Assessing the Risk of Developing Delirium on Admission to Inpatient Rehabilitation: A Clinical Prediction Model

Abstract

Objectives: To develop a clinical model to predict the risk of an individual patient developing delirium during inpatient rehabilitation, based on patient characteristics and clinical data available on admission.

Design: Retrospective observational study based on electronic health record data.

Setting and participants: We studied a previously validated data set of inpatients including incident delirium episodes during rehabilitation. These patients were admitted to ZURZACH Care, Rehaklinik Bad Zurzach, a Swiss inpatient rehabilitation clinic, between January 1, 2015, and December 31, 2018.

Methods: We performed logistic regression analysis using backward and forward selection with alpha = 0.01 to remove any noninformative potential predictor. We subsequentially used the Akaike information criterion (AIC) to select the final model among the resulting "intermediate" models. Discrimination of the final prediction model was evaluated using the C-statistic.

Results: Of the 20 candidate predictor variables, 6 were included in the final prediction model: a linear spline of age with 1 knot at 60 years and a linear spline of the functional independence measure (FIM), a measure of the functional degree of patients independency, with 1 knot at 64 points, diagnosis of disorders of fluid, electrolyte, and acid-base balance (E87), use of other analgesic and antipyretics (N02B), use of anti-parkinson drugs (N04B), and an anticholinergic burden score (ACB) of ≥3 points.

Conclusions and implications: Our clinical prediction model could, upon validation, identify patients at risk of incident delirium at admission to inpatient rehabilitation, and thus enable targeted prevention strategies.

Keywords: Delirium risk; clinical prediction model; inpatient rehabilitation.