Search

To investigate: (1) the injury epidemiology in an Australian academy; (2) how athletes transition through the high‐performance sport (HPS) pathway; and (3) why athletes leave this HPS program. This retrospective cohort study was conducted at an Australian HPS academy over a 4‐year period. Medical attention injuries were prospectively recorded. Injury incidence rates (IIR) and burden were calculated per 365 athlete‐days, according to sport, sex, and pathway level. Athlete pathway levels were mapped to the Foundations, Talent, Elite, and Mastery (FTEM) framework. Reasons for athletes transitioning out were reported. Four hundred and eighty‐one injuries were reported across 124 athletes at an IIR of 2.09 injuries per 365 athlete‐days (95% CI = 1.91–2.29). Most athletes (103, 83.1%) were injured at least once over the 4‐year period. IIRs increased (IRR = 1.17, 95% CI = 1.06–1.29, p = 0.001) as athletes progressed through the pathway. The most common reason for athlete attrition was deselection due to performance (n = 18), with 55.6% of these athletes sustaining an injury in the season prior to deselection. Injury burden was highest at E2 (119.5 days absence per 365 athlete‐days (95% CI = 62.18–229.67)) and lowest at T4 (30.47 days absence per 365 athlete‐days (95% CI = 21.98–42.24)). Injury occurrence is common across HPS, with IIRs increasing as athletes progressed to higher talent levels. Deselection due to poor performance was the main attrition factor, with more than half the deselected athletes impacted by injury prior to deselection. This study highlights an increased risk of deselection, following injury, and indicates the need for further development of prevention strategies targeting pathway athletes. [ABSTRACT FROM AUTHOR]

Purpose: Psychological stress is reported to be an important contributor to reduced sleep quality and quantity observed in elite athletes. The purpose of this study was to explore the association between psychological stress and sleep and to identify if specific aspects of sleep are disturbed. Methods: One hundred thirty-one elite athletes (mean [SD], male: n = 46, age 25.8 [4.1] y; female: n = 85, age 24.3 [3.9] y) from a range of sports completed a series of questionnaires in a 1-month period approximately 4 months before the 2016 Rio Olympic Games. Questionnaires included the Pittsburgh Sleep Quality Index; Recovery-Stress Questionnaire; Depression, Anxiety, and Stress Scale (DASS 21); and Perceived Stress Scale (PSS). Results: Regression analysis identified the PSS and DASS stress as the main variables associated with sleep. A PSS score of 6.5 or higher was associated with poor sleep. In addition, a PSS score lower than 6.5 combined with a DASS stress score higher than 4.5 was also associated with poor sleep. Univariate analyses on subcomponents of the Pittsburgh Sleep Quality Index confirmed that PSS is associated with lower sleep quality (t99 = 2.40, P =.018), increased sleep disturbances (t99 = 3.37, P =.001), and increased daytime dysfunction (t99 = 2.93, P =.004). DASS stress was associated with increased sleep latency (t94 = 2.73, P =.008), increased sleep disturbances (t94 = 2.25, P =.027), and increased daytime dysfunction (t94 = 3.58, P =.001). Conclusions: A higher stress state and higher perceived stress were associated with poorer sleep, in particular increased sleep disturbances and increased daytime dysfunction. Data suggest that relatively low levels of psychological stress are associated with poor sleep in elite athletes. [ABSTRACT FROM AUTHOR]

This study aimed to establish injury incidence rates (IIRs) and burden within an Australian male professional football club (n = 73) and to investigate longitudinal trends across five consecutive seasons (2016/17–2020/21). There was an overall IIR of 9.18 injuries per 1000 hours (h) (95% CI [7.89, 10.47]). The IIR was approximately seven times greater (rate ratio (RR): 6.85; 95% CI [5.13, 9.19]; p < 0.01) in matches (31.29 injuries per 1000 h; 95% CI [25.25, 37.33]) compared to training (4.49 injuries per 1000 h; 95% CI [3.51, 5.47]). The overall injury burden was 254.1 days lost per 1000 h (95% CI [220.9, 292.3]). Compared with the reference 2016/17 season, there were significant increases in minimal (RR: 6.94; 95% CI [1.27, 128.73]) and mild injuries (RR: 3.76; 95% CI [1.21, 16.39]) in season 2017/18 and decreases in moderate (RR: 0.40; 95% CI [0.19, 0.80]) and contact injuries (RR: 0.35; 95% CI [0.12, 0.90]) in season 2019/2020. Time-loss injury is common and represents a major burden in Australian male professional football, with injuries more frequently sustained during matches. Injury prevention practices should specifically be directed towards muscle/tendon and ligament injuries of the lower limb, particularly anterior cruciate ligament, ankle sprain and hamstring strain injuries. [ABSTRACT FROM AUTHOR]

The Low Energy Availability in Females Questionnaire (LEAF-Q) was validated to identify risk of the female athlete triad (triad) in female endurance athletes. This study explored the ability of the LEAF-Q to detect conditions related to low energy availability (LEA) in a mixed sport cohort of female athletes. Data included the LEAF-Q, SCOFF Questionnaire for disordered eating, dual-energy X-ray absorptiometry-derived body composition and bone mineral density, Mini International Neuropsychiatric Interview, blood pressure, and blood metabolic and reproductive hormones. Participants were grouped according to LEAF-Q score (≥8 or <8), and a comparison of means was undertaken. Sensitivity, specificity, and predictive values of the overall score and subscale scores were calculated in relation to the triad and biomarkers relevant to LEA. Fisher's exact test explored differences in prevalence of these conditions between groups. Seventy-five athletes (18–32 years) participated. Mean LEAF-Q score was 8.0 ± 4.2 (55% scored ≥8). Injury and menstrual function subscale scores identified low bone mineral density (100% sensitivity, 95% confidence interval [15.8%, 100%]) and menstrual dysfunction (80.0% sensitivity, 95% confidence interval [28.4%, 99.5%]), respectively. The gastrointestinal subscale did not detect surrogate markers of LEA. LEAF-Q score cannot be used to classify athletes as "high risk" of conditions related to LEA, nor can it be used as a surrogate diagnostic tool for LEA given the low specificity identified. Our study supports its use as a screening tool to rule out risk of LEA-related conditions or to create selective low-risk groups that do not need management as there were generally high negative predictive values (range 76.5–100%) for conditions related to LEA. [ABSTRACT FROM AUTHOR]

Enabling athletes to achieve peak performances while also maintaining high levels of health is contextually complex. We aim to describe what a 'health system' is and apply the essential functions of stewardship, financing, provision of services and resource generation to an Australian high-performance sport context. We introduce a fifth function that health systems should not detract from athletes' ability to achieve their sports goals. We describe how these functions aim to achieve four overall outcomes of safeguarding the health of the athletes, responding to expectations, providing financial and social protection against the costs of ill health, and efficient use of resources. Lastly, we conclude with key challenges and potential solutions for developing an integrated health system within the overall performance system in high-performance sport. [ABSTRACT FROM AUTHOR]

Background: Value-based healthcare provider reimbursement models have been proposed as an alternative to traditional fee-for-service arrangements that can align financial reimbursement more closely to the outcomes of value to patients and society. This study aimed to investigate stakeholder perceptions and experiences of different reimbursement systems for healthcare providers in high-performance sport, with a focus on fee-for-service versus salaried provider models. Methods: Three in-depth semi-structured focus group discussions and one individual interview were conducted with key stakeholders across the Australian high-performance sport system. Participants included healthcare providers, health managers, sports managers and executive personnel. An interview guide was developed using the Exploration, Preparation, Implementation, Sustainment framework, with key themes deductively mapped to the innovation, inner context and outer context domains. A total of 16 stakeholders participated in a focus group discussion or interview. Results: Participants identified several key advantages of salaried provider models over fee-for-service arrangements, including: the potential for more proactive and preventive models of care; enhanced inter-disciplinary collaboration; and the ability for providers to have a deeper understanding of context and how their role aligns with a broader set of priorities for an athlete and the organisation. Noted challenges of salaried provider models included the potential for providers to revert to reactive care delivery when not afforded adequate capacity to provide services, and difficulties for providers in demonstrating and quantifying the value of their work. Conclusions: Our findings suggest that high-performance sporting organisations seeking to improve primary prevention and multidisciplinary care should consider salaried provider arrangements. Further research to confirm these findings using prospective, experimental study designs remains a priority. [ABSTRACT FROM AUTHOR]

Objectives: To assess the effect of multiple high-risk-scenario (HRS) exposures on noncontact injury prediction in elite Australian footballers. Design: Retrospective cohort study. Methods: Sessional workload data (session rating of perceived exertion, global positioning system–derived distance, sprint distance, and maximum velocity) from 1 club (N = 60 players) over 3 seasons were collated; several established HRSs were also defined. Accumulated HRS sessional exposures were calculated retrospectively (previous 1–8 wk). Noncontact injury data were documented. Univariate and multivariate Poisson regression models determined injury incidence rate ratios (IRRs) while accounting for moderating effects (preseason workload volume and playing experience). Model performance was evaluated using receiver operating characteristics (area under curve). Results: Very low (0–8 sessions: IRR = 5.76; 95% confidence interval [CI], 1.69–19.66) and very high (>15 sessions: IRR = 4.70; 95% CI, 1.49–14.87) exposures to >85% of an individual's maximal velocity over the previous 8 wk were associated with greater injury risk compared with moderate exposures (11–12 sessions) and displayed the best model performance (area under curve = 0.64). A single session corresponding to a very low chronic load condition over the previous week for all workload variables was associated with increased injury risk, with sprint distance (IRR = 3.25; 95% CI, 1.95–5.40) providing the most accurate prediction model (area under curve = 0.63). Conclusions: Minimal exposure to high-velocity efforts (maximum speed exposure and sprint volume) was associated with the greatest injury risk. Being underloaded may be a mediator for noncontact injury in elite Australian football. Preseason workload and playing experience were not moderators of this effect. [ABSTRACT FROM AUTHOR]

In applied program settings, such as in natural environment control and education, performance evaluation is usually conducted by evaluators considering both self-comparison and comparison with peers. We have developed the performance outcome scoring template (POS-T) for assessments with high face-validity in these settings. POS-T puts achievements of individuals or groups in context, i.e. the resulting performance outcome score (POS) reflects a meaningful measure of performance magnitude with regards to internal and external comparisons. Development of a POS is performed in four steps supported by a statistical framework. Software is supplied for creation of scoring applications in different performance evaluation settings. We demonstrate the POS-T by evaluation of CO2 emissions reduction amongst 36 OECD member countries. [ABSTRACT FROM AUTHOR]

Background: The aims of this retrospective study were to (i) provide a description of sleep quality in elite athletes as measured by the Pittsburgh Sleep Quality Index (PSQI), (ii) provide normative PSQI data, (iii) identify differences across sex and sport, (iv) identify components that contribute to high PSQI scores and (v) assess PSQI test–retest reliability. Methods: The PSQI was completed by 479 athletes (371 female and 108 male) across 20 Olympic team and individual sports. For ordinal and categorical variables, the Wilcoxon rank sum test and Chi Squared tests were used, respectively. A random forest regression was built to determine the importance of each PSQI component. Test–retest reliability was assessed using two-way mixed effects intraclass correlation coefficients. Results: Fifty-two percent of athletes had a global PSQI score ≥ 5. Team sport athletes reported significantly longer sleep onset latency times but longer sleep durations compared with individual sport athletes. Sleep onset latency and sleep quality made the greatest contribution to the global PSQI scores. The PSQI demonstrated variability over periods of 2 months or more, with a minimal detectable change of 3 arbitrary units (AU). Conclusion: Long sleep onset latency and poor perceived sleep quality made the greatest contribution to the high PSQI scores observed in approximately half of elite athletes investigated. The PSQI should be administered at regular intervals due to variability within individuals over periods of 2 months or more. Individual questionnaire items or component scores of the PSQI may be useful for practitioners in guiding decision-making regarding sleep interventions in athletes. [ABSTRACT FROM AUTHOR]

Sport science and medicine practitioners are interested in the relationships between training load, injury, and illness. The extent to which training preparedness is associated with workload‐related injury and illness risk is debated. Therefore, this study applied multi‐level mixed effect logistic regression to investigate time‐dependent (±7‐ and ±28‐day) relationships between training preparedness (fatigue, mood, motivation, soreness, stress, sleep duration, and quality), training load, injury, and illness in 536 elite and pre‐elite female netball athletes. Absolute risk (AR ± 95% CI) of sustaining an injury (0.98 ± 0.06%, n = 1122 injuries, N = 254 athletes) or illness (1.09 ± 0.10%, n = 2881, N = 432 athletes) was calculated. All training preparedness variables combined resulted in an absolute risk of 0.88%‐5.88% and 0.87%‐20% for injury and illness, respectively. Injury and illness had significant (P <.05) bidirectional (ie, both increased and decreased) associations with physical (soreness) and physiological (sleep duration and quality), while illness also had negative (mood, motivation) and positive (stress) associations with psychological training preparedness variables. Low sleep duration in the 48‐h period prior was associated (P =.005) with increased injury risk (OR = 0.91 ± 0.03; AR = 4.00%), while "very poor" sleep quality (OR = 0.59 ± 0.02; AR = 7.83%) or extremes of too little (<5 hours, OR = 1.01 ± 0.03; AR = 3.13%‐14.29%) and too much (>10 hours, OR = 1.01 ± 0.03; AR = 2.61%‐10.98%) sleep had bidirectional associations (P <.001) with an increased illness risk. Changes in training preparedness variables demonstrated bidirectional associations with injury and illness. These outcomes suggest that sport science and medicine practitioners should monitor sleep, physical, and psychological recovery status, to aid early detection and intervention regarding injury and illness symptomology. [ABSTRACT FROM AUTHOR]

An emerging method to measure muscle activation patterns is muscle functional magnetic resonance imaging (mfMRI), where preexercise and postexercise muscle metabolism differences indicate spatial muscle activation patterns. We evaluated studies employing mfMRI to determine activation patterns of lumbar or lower limb muscles following exercise in physically active adults. Electronic systematic searches were conducted until March 2020. All studies employing ≥1.5 Tesla MRI scanners to compare spatial muscle activation patterns at the level of or inferior to the first lumbar vertebra in healthy, active adults. Two authors independently assessed study eligibility before appraising methodological quality using a National Institutes of Health assessment tool. Because of heterogeneity, findings were synthesized without meta-analysis. Of the 1,946 studies identified, seven qualified for inclusion and pertained to hamstring (n = 5), quadriceps (n = 1) or extrinsic foot (n = 1) muscles. All included studies controlled for internal validity, with one employing assessor blinding. MRI physics and differing research questions explain study methodology heterogeneity. Significant mfMRI findings were: following Nordic exercise, hamstrings with previous trauma (strain or surgical autograft harvest) demonstrated reduced activation compared with unharmed contralateral muscles, and asymptomatic individuals preferentially activated semitendinosus; greater biceps femoris long head to semitendinosus ratios reported following 45° hip extension over Nordic exercise; greater rectus femoris activation occurred in “flywheel” over barbell squats. mfMRI parameters differ on the basis of individual research questions. Individual muscles show greater activation following specific exercises, suggesting exercise specificity may be important for rehabilitation, although evidence is limited to single cohort studies comparing interlimb differences preexercise versus postexercise. [ABSTRACT FROM AUTHOR]

Patellar tendinopathy (PT) is a leading cause of morbidity in jump‐landing athletes. Landing mechanics are identified as a factor associated with PT and/or patellar tendon abnormality. This study aimed to identify key jump‐landing variables associated with PT. Thirty‐six junior elite basketball players (men n = 18, women n = 18) were recruited from a Basketball Australia development camp. Three‐dimensional (3D) kinematic and ground reaction force (GRF) data during a stop‐jump task were collected as well as ultrasound scans of the patellar tendons and recall history of training load data. Mixed‐model factorial analyses of variance were used to determine any significant between‐group differences. Of the 23 participants included for statistical analyses, 11 had normal bilateral patellar tendons (controls) and eight reported PT (currently symptomatic); however, the four participants categorized as asymptomatic with patellar tendon abnormality on diagnostic imaging were excluded from statistical analyses due to their small sample size. Athletes with PT displayed a similar knee flexion angle at initial foot‐ground contact (IC) and hip extension strategy during a stop‐jump horizontal landing. Despite a similar kinematic technique, athletes with PT utilized a strategy of a longer stance duration phase from IC to peak force. This strategy did not lead to those athletes with PT decreasing their peak vertical GRF nor patellar tendon force during landing but enabled these athletes to land with a lower rate of loading (control 59.2 ± 39.3 vs. PT 29.4 ± 33.7 BW.s‐1). Athletes with PT still reported significantly reduced training volume (control 4.9 ± 1.8 vs PT 1.8 ± 1.1 sessions/wk; total training time/wk control 2.4 ± 1.0 vs PT 1.4 ± 1.1 h/wk). [ABSTRACT FROM AUTHOR]

Background: The risk of sustaining a subsequent injury is elevated in the weeks after return to play (RTP) from an index injury. However, little is known about the magnitude, duration, and nature by which subsequent injury risk is increased. Purpose: To quantify and describe the risk of injury in a 12-week period after RTP from an index injury in Australian football players. Study Design: Cohort study; Level of evidence, 2. Methods: Injury data were collected from 79 players over 5 years at 1 Australian Football League club. Injuries were classified with the Orchard Sports Injury Classification System and by side of the body. Furthermore, injury severity was classified as time loss (resulting in ≥1 matches being missed) or non–time loss (no matches missed). Subsequent injury was categorized with the SIC-2.0 model and applied to the data set via an automated script. The probability of a time loss subsequent injury was calculated for in-season index injuries for each week of a 12-week period after RTP via a mixed effect logistic regression model. Results: Subsequent injury risk was found to be highest in the week of RTP for both time loss injuries (9.4%) and non–time loss injuries (6.9%). Risk decreased with each week survived after RTP; however, it did not return to baseline risk of participation (3.6%). Conclusion: These findings demonstrate that athletes returning to play are at an increased risk of injury for a number of weeks, thus indicating the requirement for tertiary prevention strategies to ensure that they survive this period. [ABSTRACT FROM AUTHOR]

Background: Injuries are common in rugby sevens, but studies to date have been limited to short, noncontinuous periods and reporting of match injuries only. Purpose: To report the injury incidence rate (IIR), severity, and burden of injuries sustained by men and women in the Australian rugby sevens program and to provide the first longitudinal investigation of subsequent injury occurrence in rugby sevens looking beyond tournament injuries only. Study Design: Descriptive epidemiology study. Methods: Ninety international rugby sevens players (55 men and 35 women) were prospectively followed over 2 consecutive seasons (2015-2016 and 2016-2017). All medical attention injuries were reported irrespective of time loss. Individual exposure in terms of minutes, distance, and high-speed distance was captured for each player for matches and on-field training, with the use of global positioning system devices. The IIR and injury burden (IIR × days lost to injury) were calculated per 1000 player-hours, and descriptive analyses were performed. Results: Seventy-three players (81.1%) sustained 365 injuries at an IIR of 43.2 per 1000 player-hours (95% CI, 43.0-43.3). As compared with male players, female players experienced a lower IIR (incidence rate ratio, 0.91; 95% CI, 0.90-0.91). Female players also sustained a higher proportion of injuries to the trunk region (relative risk, 1.75; 95% CI, 1.28-2.40) but a lower number to the head/neck region (relative risk, 0.58; 95% CI, 0.37-0.93; P =.011). The majority (80.7%) of subsequent injuries were of a different site and nature than previous injuries. A trend toward a reduced number of days, participation time, distance, and high-speed distance completed before the next injury was observed after successive injury occurrence. Conclusion: Female players have a lower IIR than male players, with variation of injury profiles observed between sexes. With a surveillance period of 2 years, subsequent injuries account for the majority of injuries sustained in rugby sevens, and they are typically different from previous types of sustained injuries. After each successive injury, the risk profile for future injury occurrence appears to be altered, which warrants further investigation to inform injury prevention strategies in rugby sevens. [ABSTRACT FROM AUTHOR]

Background: Accounting for subsequent injuries is critical for sports injury epidemiology. The subsequent injury categorisation (SIC-1.0) model was developed to create a framework for accurate categorisation of subsequent injuries but its operationalisation has been challenging.Objectives: The objective of this study was to update the subsequent injury categorisation (SIC-1.0 to SIC-2.0) model to improve its utility and application to sports injury datasets, and to test its applicability to a sports injury dataset.Methods: The SIC-1.0 model was expanded to include two levels of categorisation describing how previous injuries relate to subsequent events. A data-driven classification level was established containing eight discrete injury categories identifiable without clinical input. A sequential classification level that sub-categorised the data-driven categories according to their level of clinical relatedness has 16 distinct subsequent injury types. Manual and automated SIC-2.0 model categorisation were applied to a prospective injury dataset collected for elite rugby sevens players over a 2-year period. Absolute agreement between the two coding methods was assessed.Results: An automated script for automatic data-driven categorisation and a flowchart for manual coding were developed for the SIC-2.0 model. The SIC-2.0 model was applied to 246 injuries sustained by 55 players (median four injuries, range 1-12), 46 (83.6%) of whom experienced more than one injury. The majority of subsequent injuries (78.7%) were sustained to a different site and were of a different nature. Absolute agreement between the manual coding and automated statistical script category allocation was 100%.Conclusions: The updated SIC-2.0 model provides a simple flowchart and automated electronic script to allow both an accurate and efficient method of categorising subsequent injury data in sport. [ABSTRACT FROM AUTHOR]

Background: Combat sports involve body contact through striking, kicking and/or throwing. They are anecdotally referred to as 'dangerous', yet long-term investigation into specific injury rates is yet to be explored.Objective: To describe incidence and prevalence of injury and illness within Olympic combat sports and to investigate risk of bias of prospective injury and illness research within these sports.Methods: We systematically searched literature published up until May 2016. We included prospective studies of injury/illness in elite combat athletes lasting more than 12 weeks. Risk of bias was assessed using a modified version of the Downs and Black checklist for methodological quality. Included studies were mapped to the Oxford Centre for Evidence-Based Medicine levels of evidence.Results: Nine studies were included, and most (n=6) had moderate risk of bias. Studies provided level 1/2b evidence that the most frequently injured areas were the head/face (45.8%), wrist (12.0%) and lower back (7.8%) in boxing; the lower back (10.9%), shoulder (10.2%) and knee (9.7%) in judo; the fingers (22.8%) and thigh (9.1%) in taekwondo; and the knee (24.8%), shoulder (17.8%) and head/face (16.6%) in wrestling. Heterogeneity of injury severity classifications and inconsistencies inexposure measures prevented any direct comparisons of injury severity/incidence across combat sports.Conclusions: There is currently a lack of consensus in the collection of injury/illness data, limiting the development of prevention programmes for combat sport as a whole. However, sport-specific data that identify body areas with high injury frequency can provide direction to clinicians, enabling them to focus their attention on developing pathologies in these areas. In doing so, clinicians can enhance the practical elements of their role within the integrated combat sport performance team and assist in the regular update of surveillance records. [ABSTRACT FROM AUTHOR]

Background: Previous injury is a strong risk factor for recurrent lower limb injury in athletic populations, yet the association between previous injury and a subsequent injury different in nature or location is rarely considered.Objective: To systematically review data on the risk of sustaining a subsequent lower limb injury different in nature or location following a previous injury.Methods: Eight medical databases were searched. Studies were eligible if they reported lower limb injury occurrence following any injury of a different anatomical site and/or of a different nature, assessed injury risk, contained athletic human participants and were written in English. Two reviewers independently applied the eligibility criteria and performed the risk of bias assessment. Meta-analysis was conducted using a random effects model.Results: Twelve studies satisfied the eligibility criteria. Previous history of an ACL injury was associated with an increased risk of subsequent hamstring injury (three studies, RR=2.25, 95% CI 1.34 to 3.76), but a history of chronic groin injury was not associated with subsequent hamstring injury (three studies, RR=1.14, 95% CI 0.29 to 4.51). Previous lower limb muscular injury was associated with an increased risk of sustaining a lower limb muscular injury at a different site. A history of concussion and a variety of joint injuries were associated with an increased subsequent lower limb injury risk.Conclusions: The fact that previous injury of any type may increase the risk for a range of lower limb subsequent injuries must be considered in the development of future tertiary prevention programmes.Systematic Review Registration Number: CRD42016039904 (PROSPERO). [ABSTRACT FROM AUTHOR]

Background: Cost-benefit analyses have been proposed for determining acceptable risk of injury regarding training and competition participation. Currently, there is no best evidence synthesis of the literature evaluating the relationship between injury/illness and chance of success or failure.Objective: To evaluate the relationship between injury and/or illness and success and/or failure in athletic populations (individual and team sports).Methods: This review was prospectively registered (PROSPERO CRD42016036729) and a systematic electronic search was conducted in May 2016. Inclusion criterion was any study design describing the association between injury and/or illness and success or failure in athletic performance. Two independent authors screened search results, performed data extraction and assessed methodological quality and strength of evidence using a modified Downs and Black appraisal tool and a modified van Tulder method, respectively.Results: Of 10 546 titles identified, 14 satisfied the inclusion criteria and 7 had low risk of bias. Outcome measures associated with success and/or failure included: (1) availability of team members, (2) injury incidence, (3) injury burden, (4) squad utilisation and (5, 6) precompetition and in-competition injury. There was strong evidence that (1) increased availability of team members/athletes decreased the risk of failure and (2) precompetition and in-competition injuries were associated with increased risk of failure.Conclusions: Injuries have a detrimental impact on team and individual athletic success. Increased player availability improves chances of success. Conversely, injuries sustained both prior to and during competition may increase risk of failure. Injury prevention should therefore be a priority for maximising athletic performance. [ABSTRACT FROM AUTHOR]

Training loads contribute to sports injury risk but their mitigation has rarely been considered in a sports injury prevention framework. A key concept behind monitoring training loads for injury prevention is to screen for those at increased risk of injury so that workloads can be adjusted to minimise these risks. This review describes how advances in management of workload can be applied as a preventive measure. Primary prevention involves screening for preparticipation load risk factors, such as low training loads, prior to a training period or competition. Secondary prevention involves screening for workloads that are known to precede an injury developing so that modification can be undertaken to mitigate this risk. Tertiary prevention involves rehabilitation practices that include a graded return to training programme to reduce the risk of sustaining a subsequent injury. The association of training loads with injury incidence is now established. Prevention measures such as rule changes that affect the workload of an athlete are universal whereas those that address risk factors of an asymptomatic subgroup are more selective. Prevention measures, when implemented for asymptomatic individuals exhibiting possible injury risk factors, are indicated for an athlete at risk of developing a sports injury. Seven key indicated risks and associated prevention measures are proposed. [ABSTRACT FROM AUTHOR]

Background: The original subsequent injury categorisation (SIC-1.0) model aimed to classify relationships between chronological injury sequences to provide insight into the complexity and causation of subsequent injury occurrence. An updated model has recently been published. Comparison of the data coded according to the original and revised subsequent injury categorisation (SIC-1.0 and SIC-2.0) models has yet been formally compared.Methods: Medical attention injury data was prospectively collected for 42 elite water polo players over an 8 month surveillance period. The SIC-1.0 and SIC-2.0 models were retrospectively applied to the injury data. The injury categorisation from the two models was compared using descriptive statistics.Results: Seventy-four injuries were sustained by the 42 players (median = 2, range = 0-5), of which 32 injuries (43.2%) occurred subsequent to a previous injury. The majority of subsequent injuries were coded as occurring at a different site and being of a different nature, while also being considered clinically unrelated to the previous injury (SIC-1.0 category 10 = 57.9%; SIC-2.0 clinical category 16 = 54.4%). Application of the SIC-2.0 model resulted in a greater distribution of category allocation compared to the SIC-1.0 model that reflects a greater precision in the SIC-2.0 model.Conclusions: Subsequent injury categorisation of sport injury data can be undertaken using either the original (SIC-1.0) or the revised (SIC-2.0) model to obtain similar results. However, the SIC-2.0 model offers the ability to identify a larger number of mutually exclusive categories, while not relying on clinical adjudication for category allocation. The increased precision of SIC-2.0 is advantageous for clinical application and consideration of injury relationships. [ABSTRACT FROM AUTHOR]

Purpose: This review set out to summarise, define, and provide future direction towards the use of performance outcome measures as endpoints in research performed at international benchmark events in athletics. Methods: Scoping review methodology was applied through a search of the PubMed and Sports Discus databases and a systematic article selection procedure. Articles that met the inclusion criteria underwent triage for further quantitative and qualitative analysis. A concept chart was generated to describe the methods by which performance had been measured and introduce descriptive labels for theoretical and practical application. Results: None of 2972 articles primarily identified from the database search met the triage standards for quantitative data extraction. Eleven articles were included in a qualitative analysis. The analysis identified the common methods by which performance has been measured, reported and analysed. The resulting concept chart collates labels from the qualitative analysis (categories, themes, and constructs) with sports practice labels (performance metrics, framework, and analysis). Conclusions: The state of knowledge concerning methods to employ performance metrics as endpoints in studies performed at major competitions in athletics has been summarised. Constructing a methodology that combines the performance metric variables (continuous and ordinal) that are currently utilised as endpoints remains a challenge. [ABSTRACT FROM AUTHOR]

The author discusses the prevention of tennis-related injuries. He mentions the relationship between higher training loads and higher injury rates, the article "The training-injury prevention paradox: should athletes be training smarter and harder?" by T. J. Gabbett, and the application of load approach to tennis. The author provides tips for preventing tennis injuries which includes establishing basic fitness level, avoiding peak in loads, and maintaining correct work-rest balance.

The author reflects on a study by M. Sailly and colleagues on the development of groin pain-associated public apophysitis in athletes. Topics discussed include the clinical characteristics of pubic apophysis, its primary risk factors such as a change in training load parameters and increasing age and strength, and the importance of conservative management of training load and rehabilitation.