Objective To provide an overview of prediction models for risk of cardiovascular disease
(CVD) in the general population. Design Systematic review. Data sources Medline and …

Access to big datasets from e-health records and individual participant data (IPD) meta-
analysis is signalling a new advent of external validation studies for clinical prediction …

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 …

Background Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive, fatal motor
neuron disease with a variable natural history. There are no accurate models that predict the …

Validation of prediction models is highly recommended and increasingly common in the
literature. A systematic review of validation studies is therefore helpful, with meta-analysis …

Organisations such as the National Institute for Health and Care Excellence require the
synthesis of evidence from existing studies to inform their decisions—for example, about the …

Abstract Background The Framingham risk models and pooled cohort equations (PCE) are
widely used and advocated in guidelines for predicting 10-year risk of developing coronary …

It is widely recommended that any developed—diagnostic or prognostic—prediction model
is externally validated in terms of its predictive performance measured by calibration and …

Background: Predictions in pregnancy care are complex because of interactions among
multiple factors. Hence, pregnancy outcomes are not easily predicted by a single predictor …

BACKGROUND Identifying patients at high risk of diabetic kidney disease (DKD) helps
improve clinical outcome. PURPOSE To establish a model for predicting DKD. DATA …