Predicting, describing, or measuring? How to align model purpose with validity and applicability in critical care outcome research

Purpose of review Clinical models are commonly applied in critical care for both descriptive and predictive purposes. However, methodological rigour is often lacking in their development and validation. This review examines the principles underlying the multiple domains of model validity. We argue that a clear model purpose and theoretical framework are essential preconditions for validity. Recent findings Recently developed descriptive and predictive models illustrate different approaches to promoting validity. In developing SOFA-2, eCARTv5, Sepsis-3 and the PHOENIX paediatric sepsis criteria, authors used combinations of expert-driven consensus, data-driven derivation and iterative refinement. These examples demonstrate that validity requires a process of repeated evaluation across distinct populations, settings and time periods. Summary The best approach to establishing validity combines a clear theoretical framework, structured expert consensus (including Delphi methodology), rigorous statistical evaluation (discrimination, calibration, net benefit) and prospective external validation. The distinction between models designed to predict outcomes and those designed to describe or quantify organ dysfunction is fundamental and should guide development and validation strategy from the outset.