Causal inference did not detect any effect of jump load on knee complaints in elite men's volleyball.

The aim was to determine how jump load affects knee complaints in elite men's volleyball. We collected data from four men's premier league volleyball teams through three seasons in a prospective cohort study (65 players, 102 player-seasons). Vert inertial measurement devices captured the jump load (jump frequency and jump height) from 21 088 daily player sessions, and knee complaints were reported in 3568 weekly OSTRC-O questionnaires. Mixed complementary log-log regression models described the probability of (i) experiencing symptoms if players were currently asymptomatic, (ii) worsening symptoms if players had symptoms, and (iii) recovery from knee complaints. Based on our causal assumptions, weekly jump load was modeled as the independent variable, adjusted for age (years), weight (kg), position on volleyball team, and past jump load. No certain evidence of an association was found between weekly jump load and probability of (i) knee complaints (p from 0.10 to 0.32 for three restricted cubic splines of load), (ii) worsening symptoms if the player already had symptoms (p from 0.11 to 0.97), (iii) recovery (p from 0.36 to 0.63). The probability of knee complaints was highest for above-average weekly jump load (~1.2% for an outside hitter with mean age and height) compared with low loads (~1%) and very high loads (→ ~ 0%). The association between jump load and knee complaints risk remains unclear. Small differences in risk across observed jump load levels were observed. It would likely require substantially increased sample sizes to detect this association with certainty.

Lower HAGOS subscale scores associated with a longer duration of groin problems in football players in the subsequent season.

Introduction: Groin injuries represent a considerable problem in football. Although the Adductor Strengthening Programme reduced groin injury risk, players can still experience groin symptoms throughout the season. This study aimed to determine whether preseason Copenhagen Hip and Groin Outcome Score (HAGOS) and a history of previous injury can identify individuals at risk of having a longer duration of groin problems the subsequent season, using an 'any physical complaint' definition of injury. Methods: Preseason HAGOS score and weekly groin problems were registered with the Oslo Sports Trauma Research Center Overuse questionnaire during one full season in 632 male semiprofessional adult players. Results: The prognostic model showed a decreased number of weeks with groin problems for each increase in HAGOS score for 'groin-related quality of life' (QOL) (IRR=0.99, p=0.003). A 10-point higher 'QOL' score predicted 10% fewer weeks of groin problems. Additionally, previous hip/groin injury was associated with a 74% increase in the number of weeks with symptoms (p<0.001). Conclusion: The HAGOS questionnaire applied preseason can detect players at risk of getting more weeks with groin problems the following season. The 'QOL' subscale seems to be the superior subscale for estimating subsequent groin problem duration. While HAGOS appears promising in identifying players at risk, previous groin injury is the most robust indicator, showing a substantial 74% increase in weeks with symptoms.

A new statistical approach to training load and injury risk: separating the acute from the chronic load.

The relationship between recent (acute) training load relative to long-term (chronic) training load may be associated with sports injury risk. We explored the potential for modelling acute and chronic loads separately to address current statistical methodology limitations. We also determined whether there was any evidence of an interaction in the association between acute and chronic training loads and injury risk in football. A men's Qatar Stars League football cohort (1 465 players, 1 977 injuries), where training load was defined as the number of minutes of activity, and a Norwegian elite U-19 football cohort (81 players, 60 injuries), where training load was defined as the session rating of perceived exertion (sRPE). Mixed logistic regression was run with training load on the current day (acute load) and cumulative past training load estimated by distributed lag non-linear models (chronic load) as independent variables. Injury was the outcome. An interaction between acute and chronic training load was modelled. In both football populations, we observed that the risk of injury on the current day for different values of acute training load was highest for players with low chronic load, followed by high and then medium chronic load. The slopes varied substantially between different levels of chronic training load, indicating an interaction. Modelling acute and chronic loads separately in regression models is a suitable statistical approach for analysing the association between relative training load and injury risk in injury prevention research. Sports scientists should also consider the potential for interactions between acute and chronic load.

Impact of COVID-19 lockdown on injury risk in Qatar's professional football.

OBJECTIVES: To compare injury incidence, burden and characteristics between the pre- and post-COVID-19 lockdown periods in Qatari professional football. DESIGN: Prospective cohort study. METHODS: Injury and exposure data for two post-COVID-19 lockdown periods [early post-lockdown period: short-term ~2 months (54 matches) and late post-lockdown period: long-term 8-months (183 matches)] were compared to the benchmark of the same periods from the three previous seasons (2017/18-2019/20). RESULTS: We observed no difference in overall, training or match incidence between early post-lockdown period and the benchmark reference. However, this short-term period resulted in lower burden for overall- (RR 0.80, P < 0.0001), training- (RR 0.73, P < 0.0001) and match-injuries (RR 0.40, P < 0.0001) compared to the benchmark. During late post-lockdown period match injury incidence (RR 0.72, P = 0.0010) and match injury burden (RR 0.69, P < 0.001) were lower than the benchmark. In contrast, both overall- (RR 1.30, P < 0.001) and training-injury burden (RR 1.65, P < 0.001) were higher. A significant increase in adductor strains in both post-lockdown periods was observed. CONCLUSIONS: Immediately after the COVID-19 lockdown (short-term effect), there was no difference in injury incidence but a lower injury burden compared to benchmark. Moreover, the rapid return to competition for the successive season (long-term effect) was associated with a higher overall- and training-injury burden, but a lower match-injury burden compared to the benchmark.

Assessing the cumulative effect of long-term training load on the risk of injury in team sports.

Objectives: Determine how to assess the cumulative effect of training load on the risk of injury or health problems in team sports. Methods: First, we performed a simulation based on a Norwegian Premier League male football dataset (n players=36). Training load was sampled from daily session rating of perceived exertion (sRPE). Different scenarios of the effect of sRPE on injury risk and the effect of relative sRPE on injury risk were simulated. These scenarios assumed that the probability of injury was the result of training load exposures over the previous 4 weeks. We compared seven different methods of modelling training load in their ability to model the simulated relationship. We then used the most accurate method, the distributed lag non-linear model (DLNM), to analyse data from Norwegian youth elite handball players (no. of players=205, no. of health problems=471) to illustrate how assessing the cumulative effect of training load can be done in practice. Results: DLNM was the only method that accurately modelled the simulated relationships between training load and injury risk. In the handball example, DLNM could show the cumulative effect of training load and how much training load affected health problem risk depending on the distance in time since the training load exposure. Conclusion: DLNM can be used to assess the cumulative effect of training load on injury risk.

Incidence and risk factors of intraoperative periprosthetic femoral fractures during primary total hip arthroplasty: 218,423 cases reported to the Norwegian Arthroplasty Register between 1987 and 2020.

BACKGROUND AND PURPOSE: Intraoperative periprosthetic femoral fractures (IPFFs) can occur during primary total hip arthroplasty (THA). We describe the incidence of IPFFs during THA in Norway and estimate potential risk factors that could be associated with IPFF Patients and methods - Data from the Norwegian Arthoplasty Register (1987-2020) was used: 2,268 IPFFs from 218,423 primary THAs in 172,598 patients. The following factors were analyzed: sex, age, diagnosis, previous operation on the same hip, surgical approach, and stem fixation technique. Association of these factors with IPFF risk was assessed using multivariable Poisson regression. RESULTS: IPFF occurred during 2,268 operations with an incidence of 1.0% among all primary THAs. The risk of IPFF was associated with female sex (relative risk 1.8; 99% CI 1.5-2.1), age 80-90 years and age over 90 years (compared with age 60-70 years: 1.3; CI 1.0-1.6 and 2.6; CI 1.6-4.3, respectively), non-osteoarthritis diagnoses (2.2; CI 1.9-2.6), previous surgery to the same hip (1.8; CI 1.5-2.2), lateral approach (compared with the posterior approach: 1.5; CI 1.1-2.0), and cementless stem fixation (2.7; CI 2.0-3.6). INTERPRETATION: Surgeons should be aware of the factors associated with an increased risk of IPFF: female sex, age above 80 years, non-osteoarthritis diagnoses, and previous surgery to the same hip. Cemented stem fixation and posterior approach should be favored in high-risk patients, such as elderly women.

Not straightforward: modelling non-linearity in training load and injury research.

OBJECTIVES: To determine whether the relationship between training load and injury risk is non-linear and investigate ways of handling non-linearity. METHODS: We analysed daily training load and injury data from three cohorts: Norwegian elite U-19 football (n=81, 55% male, mean age 17 years (SD 1)), Norwegian Premier League football (n=36, 100% male, mean age 26 years (SD 4)) and elite youth handball (n=205, 36% male, mean age 17 years (SD 1)). The relationship between session rating of perceived exertion (sRPE) and probability of injury was estimated with restricted cubic splines in mixed-effects logistic regression models. Simulations were carried out to compare the ability of seven methods to model non-linear relationships, using visualisations, root-mean-squared error and coverage of prediction intervals as performance metrics. RESULTS: No relationships were identified in the football cohorts; however, a J-shaped relationship was found between sRPE and the probability of injury on the same day for elite youth handball players (p<0.001). In the simulations, the only methods capable of non-linear modelling relationships were the quadratic model, fractional polynomials and restricted cubic splines. CONCLUSION: The relationship between training load and injury risk should be assumed to be non-linear. Future research should apply appropriate methods to account for non-linearity, such as fractional polynomials or restricted cubic splines. We propose a guide for which method(s) to use in a range of different situations.