The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the …

Prediction models in health care use predictors to estimate for an individual the probability
that a condition or disease is already present (diagnostic model) or will occur in the future …

Early identification of children at risk of developing asthma at school age is crucial, but the
usefulness of childhood asthma prediction models in clinical practice is still unclear. We …

The number of studies examining associations between training load and injury has
increased exponentially. As a result, many new measures of exposure and training-load …

Objective This review aimed to summarize the use of machine learning for predicting the
potential benefits of stroke rehabilitation treatments, to evaluate the risk of bias of predictive …

In part 2 of this clinical commentary, we highlight the conceptual and methodologic pitfalls
evident in current training-load–injury research. These limitations make these studies …

Abstract Background Context Evidence is lacking on the prognosis and prognostic factors of
back-related leg pain and sciatica in patients seeing their primary care physicians. This …

Cardiovascular disease (CVD) risk-prediction models are used to identify high-risk
individuals and guide statin initiation. However, these models are usually derived from …

Background Timely interventions in women presenting with preterm labour can substantially
improve health outcomes for preterm babies. However, establishing such a diagnosis is very …

Background Clinical prediction models are developed widely across medical disciplines.
When predictors in such models are highly collinear, unexpected or spurious predictor …