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OBJECTIVE: To determine the Fragility Index of hamstring injury risk factors, defined as the minimum number of participants who would need to change classification to make a hamstring injury risk factor statistically nonsignificant. DESIGN: Retrospective secondary data analysis. METHODS: Studies that investigated 1 or more risk factors for hamstring injury, and presented sufficient data to develop a 2 × 2 contingency table were included. A systematic literature search and reference screening of a recent hamstring injury systematic review were conducted to identify 78 articles. Relative risk and 95% confidence intervals were determined and then systematically recalculated by removing 1 observation from the high-risk injury count and adding it to the high-risk noninjury count. The Fragility Index for a risk factor was the number of observations required to be moved between groups until the relative risk was no longer significant. RESULTS: The median Fragility Index of all hamstring injury risk factors was 3 (Q1-Q3 = 2-6). The Fragility Index for nonmodifiable risk factors was 3 (Q1-Q3 = 2-6) and 3 (Q1-Q3 = 2-5) for modifiable risk factors. Over 35% of all included hamstring injury risk factors had a Fragility Index of ≤2. CONCLUSION: Most statistically significant hamstring injury risk factors are fragile associations. The interpretation of significant hamstring injury risk factors should consider a range of statistical metrics, and while the Fragility Index should never be considered in isolation, it is an intuitive measure to help assess the robustness of findings. J Orthop Sports Phys Ther 2024;54(10):672-678. Epub 4 September 2024. doi:10.2519/jospt.2024.12300 .

Background/aim: This study aimed to determine which factors were most predictive of hamstring strain injury (HSI) during different stages of the competition in professional Australian Football., Methods: Across two competitive seasons, eccentric knee flexor strength and biceps femoris long head architecture of 311 Australian Football players (455 player seasons) were assessed at the start and end of preseason and in the middle of the competitive season. Details of any prospective HSI were collated by medical staff of participating teams. Multiple logistic regression models were built to identify important risk factors for HSI at the different time points across the season., Results: There were 16, 33, and 21 new HSIs reported in preseason, early in-season, and late in-season, respectively, across two competitive seasons. Multivariate logistic regression and recursive feature selection revealed that risk factors were different for preseason, early in-season, and late in-season HSIs. A combination of previous HSI, age, height, and muscle thickness were most associated with preseason injuries (median area under the curve [AUC], 0.83). Pennation angle and fascicle length had the strongest association with early in-season injuries (median AUC, 0.86). None of the input variables were associated with late in-season injuries (median AUC, 0.46). The identification of early in-season HSI and late in-season HSI was not improved by the magnitude of change of data across preseason (median AUC, 0.67)., Conclusions: Risk factors associated with prospective HSI were different across the season in Australian Rules Football, with nonmodifiable factors (previous HSI, age, and height) mostly associated with preseason injuries. Early in-season HSI were associated with modifiable factors, notably biceps femoris long head architectural measures. The prediction of in-season HSI was not improved by assessing the magnitude of change in data across preseason., (Copyright © 2023 by the American College of Sports Medicine.)

Objective: This study aimed to systematically review and meta-analyse the incidence and prevalence of hamstring injuries in field-based team sports. A secondary aim was to determine the impact of other potential effect moderators (match vs training; sport; playing surface; cohort age, mass and stature; and year when data was collected) on the incidence of hamstring injury in field-based team sports., Design: Systematic review and meta-analysis., Data Sources: CINAHL, Cochrane Library, MEDLINE Complete (EBSCO), Embase, Web of Science and SPORTDiscus databases were searched from database inception to 5 August 2020., Eligibility Criteria: Prospective cohort studies that assessed the incidence of hamstring injuries in field-based team sports., Method: Following database search, article retrieval and title and abstract screening, articles were assessed for eligibility against predefined criteria then assessed for methodological quality using the Critical Appraisal Tool for prevalence studies. Meta-analysis was used to pool data across studies, with meta-regression used where possible., Results: Sixty-three articles were included in the meta-analysis, encompassing 5952 injuries and 7 262 168 hours of exposure across six field-based team sports (soccer, rugby union, field hockey, Gaelic football, hurling and Australian football). Hamstring injury incidence was 0.81 per 1000 hours, representing 10% of all injuries. Prevalence for a 9-month period was 13%, increasing 1.13-fold for every additional month of observation (p=0.004). Hamstring injury incidence increased 6.4% for every 1 year of increased average cohort age, was 9.4-fold higher in match compared with training scenarios (p=0.003) and was 1.5-fold higher on grass compared with artificial turf surfaces (p<0.001). Hamstring injury incidence was not significantly moderated by average cohort mass (p=0.542) or stature (p=0.593), was not significantly different between sports (p=0.150) and has not significantly changed over the last 30 years (p=0.269)., Conclusion: Hamstring injury represents 10% of all injuries in field-based team sports, with 13% of the athletes experiencing a hamstring injury over a 9-month period most commonly during matches. More work is needed to reduce the incidence of hamstring injury in field-based team sports., Prospero Registration Number: CRD42020200022., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: To determine if eccentric knee flexor strength and biceps femoris long head (BFlh) fascicle length were associated with prospective hamstring strain injury (HSI) in professional Australian Football players, and if more frequent assessments of these variables altered the association with injury risk., Methods: Across two competitive seasons, 311 Australian Football players (455 player seasons) had their eccentric knee flexor strength during the Nordic hamstring exercise and BFlh architecture assessed at the start and end of preseason and in the middle of the competitive season. Player age and injury history were also collected in preseason. Prospective HSIs were recorded by team medical staff., Results: Seventy-four player seasons (16%) sustained an index HSI. Shorter BFlh fascicles (<10.42 cm) increased HSI risk when assessed at multiple time points only (relative risk [RR], 1.9; 95% confidence interval [CI], 1.2-3.0). Neither absolute (N) nor relative (N·kg-1) eccentric knee flexor strength was associated with HSI risk, regardless of measurement frequency (RR range, 1.0-1.1); however, between-limb imbalance (>9%), when measured at multiple time points, was (RR, 1.8; 95% CI, 1.1-3.1). Prior HSI had the strongest univariable association with prospective HSI (RR, 2.9; 95% CI, 1.9-4.3). Multivariable logistic regression models identified a combination of prior HSI, BFlh architectural variables and between-limb imbalance in eccentric knee flexor strength as optimal input variables; however, their predictive performance did not improve with increased measurement frequency (area under the curve, 0.681-0.726)., Conclusions: More frequent measures of eccentric knee flexor strength and BFlh architecture across a season did not improve the ability to identify which players would sustain an HSI., (Copyright © 2021 by the American College of Sports Medicine.)

Background: Hamstring strain injuries are the most common injuries in team sports. Biceps femoris long head architecture is associated with the risk of hamstring injury in soccer. To assess the overall predictive ability of architectural variables, risk factors need to be applied to and validated across different cohorts., Purpose: To assess the generalizability of previously established risk factors for a hamstring strain injury (HSI), including demographics, injury history, and biceps femoris long head (BFlh) architecture to predict HSIs in a cohort of elite Australian football players., Study Design: Cohort study; Level of evidence, 3., Methods: Demographic, injury history, and BFlh architectural data were collected from elite soccer (n = 152) and Australian football (n = 169) players at the beginning of the preseason for their respective competitions. Any prospectively occurring HSIs were reported to the research team. Optimal cut points for continuous variables used to determine an association with the HSI risk were established from previously published data in soccer and subsequently applied to the Australian football cohort to derive the relative risk (RR) for these variables. Logistic regression models were built using data from the soccer cohort and utilized to estimate the probability of an injury in the Australian football cohort. The area under the curve (AUC) and Brier score were the primary outcome measures to assess the performance of the logistic regression models., Results: A total of 27 and 30 prospective HSIs occurred in the soccer and Australian football cohorts, respectively. When using cut points derived from the soccer cohort and applying these to the Australian football cohort, only older athletes (aged ≥25.4 years; RR, 2.7 [95% CI, 1.4-5.2]) and those with a prior HSI (RR, 2.5 [95% CI, 1.3-4.8]) were at an increased risk of HSIs. Using the same approach, height, weight, fascicle length, muscle thickness, pennation angle, and relative fascicle length were not significantly associated with an increased risk of HSIs in Australian football players. The logistic regression model constructed using age and prior HSIs performed the best (AUC = 0.67; Brier score = 0.14), with the worst performing model being the one that was constructed using pennation angle (AUC = 0.53; Brier score = 0.18)., Conclusion: Applying cut points derived from previously published data in soccer to a dataset from Australian football identified older age and prior HSIs, but none of the modifiable HSI risk factors, to be associated with an injury. The transference of HSI risk factor data between soccer and Australian football appears limited and suggests that cohort-specific cut points must be established.

Objective: The primary aim was to compare time from acute hamstring strain injury (HSI) to return-to-play (RTP) clearance following a standardized rehabilitation protocol performed within either pain-free or pain-threshold limits. Secondary aims were to compare isometric knee flexor strength, biceps femoris long head (BFLH) fascicle length, fear of movement, and reinjury occurrence at the 6-month follow-up between pain-free and pain-threshold groups., Design: Randomized controlled trial., Methods: Forty-three men with acute HSIs were randomly allocated to a pain-free (n = 22) or pain-threshold (n = 21) rehabilitation group. Days from HSI to RTP clearance, isometric knee flexor strength, BFLH fascicle length, fear of movement, and reinjury occurrence at the 6-month follow-up were reported., Results: Median time from HSI to RTP clearance was 15 days (95% confidence interval [CI]: 13, 17) in the pain-free group and 17 days (95% CI: 11, 24) in the pain-threshold group, which was not significantly different ( P = .37). Isometric knee flexor strength recovery at 90° of hip and 90° of knee flexion was greater in the pain-threshold group at RTP clearance by 15% (95% CI: 1%, 28%) and by 15% (95% CI: 1%, 29%) at 2-month follow-up, respectively. Improvement in BFLH fascicle length from baseline was 0.91 cm (95% CI: 0.34, 1.48) greater at 2-month follow-up in the pain-threshold group. Two reinjuries occurred in both the pain-free and pain-threshold groups between RTP clearance and the 6-month follow-up., Conclusion: Pain-threshold rehabilitation did not accelerate RTP clearance, but resulted in greater recovery of isometric knee flexor strength and better maintenance of BFLH fascicle length, compared to pain-free rehabilitation. J Orthop Sports Phys Ther 2020;50(2):91-103. Epub 28 Jun 2019. doi:10.2519/jospt.2020.8895 .

Purpose: Three of the most commonly identified hamstring strain injury (HSI) risk factors are age, previous HSI, and low levels of eccentric hamstring strength. However, no study has investigated the ability of these risk factors to predict the incidence of HSI in elite Australian footballers. Accordingly, the purpose of this prospective cohort study was to investigate the predictive ability of HSI risk factors using machine learning techniques., Methods: Eccentric hamstring strength, demographic and injury history data were collected at the start of preseason for 186 and 176 elite Australian footballers in 2013 and 2015, respectively. Any prospectively occurring HSI were reported to the research team. Using various machine learning techniques, predictive models were built for 2013 and 2015 within-year HSI prediction and between-year HSI prediction (2013 to 2015). The calculated probabilities of HSI were compared with the injury outcomes and area under the curve (AUC) was determined and used to assess the predictive performance of each model., Results: The minimum, maximum, and median AUC values for the 2013 models were 0.26, 0.91, and 0.58, respectively. For the 2015 models, the minimum, maximum and median AUC values were, correspondingly, 0.24, 0.92, and 0.57. For the between-year predictive models the minimum, maximum, and median AUC values were 0.37, 0.73, and 0.52, respectively., Conclusions: Although some iterations of the models achieved near perfect prediction, the large ranges in AUC highlight the fragility of the data. The 2013 models performed slightly better than the 2015 models. The predictive performance of between-year HSI models was poor however. In conclusion, risk factor data cannot be used to identify athletes at an increased risk of HSI with any consistency.

Background: Rehabilitation progression and return-to-play (RTP) decision making following hamstring strain injury (HSI) can be challenging for clinicians, owing to the competing demands of reducing both convalescence and the risk of re-injury. Despite an increased focus on the RTP process following HSI, little attention has been paid to rehabilitation progression and RTP criteria, and subsequent time taken to RTP and re-injury rates., Objective: The aim of this systematic review is to identify rehabilitation progression and RTP criteria implemented following HSI and examine the subsequent time taken to RTP and rates of re-injury., Methods: A systematic literature review of databases MEDLINE, CINAHL, SPORTDiscus, Cochrane Library, Web of Science and EMBASE was conducted to identify studies of participants with acute HSI reporting time taken to RTP and rates of re-injury after a minimum 6-month follow-up. General guidelines and specific criteria for rehabilitation progression were identified for each study. In addition, RTP criteria were identified and categorised as performance tests, clinical assessments, isokinetic dynamometry or the Askling H-test., Results: Nine studies were included with a total of 601 acute HSI confirmed by clinical examination or magnetic resonance imaging within 10 days of initial injury. A feature across all nine studies was that the injured individual's perception of pain was used to guide rehabilitation progression, whilst clinical assessments and performance tests were the most frequently implemented RTP criteria. Mean RTP times were lowest in studies implementing isokinetic dynamometry as part of RTP decision making (12-25 days), whilst those implementing the Askling H-test had the lowest rates of re-injury (1.3-3.6%)., Conclusions: This systematic review highlights the strong emphasis placed on the alleviation of pain to allow HSI rehabilitation progression, and the reliance on subjective clinical assessments and performance tests as RTP criteria. These results suggest a need for more objective and clinically practical criteria, allowing a more evidence-based approach to rehabilitation progression, and potentially reducing the ambiguity involved in the RTP decision-making process.