Adverse Drug reactions in an Ageing PopulaTion risk Prediction (ADAPTiP)
tool: the development of a model for predicting adverse drug
reaction-related hospital admissions in older patients
Abstract
Background: Older patients are at an increased risk of developing
adverse drug reactions (ADRs). The aim of this study was to develop a
risk prediction model (ADAPTiP) for ADR-related hospital admissions in
older populations, based on predictors available at the time of hospital
admission. Methods: We used the Adverse Drug reactions in an Ageing
PopulaTion (ADAPT) cohort (N=798; 361 ADR-related admissions; 437
non-ADR-related admissions), a cross-sectional and prospective cohort
study designed to examine the prevalence of and risk factors for
ADR-related hospital admissions in patients aged ≥ 65 years. Twenty
predictors (categorised as sociodemographic-related, functional
ability-related, disease-related and medication-related) were considered
in the development of the model. A multivariable logistic regression
model was developed using statistically significant univariate
associations and/or clinically relevant predictors to estimate adjusted
odds ratios and 95% confidence intervals (CI). Calibration and
discriminative performance of the model was assessed by the
Hosmer-Lemeshow test and by calculating the area under the receiver
operator characteristic (AUROC) curve. Results: The multivariable model
(ADAPTiP) included ten predictors. Antithrombotic agents, diuretics and
RAAS drug classes and the primary presenting complaints of bleeding
disorders, gastrointestinal disorders and syncope and frailty were
significantly associated with an ADR-related hospital admission.
Increasing age and having chronic lung disease were significantly
associated with having a non-ADR-related hospital admission. The AUROC
was 0.78 [95%CI:0.75;0.81] with sensitivity and specificity values
of 59% and 83%, respectively. Conclusion: ADAPTiP has potential as a
risk prediction model for ADR-related hospital admissions. Future
research will validate this model in other settings.