Total elbow replacement in England: a protocol for analysis of National Joint Registry and Hospital Episode Statistics data.

Introduction: Primary total elbow replacement (TER) services in England are being restructured with the goal of centralising care to specialised centres. It is important to monitor the impact of this service redesign. This protocol outlines an intended analysis to provide detailed descriptions of the patients who are receiving primary TER, where and by whom TER is being performed, and what the current surgical practices for TER are in England before the reconfiguration.

How to develop, validate, and update clinical prediction models using multinomial logistic regression.

Objectives: Multicategory prediction models (MPMs) can be used in health care when the primary outcome of interest has more than two categories. The application of MPMs is scarce, possibly due to added methodological complexities compared to binary outcome models. We provide a guide of how to develop, validate, and update clinical prediction models based on multinomial logistic regression.

Calibration plots for multistate risk predictions models.

Introduction: There is currently no guidance on how to assess the calibration of multistate models used for risk prediction. We introduce several techniques that can be used to produce calibration plots for the transition probabilities of a multistate model, before assessing their performance in the presence of random and independent censoring through a simulation.

Methods: We studied pseudo-values based on the Aalen-Johansen estimator, binary logistic regression with inverse probability of censoring weights (BLR-IPCW), and multinomial logistic regression with inverse probability of censoring weights (MLR-IPCW).

Prognostic factors associated with failure of total elbow arthroplasty.

Aims: The aims of this study were to identify and evaluate the current literature examining the prognostic factors which are associated with failure of total elbow arthroplasty (TEA).

Methods: Electronic literature searches were conducted using MEDLINE, Embase, PubMed, and Cochrane. All studies reporting prognostic estimates for factors associated with the revision of a primary TEA were included.

Developing and externally validating multinomial prediction models for methotrexate treatment outcomes in patients with rheumatoid arthritis: results from an international collaboration.

Objectives: In rheumatology, there is a clinical need to identify patients at high risk (>50%) of not responding to the first-line therapy methotrexate (MTX) due to lack of disease control or discontinuation due to adverse events (AEs). Despite this need, previous prediction models in this context are at high risk of bias and ignore AEs. Our objectives were to (i) develop a multinomial model for outcomes of low disease activity and discontinuing due to AEs 6 months after starting MTX, (ii) update prognosis 3-month following treatment initiation, and (iii) externally validate these models.

Prognostic factors associated with failure of total elbow replacement: a protocol for a systematic review.

Introduction: Total elbow replacement (TER) has higher failure rates requiring revision surgery compared with the replacement of other joints. Understanding the factors associated with failure is essential for informed decision-making between patients and clinicians, and for reducing the failure rate. This review aims to identify, describe and appraise the literature examining prognostic factors for failure of TER.

Sample size requirements are not being considered in studies developing prediction models for binary outcomes: a systematic review.

Background: Having an appropriate sample size is important when developing a clinical prediction model. We aimed to review how sample size is considered in studies developing a prediction model for a binary outcome.

Methods: We searched PubMed for studies published between 01/07/2020 and 30/07/2020 and reviewed the sample size calculations used to develop the prediction models.

Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques.

Introduction: This study considers the prediction of the time until two survival outcomes have both occurred. We compared a variety of analytical methods motivated by a typical clinical problem of multimorbidity prognosis.

Methods: We considered five methods: product (multiply marginal risks), dual-outcome (directly model the time until both events occur), multistate models (msm), and a range of copula and frailty models.

Day-to-day variability of knee pain and the relationship with physical activity in people with knee osteoarthritis: an observational, feasibility study using consumer smartwatches.

Objective: To assess the feasibility of using smartwatches in people with knee osteoarthritis (OA) to determine the day-to-day variability of pain and the relationship between daily pain and step count.

Design: Observational, feasibility study.

Setting: In July 2017, the study was advertised in newspapers, magazines and, on social media.

Serum HE4 predicts progestin treatment response in endometrial cancer and atypical hyperplasia: A prognostic study.

Objective: To investigate serum human epididymis-4 (HE4) as a predictive biomarker of intrauterine progestin response in endometrial cancer and atypical endometrial hyperplasia (AEH).

Design: Prospective prognostic factor study.

Setting: Consecutive sample of women attending a tertiary gynaecological oncology centre in northwest England.

Can prognostic factors for indirect muscle injuries in elite football (soccer) players be identified using data from preseason screening? An exploratory analysis using routinely collected periodic health examination records.

Background: In elite football, periodic health examination (PHE) may be useful for injury risk prediction.

Objective: To explore whether PHE-derived variables are prognostic factors for indirect muscle injuries (IMIs) in elite players.

Design: Retrospective cohort study.

Clinical prediction models for methotrexate treatment outcomes in patients with rheumatoid arthritis: A systematic review and meta-analysis.

Background: In the management of rheumatoid arthritis (RA), there is a clinical need to identify which patients are at high-risk of not responding to methotrexate (MTX), or experiencing adverse events (AEs), to enable earlier alternative treatments. Many clinical prediction models (CPMs) have previously been developed, but a summary of such models and their methodological quality is lacking. This systematic review aimed to (i) identify and summarize previously published CPMs of MTX outcomes in biologic-naïve RA patients, and (ii) critically appraise their methodological properties.

Association between psoriatic disease and lifestyle factors and comorbidities: cross-sectional analysis and Mendelian randomization.

Objectives: To examine associations between PsA and psoriasis vs lifestyle factors and comorbidities by triangulating observational and genetic evidence.

Methods: We analysed cross-sectional data from the UK Biobank (1836 PsA, 8995 psoriasis, 36 000 controls) to describe the association between psoriatic disease and lifestyle factors (including BMI and smoking) and 15 comorbidities [including diabetes and coronary artery disease (CAD)] using logistic models adjusted for age, sex and lifestyle factors. We applied bidirectional Mendelian randomization (MR) to genome-wide association data (3609 PsA and 7804 psoriasis cases, up to 1.

Heterogeneity in the association between weather and pain severity among patients with chronic pain: a Bayesian multilevel regression analysis.

Introduction: Previous studies on the association between weather and pain severity among patients with chronic pain have produced mixed results. In part, this inconsistency may be due to differences in individual pain responses to the weather.

Methods: To test the hypothesis that there might be subgroups of participants with different pain responses to different weather conditions, we examined data from a longitudinal smartphone-based study, Cloudy with a Chance of Pain, conducted between January 2016 and April 2017.

Understanding the Predictors of Missing Location Data to Inform Smartphone Study Design: Observational Study.

Background: Smartphone location data can be used for observational health studies (to determine participant exposure or behavior) or to deliver a location-based health intervention. However, missing location data are more common when using smartphones compared to when using research-grade location trackers. Missing location data can affect study validity and intervention safety.

Clinical Prediction Models in Sports Medicine: A Guide for Clinicians and Researchers.

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.

Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods.

Background: Clinical prediction models (CPMs) predict the risk of health outcomes for individual patients. The majority of existing CPMs only harness cross-sectional patient information. Incorporating repeated measurements, such as those stored in electronic health records, into CPMs may provide an opportunity to enhance their performance.

The Value of Preseason Screening for Injury Prediction: The Development and Internal Validation of a Multivariable Prognostic Model to Predict Indirect Muscle Injury Risk in Elite Football (Soccer) Players.

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).

A review of the use of propensity score diagnostics in papers published in high-ranking medical journals.

Background: Propensity scores are widely used to deal with confounding bias in medical research. An incorrectly specified propensity score model may lead to residual confounding bias; therefore it is essential to use diagnostics to assess propensity scores in a propensity score analysis. The current use of propensity score diagnostics in the medical literature is unknown.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal.

Objective: To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease.

Design: Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group.

Data Sources: PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020.

Are weather conditions associated with chronic musculoskeletal pain? Review of results and methodologies.

Many people believe that weather influences chronic musculoskeletal pain. Previous studies on this association are narratively reviewed, with particular focus on comparing methodologies and summarising study findings in light of study quality. We searched 5 databases (Medline, Embase, Web of Science, PsycINFO, and Scopus) for observational studies on the association between weather variables and self-reported musculoskeletal pain severity.

Engagement and Participant Experiences With Consumer Smartwatches for Health Research: Longitudinal, Observational Feasibility Study.

Background: Wearables provide opportunities for frequent health data collection and symptom monitoring. The feasibility of using consumer cellular smartwatches to provide information both on symptoms and contemporary sensor data has not yet been investigated.

Objective: This study aimed to investigate the feasibility and acceptability of using cellular smartwatches to capture multiple patient-reported outcomes per day alongside continuous physical activity data over a 3-month period in people living with knee osteoarthritis (OA).

What is the inter-rater agreement of injury classification using the WHO minimum data set for emergency medical teams?

Background: In 2017, the WHO produced its first minimum data set (MDS) for emergency medical team (EMT) daily reporting during the sudden-onset disasters (SODs), following expert consensus. The MDS was deliberately designed to be simple in order to improve the rate of data capture; however, it is new and untested. This study assesses the inter-rater agreement between practitioners when performing the injury aspect of coding within the WHO EMT MDS.