Search

Background Nitrate (NO3−) supplementation has been reported to lower motor unit (MU) firing rate (MUFR) during dynamic resistance exercise; however, its impact on MU activity during isometric and ischemic exercise is unknown. Purpose To assess the effect of NO3− supplementation on knee extensor MU activities during brief isometric contractions and a 3 min sustained contraction with blood flow restriction (BFR). Methods Sixteen healthy active young adults (six females) completed two trials in a randomized, double-blind, crossover design. Trials were preceded by 5 days of either NO3− (NIT) or placebo (PLA) supplementation. Intramuscular electromyography was used to determine the M. vastus lateralis MU potential (MUP) size, MUFR and near fibre (NF) jiggle (a measure of neuromuscular stability) during brief (20 s) isometric contractions at 25% maximal strength and throughout a 3 min sustained BFR isometric contraction. Results Plasma nitrite (NO2−) concentration was elevated after NIT compared to PLA (475 ± 93 vs. 198 ± 46 nmol L−1, p p > 0.05), MUP duration was shorter with NIT compared to PLA during brief isometric contractions and the sustained ischemic contraction (p p Conclusions These findings provide insight into the effect of NO3− supplementation on MUP properties and reveal faster MUP duration after short-term NO3− supplementation which may have positive implications for skeletal muscle contractile performance.

Participating in sport carries inherent risk of injury. Clinicians execute high-level clinical reasoning and decision making to support athletes to achieve the best outcomes. Accurately diagnosing a problem, estimating prognosis, or selecting the most suitable intervention for each athlete is challenging. Clinical prediction models are tools to assist clinicians in estimating the risk or probability of a health outcome for an individual by using data from multiple predictors. Although common in general medical literature, clinical prediction models are rare in sports medicine. The purpose of this article was to (1) describe the steps required to develop and validate (ie, evaluate) a clinical prediction model for clinical researchers, and (2) help sports medicine clinicians understand and interpret clinical prediction model studies. Using a case study to illustrate how to implement clinical prediction models in practice, we address the following issues in developing and validating a clinical prediction model: study design and data, sample size, missing data, selecting predictors, handling continuous predictors, model fitting, internal and external validation, performance measures, reporting, and model presentation. Our work builds on initiatives to improve diagnostic and prognostic clinical research, including the PROGnosis RESearch Strategy (PROGRESS) series of papers and textbook and the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement.

Background /objective: The Survey Instrument for Natural History, Aetiology and Prevalence of Patellofemoral Pain (SNAPPS) is a self-report questionnaire which is a specifically designed measurement instrument to identify patellofemoral pain. It has reported high sensitivity, specificity and test-retest reliability to discriminate between people with knee pain, with or without patellofemoral pain. SNAPPS hasn't been studied in Thailand; therefore, the aim of this study was to cross-culturally adapt the questionnaire into Thai. Method This study was separated into two phases: cross-cultural adaptation and test-retest reliability. The Survey Instrument for Natural History, Aetiology and Prevalence of Patellofemoral Pain was translated into Thai following the guidelines for the cross cultural adaptation of self-report measures including six steps. Thirty four knee pain patients performed the test-retest reliability of the final version of this questionnaire. They were clinically diagnosed with patellofemoral pain by a physical therapist. They were asked to complete the questionnaire twice; with the 1st session and 2nd session having a 30 min break between. The intraclass correlation coefficient (ICC3, 1) method was used to determine test-retest reliability. The correlation of SNAPPS and VAS-U, VAS-W, VAS-S, VAS- J, VAS- R, and VAS- SQ were analyzed by Pearson correlation. Results The thirty-four participants (19 males, 15 females; with ages ranging 19–24 years) with patellofemoral pain were assessed twice with a 30 min break between the two sessions. The total scores of section 2 and 4 of the questionnaire indicated very strong test-retest reliability, ranging from 0.83 to 0.954 and the total score was ICC 0.91. Moreover, the Survey Instrument for Natural History, Aetiology and Prevalence of Patellofemoral Pain had a correlation with intensity of pain during ascending and descending stairs. Conclusion The Thai version of the Survey Instrument for Natural History, Aetiology and Prevalence of Patellofemoral Pain can be used to assess patellofemoral pain in young Thai patients.

Background: Running is a popular sport with widely recognized health benefits. Given the high rates of knee injury in runners and the growing prevalence of knee osteoarthritis (KOA), it may be useful to assess perceptions about running and knee joint health. Purpose: The objectives of this study were to (1) explore and compare the perceptions of the general public (PUB) and health care professionals (HCPs) on the topic of running and knee health and (2) explore recommendations about running and knee health provided by HCPs. Study Design: Cross-sectional study. Methods: We conducted an online survey between June 18 and October 1, 2020. The questionnaire included questions on running and knee health, and HCPs were asked about their typical recommendations and level of confidence in providing recommendations on the topic. Perceptions (proportions) were compared between the PUB and HCPs using the chi-square test. Results: In total, 4521 responses (PUB, n = 2514; HCPs, n = 2007) were analyzed. A greater proportion of HCPs perceived regular running as healthy for knees (86% vs 68%; P < .001). More of the PUB than HCPs ( P < .001) believed that running frequently (29% vs 13%), long distances (54% vs 45%), and on hard surfaces (60% vs 36%) increased the risk of developing KOA. Running for those with KOA was perceived by the PUB as posing an increased risk of getting more knee pain (48%) and needing joint replacement surgery (38%), more so than by HCPs (26% and 17%, respectively). The majority of HCPs reported being relatively confident in providing evidence-based recommendations about running and knee health and mostly recommended that runners with KOA modify training parameters instead of quit. Conclusion: More HCPs perceived running as healthy for knees when compared with the PUB. Most HCPs felt confident in providing evidence-based recommendations about running and knee health.

BackgroundIn elite football, periodic health examination (PHE) may be useful for injury risk prediction.ObjectiveTo explore whether PHE-derived variables are prognostic factors for indirect muscle injuries (IMIs) in elite players.DesignRetrospective cohort study.SettingAn English Premier League football club.Participants134 outfield elite male players, over 5 seasons (1 July 2013–19 May 2018).Outcome and analysisThe outcome was any time-loss, lower extremity index IMI (I-IMI). Prognostic associations were estimated using odds ratios (ORs) and corresponding statistical significance for 36 variables, derived from univariable and multivariable logistic regression models. Missing data were handled using multiple imputation. Non-linear associations were explored using fractional polynomials.ResultsDuring 317 participant-seasons, 138 I-IMIs were recorded. Univariable associations were determined for previous calf IMI frequency (OR 1.80, 95% CI 1.09 to 2.97), hamstring IMI frequency (OR 1.56, 95% CI 1.17 to 2.09), if the most recent hamstring IMI occurred >12 months but 12 months but ConclusionPHE has limited use for injury risk prediction. Most variables did not add prognostic value over and above age, other than if a player experienced a hamstring IMI >12 months but Trial registration numberNCT03782389.

Patellofemoral pain is a common and often debilitating musculoskeletal condition. Clinical translation and evidence synthesis of patellofemoral pain research are compromised by heterogenous and often inadequately reported study details. This consensus statement and associated checklist provides standards for REPORTing of quantitative PatelloFemoral Pain (REPORT-PFP) research to enhance clinical translation and evidence synthesis, and support clinician engagement with research and data collection. A three-stage Delphi process was initiated at the 2015 International Patellofemoral Research Network (iPFRN) retreat. An initial e-Delphi activity (n=24) generated topics and items, which were refined at the 2017 iPFRN retreat, and voted on prior to and following the 2019 iPFRN retreat (n=51 current and past retreat participants). Voting criteria included ‘strongly recommended’ (essential), ‘recommended’ (encouraged) and uncertain/unsure. An item was included in the checklist if ≥70% respondents voted ‘recommended’. Items receiving ≥70% votes for ‘strongly recommended’ were labelled as such. The final REPORT-PFP checklist includes 31 items (11 strongly recommended, 20 recommended), covering (i) demographics (n=2,4); (ii) baseline symptoms and previous treatments (n=3,7); (iii) outcome measures (2,4); (iv) outcomes measure description (n=1,2); (v) clinical trial methodology (0,3) and (vi) reporting study results (n=3,0). The REPORT-PFP checklist is ready to be used by researchers and clinicians. Strong stakeholder engagement from clinical academics during development means consistent application by the international patellofemoral pain research community is likely. Checklist adherence will improve research accessibility for clinicians and enhance future evidence synthesis.

Objective: To compare bone marrow oedema-like lesion (BML) volume in subjects with symptomatic patellofemoral (PF) knee osteoarthritis (OA) using four different MRI sequences and to determine reliability of BML volume assessment using these sequences and their correlation with pain. Methods: 76 males and females (mean age 55.8 years) with symptomatic patellofemoral knee OA had 1.5 T MRI scans. PD fat suppressed (FS), STIR, contrast-enhanced (CE) T1W FS, and 3D T1W fast field echo (FFE) sequences were obtained. All sequences were assessed by one reader, including repeat assessment of 15 knees using manual segmentation and the measurements were compared. We used random-effects panel linear regression to look for differences in the log-transformed BML volume (due to positive skew in the BML volume distribution) between sequences and to determine associations between BML volumes and knee pain. Results: 58 subjects had PF BMLs present on at least one sequence. Median BML volume measured using T1W FFE sequence was significantly smaller (224.7 mm3, interquartile range [IQR] 82.50–607.95) than the other three sequences. BML volume was greatest on the CE sequence (1129.8 mm3, IQR 467.28–3166.02). Compared to CE sequence, BML volumes were slightly lower when assessed using PDFS (proportional difference = 0.79; 95% confidence interval [CI] 0.62, 1.01) and STIR sequences (proportional difference = 0.85; 95% CI 0.67, 1.08). There were strong correlations between BML volume on PDFS, STIR, and CE T1W FS sequences (ρs = 0.98). Correlations were lower between these three sequences and T1W FFE (ρs = 0.80–0.81). Intraclass correlation coefficients were excellent for proton density fat-suppressed, short-tau inversion recovery, and CE T1W FS sequences (0.991–0.995), while the ICC for T1W FFE was good at 0.88. We found no significant association between BML volumes assessed using any of the sequences and knee pain. Conclusion: T1W FFE sequences were less reliable and measured considerably smaller BML volume compared to other sequences. BML volume was larger when assessed using the contrast enhanced T1W FS though not statistically significantly different from BMLs when assessed using PDFS and STIR sequences. Advances in knowledge: This is the first study to assess BMLs by four different MRI pulse sequences on the same data set, including different fluid sensitive sequences and gradient echo type sequence.

Sports medicine clinicians are expected to make accurate diagnoses, estimate prognoses and identify athletes at risk of sustaining an injury.1 These complex decisions are dependent on clinical reasoning, which is informed by, and often biased toward, a practitioner’s scientific knowledge and experience. Clinical prediction models are developed by researchers to help facilitate such decisions in practice2; data for multiple predictor variables are combined to estimate an individual’s risk of a health outcome either being present (diagnosis) or whether it will occur in future (prognosis).3 Despite being employed widely in clinical medicine, clinical prediction models are uncommon in sports medicine. Clinical prediction models can offer benefits to both practitioners and athletes, but only if they are developed and validated using rigorous methods and transparently reported so that potential users can judge their accuracy and usefulness. Therefore, the purpose of this editorial is to describe the recommended steps for clinical prediction development and validation and to guide practitioners using and interpreting prediction models in sports medicine. The first step in developing a prediction model is to identify its clinical need, the target population and how and when it would fit into the clinical workflow. Models should predict outcomes that are relevant to sport stakeholders, and be clearly defined, including how and when assessed.4 Next is to identify any existing models that could be evaluated or updated. If not, …

Background Current clinical guidelines recommend conservative management including non-pharmacologic therapy prior to considering surgery for knee OA. There is a paucity of clinical trials investigating the use of biomechanical device therapies on those with patellofemoral joint osteoarthritis (PFJOA). The aim was to systematically review the effectiveness of biomechanical devices (bracing, taping, and footwear) in the management of symptomatic PFJOA. Method The Cochrane, PEDro, MEDLINE, CINAHL, AMED and EMBASE electronic databases were search from inception to October 31, 2020. Included studies were randomised controlled or clinical trials studying any form of biomechanical device therapy in the management of PFJOA in the English language. Studies included in the search were quality-appraised using the PEDro scoring system. Result Eleven studies were identified which included assessment of either patellar taping, or foot orthotics, knee bracing or combined physiotherapy treatments. Trial quality ranged from ‘poor’ through ‘fair’ to ‘good’. For patellar bracing, pooled analysis of two good quality randomised controlled trials showed no overall significant improvement on a visual analogue scale (VAS) (random effects (RE) standardised mean difference (SMD) = −0.42 (95%CI −1.12 to +0.29). Pooled data from the same two studies showed a non-significant improvement in favour of bracing assessed by the KOOS/WOMAC (RE SMD = −0.18 (95%CI −0.66 to +0.31). Two studies of ‘fair’ and ‘good’ quality applying patellar tape showed a significant reduction in pain immediately after application and after 4 days. A randomised trial of a foot orthotic showed a non-significant improvement in pain after 6 weeks with a between groups adjusted mean difference for maximum VAS of 21.9 mm (95% CI − 2.1 to 46.0) and 8.1 (95% CI− 6.9 to 23.1) for KOOS pain. A multimodal physiotherapy intervention (which included taping in two studies) showed a pooled significant improvement in VAS (SMD = −0.4; (95% CI −0.71 to −0.09) at 3 months compared to controls. Conclusion There is some good quality evidence that a combined physiotherapy approach significantly reduces short-term pain in those with PFJOA. Long-term effects of all interventions are still unknown, which indicates the need for further research to determine the longer term impact of all biomechanical devices on outcomes in symptomatic PFJOA.

BackgroundBrace effectiveness for knee osteoarthritis (OA) remains unclear and international guidelines offer conflicting recommendations. Our trial will determine the clinical and cost-effectiveness of adding knee bracing (matched to patients’ clinical and radiographic presentation and with adherence support) to a package of advice, written information and exercise instruction delivered by physiotherapists.Methods and analysisA multicentre, pragmatic, two-parallel group, single-blind, superiority, randomised controlled trial with internal pilot and nested qualitative study. 434 eligible participants with symptomatic knee OA identified from general practice, physiotherapy referrals and self-referral will be randomised 1:1 to advice, written information and exercise instruction and knee brace versus advice, written information and exercise instruction alone. The primary analysis will be intention-to-treat comparing treatment arms on the primary outcome (Knee Osteoarthritis Outcomes Score (KOOS)-5) (composite knee score) at the primary endpoint (6 months) adjusted for prespecified covariates. Secondary analysis of KOOS subscales (pain, other symptoms, activities of daily living, function in sport and recreation, knee-related quality of life), self-reported pain, instability (buckling), treatment response, physical activity, social participation, self-efficacy and treatment acceptability will occur at 3, 6, and 12 months postrandomisation. Analysis of covariance and logistic regression will model continuous and dichotomous outcomes, respectively. Treatment effect estimates will be presented as mean differences or ORs with 95% CIs. Economic evaluation will estimate cost-effectiveness. Semistructured interviews to explore acceptability and experiences of trial interventions will be conducted with participants and physiotherapists delivering interventions.Ethics and disseminationNorth West Preston Research Ethics Committee, the Health Research Authority and Health and Care Research in Wales approved the study (REC Reference: 19/NW/0183; IRAS Reference: 247370). This protocol has been coproduced with stakeholders including patients and public. Findings will be disseminated to patients and a range of stakeholders.Trial registration numberISRCTN28555470.

IntroductionKnee osteoarthritis (OA) is a prevalent and disabling musculoskeletal condition. Biomechanical factors may play a key role in the aetiology of knee OA, therefore, a broad class of interventions involves the application or wear of devices designed to mechanically support knees with OA. These include gait aids, bracing, taping, orthotics and footwear. The literature regarding efficacy of mechanical interventions has been conflicting or inconclusive, and this may be because certain subgroups with knee OA respond better to mechanical interventions. Our primary aim is to identify subgroups with knee OA who respond favourably to mechanical interventions.Methods and analysisWe will conduct a systematic review to identify randomised clinical trials of any mechanical intervention for the treatment of knee OA. We will invite lead authors of eligible studies to share individual participant data (IPD). We will perform an IPD meta-analysis for each type of mechanical intervention to evaluate efficacy, with our main outcome being pain. Where IPD are not available, this will be achieved using aggregate data. We will then evaluate five potential treatment effect modifiers using a two-stage approach. If data permit, we will also evaluate whether biomechanics mediate the effects of mechanical interventions on pain in knee OA.Ethics and disseminationNo new data will be collected in this study. We will adhere to institutional, national and international regulations regarding the secure and confidential sharing of IPD, addressing ethics as indicated. We will disseminate findings via international conferences, open-source publication in peer-reviewed journals and summaries posted on websites serving the public and clinicians.PROSPERO registration numberCRD42020155466.

This study used periodic health examination (PHE) data from 134 outfield elite male football players, over 5 seasons (1st July 2013 to 19th May 2018). Univariable and multivariable logistic regression models were used to determine prognostic associations between 36 variables and time-loss, lower extremity index indirect muscle injuries (I-IMIs). Non-linear associations were explored using fractional polynomials. During 317 participant-seasons, 138 I-IMIs were recorded. Univariable associations were determined for previous calf indirect muscle injury (IMI) frequency (OR=1.80, 95% confidence interval (CI) = 1.09 to 2.97), hamstring IMI frequency (OR=1.56, 95% CI=1.17 to 2.09), if the most recent hamstring IMI occurred > 12 months but < 3 years prior to PHE (OR= 2.95, 95% CI = 1.51 to 5.73) and age (OR =1.12 per 1-year increase, 95% CI = 1.06 to 1.18). Multivariable analyses demonstrated that if a player’s most recent previous hamstring IMI was >12 months but

This thesis establishes the feasibility and validity of using digital surveys to collect population-based data. Subsequently, the thesis reports on the utilisation of a digital questionnaire determine the prevalence of patellofemoral pain (PFP) at mass-participant running events within the UK. In Chapter 2, to determine the feasibility creating a digital Survey instrument for Natural history, Aetiology and Prevalence of Patellofemoral pain Studies (SNAPPS) questionnaire, a systematic review comparing the response rate and completeness of digital and paper-based epidemiological surveys was conducted. The review found paper-based surveys to have a slightly higher response rate than digital surveys. As digital surveys offer several other benefits including lower costs per response, ease of data collection and automation of results coding, a pragmatic and practical approach was taken and, the paper version of the SNAPPS questionnaire was converted to a digital online version. In Chapter 3, eSNAPPS was developed and then validated against the original paper SNAPPS. Results showed that eSNAPPS was equivalent to paper SNAPPS and was valid against the paper version in determining the presence of PFP. Subsequently, in Chapter 4, eSNAPPS was utilised to evaluate the prevalence of PFP in individuals from the general population who attended mass-participation events in the UK. In this chapter, a cross-sectional study was conducted. There were over 1,080 responses, and with no missing data within the returned surveys. Furthermore, from the largest study in the UK and second largest in the world, the prevalence of PFP of those within the community attending mass-participant events was 17.4%. The results in this chapter highlighted that it was feasible to collect population-based data using eSNAPPS and that the adaptation of SNAPPS questionnaire has a positive outcome on the quality of data whilst also minimising the logistical demand surrounding data entry and data management. The findings from this thesis confirm the role that digital surveys can play in data collections for large scale epidemiology studies and the role of eSNAPPS in establishing the prevalence of PFP in the general population.

Objective\ud \ud Trials testing promising interventions in knee osteoarthritis (OA) often fail to show pain reductions. This may be due to change in activity whereby a person’s pain decreases, leading them to increase their activity levels, in turn increasing pain back to baseline levels. Using data from a trial of a beneficial treatment for knee pain, we explored whether activity changes might mask a treatment’s effect on pain, by looking at whether activity levels increased with effective treatment and whether change in activity level related to change in pain.\ud \ud Design\ud \ud During the InRespond trial (ISRCTN55059760) participants wore an accelerometer for 7 days before and during treatments. We assessed change in pain on treatment using scores for overall knee pain and pain in a nominated pain-aggravating activity both in the last week and evaluated change in different types of activity using accelerometer data. Principal components analysis tested whether change in activity and pain outcomes were correlated and created composites combining them. We then tested whether activity, pain or the composites showed a treatment effect, and examined their responsiveness.\ud \ud Results\ud \ud In the 61 participants (mean age 64.5 years, 38% women, mean overall knee pain score 5.08 (0-10)), activity levels mostly decreased during the trial. Principal component analyses suggested that pain and activity did not correlate highly, loading on different components. Treatment that showed significant effects on pain did not show similar effects on either activity (e.g. the active treatment had a slightly greater reduction in total steps taken than the control treatment (difference 1942.6 steps/week, p =.42) nor on composites combining activity and pain. Pain outcomes were the most responsive; static loading (standing) outcomes were the most responsive activity outcome.\ud \ud Conclusion\ud We found no evidence to support the hypothesis that activity levels increase during effective OA treatment and might account for the negligible pain effects of OA treatments.

Background In elite football (soccer), periodic health examination (PHE) could provide prognostic factors to predict injury risk. Objective To develop and internally validate a prognostic model to predict individualised indirect (non-contact) muscle injury (IMI) risk during a season in elite footballers, only using PHE-derived candidate prognostic factors. Methods Routinely collected preseason PHE and injury data were used from 152 players over 5 seasons (1st July 2013 to 19th May 2018). Ten candidate prognostic factors (12 parameters) were included in model development. Multiple imputation was used to handle missing values. The outcome was any time-loss, index indirect muscle injury (I-IMI) affecting the lower extremity. A full logistic regression model was fitted, and a parsimonious model developed using backward-selection to remove factors that exceeded a threshold that was equivalent to Akaike’s Information Criterion (alpha 0.157). Predictive performance was assessed through calibration, discrimination and decision-curve analysis, averaged across all imputed datasets. The model was internally validated using bootstrapping and adjusted for overfitting. Results During 317 participant-seasons, 138 I-IMIs were recorded. The parsimonious model included only age and frequency of previous IMIs; apparent calibration was perfect, but discrimination was modest (C-index = 0.641, 95% confidence interval (CI) = 0.580 to 0.703), with clinical utility evident between risk thresholds of 37–71%. After validation and overfitting adjustment, performance deteriorated (C-index = 0.589 (95% CI = 0.528 to 0.651); calibration-in-the-large = − 0.009 (95% CI = − 0.239 to 0.239); calibration slope = 0.718 (95% CI = 0.275 to 1.161)). Conclusion The selected PHE data were insufficient prognostic factors from which to develop a useful model for predicting IMI risk in elite footballers. Further research should prioritise identifying novel prognostic factors to improve future risk prediction models in this field. Trial registration NCT03782389

AimsWe conducted a systematic review assessing the reporting quality of studies validating models based on machine learning (ML) for clinical diagnosis, with a specific focus on the reporting of information concerning the participants on which the diagnostic task was evaluated on.MethodMedline Core Clinical Journals were searched for studies published between July 2015 and July 2018. Two reviewers independently screened the retrieved articles, a third reviewer resolved any discrepancies. An extraction list was developed from the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis guideline. Two reviewers independently extracted the data from the eligible articles. Third and fourth reviewers checked, verified the extracted data as well as resolved any discrepancies between the reviewers.ResultsThe search results yielded 161 papers, of which 28 conformed to the eligibility criteria. Detail of data source was reported in 24 of the 28 papers. For all of the papers, the set of patients on which the ML-based diagnostic system was evaluated was partitioned from a larger dataset, and the method for deriving such set was always reported. Information on the diagnostic/non-diagnostic classification was reported well (23/28). The least reported items were the use of reporting guideline (0/28), distribution of disease severity (8/28 patient flow diagram (10/28) and distribution of alternative diagnosis (10/28). A large proportion of studies (23/28) had a delay between the conduct of the reference standard and ML tests, while one study did not and four studies were unclear. For 15 studies, it was unclear whether the evaluation group corresponded to the setting in which the ML test will be applied to.ConclusionAll studies in this review failed to use reporting guidelines, and a large proportion of them lacked adequate detail on participants, making it difficult to replicate, assess and interpret study findings.PROSPERO registration numberCRD42018099167.

BackgroundIn elite football (soccer), periodic health examination (PHE) could provide prognostic factors to predict injury risk.ObjectiveTo develop and internally validate a prognostic model to predict individual indirect (non-contact) muscle injury (IMI) risk during a season in elite footballers, only using PHE-derived candidate prognostic factors.MethodsRoutinely collected preseason PHE and injury data were used from 119 players over 5 seasons (1stJuly 2013 to 19thMay 2018). Ten candidate prognostic factors (12 parameters) were included in model development. Multiple imputation was used to handle missing values. The outcome was any time-loss, index indirect muscle injury (I-IMI) affecting the lower extremity. A full logistic regression model was fitted, and a parsimonious model developed using backward-selection to remove non-significant factors. Predictive performance was assessed through calibration, discrimination and decision-curve analysis, averaged across all imputed datasets. The model was internally validated using bootstrapping and adjusted for overfitting.ResultsDuring 317 participant-seasons, 138 I-IMIs were recorded. The parsimonious model included only age and frequency of previous IMIs; apparent calibration was perfect but discrimination was modest (C-index = 0.641, 95% confidence interval (CI): 0.580 to 0.703), with clinical utility evident between risk thresholds of 37-71%. After validation and overfitting adjustment, performance deteriorated (C-index = 0.580; calibration-in-the-large =-0.031, calibration slope =0.663).ConclusionThe selected PHE data were insufficient prognostic factors from which to develop a useful model for predicting IMI risk in elite footballers. Further research should prioritise identifying novel prognostic factors to improve future risk prediction models in this field.Trial registration numberNCT03782389KEY POINTSFactors measured through preseason screening generally have weak prognostic strength for future indirect muscle injuries and further research is needed to identify novel, robust prognostic factors.Because of sample size restrictions, and until the evidence base improves, it is likely that any further attempts at creating a prognostic model at individual club level would also suffer from poor performance.The value of using preseason screening data to make injury predictions or to select bespoke injury prevention strategies remains to be demonstrated, so screening should only be considered as useful for detection of salient pathology or for rehabilitation/ performance monitoring purposes at this time.

Objective To present the current status of knowledge in the field of patellofemoral (PF) osteoarthritis (OA) and formulate a research agenda in order to guide future research on this topic. Design A 1-day meeting was organized with the aim to bring together international experts in the field to discuss the current state of knowledge on PF OA. Experts from multiple disciplines were invited based on their scientific publications in the field of PF OA and interest in the subject. Topics discussed include the diagnosis, impact, prognosis, and treatment of PF OA. Methods Following context-setting presentations, an interactive discussion was held in order to achieve consensus on the PF OA topics of interest: (1) diagnosis and definition; (2) burden; (3) outcome measures; (4) prognosis; (5) risk factors, and (6) treatment. Groups of meeting attendees reviewed the literature on these topics and narratively summarized the current state of knowledge, and each group formulated research agenda items relevant to the specific topics of interest. Each consortium member consequently ranked the importance of all items on a 0–10 Numerical Rating Scale (NRS) (10 = extremely important, to 0 = not at all important). Results After ranking all formulated items on importance, 6 of the 28 research agenda items formulated received an average of 7.5 points on the NRS. The most highly ranked items covered the fields of treatment, diagnosis, and definition of PF OA. Conclusions We recommend to develop clear clinical criteria for PF OA and to reach consensus on the definition of PF OA by both radiographs and MRI. Additionally, more understanding is necessary to be able to distinguish PF symptoms from those arising from the tibiofemoral joint. More insight is needed on effective treatment strategies for PF OA; specifically, tailoring nonpharmacological treatments to individuals with PF OA, and determining whether isolated PF OA requires different treatment strategies than combined PF and tibiofemoral OA.

Patellofemoral pain (PFP) can cause significant pain leading to limitations in societal participation and physical activity. PFP is usually associated with athletes undergoing intensive physical training, or military recruits; but recent evidence shows that PFP is common in the general population. The relationship of PFP with physical activity is not entirely clear. Our aim is to provide a better estimate of the general population prevalence of PFP and to relate this to the level of physical activity, and demographic characteristics. The Survey instrument for Natural history, Aetiology and Prevalence of Patellofemoral pain Studies (SNAPPS) was developed as a PFP screening tool to be used in the community. The electronic version of the SNAPPS (eSNAPPS) has recently been validated and was used to survey attendees at mass-participation running events. We will use an electronic survey to collect data from a sample of 1100 Rugby League World Cup spectators. The survey will have four sections: i) general and demographic; ii) knee pain (eSNAPPS); iii) level of physical activity; and iv) quality of life in relation to knee pain. The primary analytic approach will be descriptive of PFP prevalence. Secondary analyses will explore the relationships of the presence of PFP and the other variables. We will disseminate this work by publication of peer-reviewed papers in scientific journals, presentations at scientific conferences, and on the dedicated SNAPPS website https://www.snappspfp.com/.