Rates of Head Contacts, Body Checking, and Suspected Injuries in Ringette Than Female Ice Hockey:Time to Ring in Opportunities for Prevention

Objective: Ringette is a popular team ice sport in Canada, primarily played by females. Bodychecking is prohibited at all levels of play. This study used video-analysis to evaluate physical contact (PC), head contact (HC), and suspected injury and concussion incidence rates (IR) in youth ringette. Study Design: Cross-sectional. Subjects: Youth ringette players from the 2021-2022 season playing in the U16 (ages 14-15) or U19 (ages 16-18) age groups (A or AA levels). Games were filmed from regular season, provincials, and nationals (AA only). Observation Technique: Game video-recordings were analyzed using Dartfish video-analysis software. Validated criteria were used to assess trunk PC intensity (levels 1-3=lower-intensity PC, levels 4-5=higher-intensity bodychecking), HC type (HC1=direct player-to-player, HC2=indirect), suspected injury (concussion, non-concussion), and penalty enforcement. Outcome Measures: Multivariable Poisson regression analyses (adjusted for cluster by teamgame, offset by game-minutes) were used to estimate PC, HC, and suspected injury and concussion IRs. Incidence rate ratios (IRR) were used to compare IR across age groups, levels of play, and game types. Proportions of bodychecks and HC1s penalized were reported. Results: Seventy-eight team-games were included (U16 n=40, U19 n=38; A n=30, AA n=48; regular season n=30, provincials n=32, nationals n=16). The overall bodychecking IR was 17.34/100 team-minutes (95% CI:14.80-20.33), HC 19.09/100 team-minutes (95% CI:16.7421.78), suspected injury 1.53/100 team-minutes (95% CI:1.13-2.09), and suspected concussion 0.74/100 team-minutes (95% CI:0.48-1.13). Only 29% (95% CI:24.97-32.59) of bodychecks and 7% (95% CI:4.76-9.70) of HC1s were penalized. No differences were found in bodychecking, HCs, or suspected injury and concussion IRs between age groups or levels of play. Bodychecking IRs were 64% (IRR=1.64; 95% CI:1.13-2.39) higher in provincials and 24% (IRR=1.24; 95% CI:1.02-1.50) higher in nationals than regular season games. A 31% (IRR=0.69; 95% CI:0.49-0.97) lower rate of HCs was reported in national games compared to provincial games. Bodychecking was the most common mechanism for concussion (70%) and nonconcussion injuries (67%), with concussions most often associated with HC2s (62.5%). Conclusions: Bodychecking and HC1 IRs were high among youth ringette players, despite rules prohibiting them. Future research should target prevention strategies aimed to reduce HC1s and bodychecking to reduce injury and concussion IRs in youth ringette

Concurrent validity and reliability of a semi-automated approach to measuring the magnetic resonance imaging morphology of the knee joint in active youth

Post-traumatic knee osteoarthritis is attributed to alterations in joint morphology, alignment, and biomechanics triggered by injury. While magnetic resonance (MR) imaging-based measures of joint morphology and alignment are relevant to understanding osteoarthritis risk, time consuming manual data extraction and measurement limit the number of outcomes that can be considered and deter widespread use. This paper describes the development and evaluation of a semi-automated software for measuring tibiofemoral and patellofemoral joint architecture using MR images from youth with and without a previous sport-related knee injury. After prompting users to identify and select key anatomical landmarks, the software can calculate 37 (14 tibiofemoral, 23 patellofemoral) relevant geometric features (morphology and alignment) based on established methods. To assess validity and reliability, 11 common geometric features were calculated from the knee MR images (proton density and proton density fat saturation sequences; 1.5 T) of 76 individuals with a 3-10-year history of youth sport-related knee injury and 76 uninjured controls. Spearman's or Pearson's correlation coefficients (95% CI) and Bland-Altman plots were used to assess the concurrent validity of the semi-automated software (novice rater) versus expert manual measurements, while intra-class correlation coefficients (ICC 2,1; 95%CI), standard error of measurement (95%CI), 95% minimal detectable change, and Bland-Altman plots were used to assess the inter-rater reliability of the semi-automated software (novice vs resident radiologist rater). Correlation coefficients ranged between 0.89 (0.84, 0.92; Lateral Trochlear Inclination) and 0.97 (0.96, 0.98; Patellar Tilt Angle). ICC estimates ranged between 0.79 (0.63, 0.88; Lateral Patellar Tilt Angle) and 0.98 (0.95, 0.99; Bisect Offset). Bland-Altman plots did not reveal systematic bias. These measurement properties estimates are equal, if not better than previously reported methods suggesting that this novel semi-automated software is an accurate, reliable, and efficient alternative method for measuring large numbers of geometric features of the tibiofemoral and patellofemoral joints from MR studies. </p