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Before examining the impact of training load on injury risk in runners, it is important to gain insight into the differences between methods that are used to measure change in training load. To investigate differences between 4 methods when calculating change in training load: (1) weekly training load; (2) acute : chronic workload ratio (ACWR), coupled rolling average (RA); (3) ACWR, uncoupled RA; (4) ACWR, exponentially weighted moving average (EWMA). Descriptive epidemiology study. This study is part of a randomized controlled trial on running injury prevention among recreational runners. Runners received a baseline questionnaire and a request to share global positioning system training data. Runners who registered for running events (distances 10–42.195 km) in the Netherlands. The primary outcome measure was the predefined significant increase in training load (weekly training loads ≥ 30% progression and ACWRs ≥ 1.5), based on training distance. Proportional Venn diagrams visualized the differences between the methods. A total of 430 participants (73.3% men; mean age = 44.3 ± 12.2 years) shared their global positioning system training data for a total of 22 839 training sessions. For the weekly training load, coupled RA, uncoupled RA, and EWMA method, respectively, 33.4% (95% CI = 32.8, 34.0), 16.2% (95% CI = 15.7, 16.6), 25.8% (95% CI = 25.3, 26.4), and 18.9% (95% CI = 18.4, 19.4) of the training sessions were classified as significant increases in training load. Of the training sessions with significant increases in training load, 43.0% from the weekly training load method were different than the coupled RA and EWMA methods. Training sessions with significant increases in training load based on the coupled RA method showed 100% overlap with the uncoupled RA and EWMA methods. The difference in the change in training load measured by weekly training load and ACWR methods was high. To validate an appropriate measure of change in training load in runners, future research on the association between training loads and running-related injury risk is needed. [ABSTRACT FROM AUTHOR]

Objectives To identify highly ranked features related to clinicians' diagnosis of clinically relevant knee OA. Methods General practitioners (GPs) and secondary care physicians (SPs) were recruited to evaluate 5–10 years follow-up clinical and radiographic data of knees from the CHECK cohort for the presence of clinically relevant OA. GPs and SPs were gathered in pairs; each pair consisted of one GP and one SP, and the paired clinicians independently evaluated the same subset of knees. A diagnosis was made for each knee by the GP and SP before and after viewing radiographic data. Nested 5-fold cross-validation enhanced random forest models were built to identify the top 10 features related to the diagnosis. Results Seventeen clinician pairs evaluated 1106 knees with 139 clinical and 36 radiographic features. GPs diagnosed clinically relevant OA in 42% and 43% knees, before and after viewing radiographic data, respectively. SPs diagnosed in 43% and 51% knees, respectively. Models containing top 10 features had good performance for explaining clinicians' diagnosis with area under the curve ranging from 0.76–0.83. Before viewing radiographic data, quantitative symptomatic features (i.e. WOMAC scores) were the most important ones related to the diagnosis of both GPs and SPs; after viewing radiographic data, radiographic features appeared in the top lists for both, but seemed to be more important for SPs than GPs. Conclusions Random forest models presented good performance in explaining clinicians' diagnosis, which helped to reveal typical features of patients recognized as clinically relevant knee OA by clinicians from two different care settings. [ABSTRACT FROM AUTHOR]

Background Patellofemoral pain (PFP) is a nontraumatic knee problem primarily observed in physically active adolescents. The objective of this study was to determine the incidence and management of PFP in children and adolescents in general practice Methods A retrospective cohort study was conducted using a regional primary care database containing full electronic health records of over 300,000 patients. Patients with a new PFP diagnosis between the years 2013 and 2019 were extracted using a search algorithm based on International Classification of Primary Health Care coding and search terms in free text. Data on the management of PFP were manually checked and analysed. In addition, a sub-analysis for chronic and nonchronic PFP patients was performed. Results The mean incidence of PFP over the study period was 3.4 (95% CI 3.2–3.6) per 1,000 person years in the age group of 7–24 years. Girls had a higher incidence rate (4.6 [95% CI 4.3–5.0]) compared to boys (2.3 [95% CI 2.1–2.5]). Peak incidence was at age 13 years for both sexes. The most commonly applied management strategy was advice (55.1%), followed by referral to physiotherapy (28.2%), analgesics prescription (10.4%), and referral to the orthopaedic surgeon (8.9%). No differences were found in age, sex, and treatment between chronic and nonchronic PFP patients. Conclusions The average Dutch general practitioner sees approximately 1.4 new child or adolescent with PFP per year. Overall management strategies were in concordance with current Dutch general practice guideline on nontraumatic knee problems. More insight should be gained in the population with chronic complaints. [ABSTRACT FROM AUTHOR]

Objectives Previous systematic reviews focused on the evidence of common risk factors for knee OA (KOA); however, the effect and strength of association between risk factors and KOA might be different between the two sexes. The aim of the present systematic review was to determine the current evidence on sex differences in the association between risk factors and KOA and their prevalence. Methods We searched the following electronic bibliographic databases: MEDLINE (PubMed), EMBASE and Web of Science. A methodological quality assessment was conducted independently by two researchers according to an adapted version of the standardized set of criteria known as the Newcastle-Ottawa Quality Assessment Scale (NOS). The NOS, a star system, was converted to three categories of quality. Results In total, 27 studies reported sex-specific risk estimates on several risk factors for KOA. Out of the 22 longitudinal cohort studies (except one nested case–control), 12 were of good quality and 10 were of fair quality. The five cross-sectional studies consisted of one of good, three of fair and one of poor quality. There was an indication of sex differences in risk factors leading to higher risk of KOA: high BMI, alcohol consumption, atherosclerosis and high vitamin E levels in women, and high physical activity, soft drink consumption and abdominal obesity in men. Knee injury, high blood pressure and low step rate seem to affect both women and men. Conclusion More good quality studies are needed to assess sex differences in risk factors for KOA, especially for symptomatic/clinical OA. [ABSTRACT FROM AUTHOR]