ArticleEuropean geriatric medicine2025
Adverse drug reactions and events in an Ageing PopulaTion risk Prediction (ADAPTiP) tool: the development and validation of a model for predicting adverse drug reactions and events in older patients.
Article in European geriatric medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hospital admissions due to adverse drug reactions and adverse drug events in older adults: a systematic review.Age and ageing · 2025Pooled it
- Artificial intelligence-driven risk prediction of polypharmacy in older adults: current advances, clinical applications, and future perspectives.Frontiers in public health · 2026Review
- Machine learning risk prediction models for medication harm in hospitalised adult patients.Therapeutic advances in drug safety · 2026Article
- Association between socioeconomic status and dispensing of higher-risk drug classes and polypharmacy in older community-based populations: a nationwide cohort study.European journal of clinical pharmacology · 2025Article
- Identifying predictors of medication-related harm in older populations: a latent class analysis approach.Age and ageing · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
purposeOlder people are at an increased risk of developing adverse drug reactions (ADR) and adverse drug events (ADE). This study aimed to develop and validate a risk prediction model (ADAPTiP) for ADR/ADE in older populations.
methodsWe 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 study designed to examine the prevalence 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. The model was developed using multivariable logistic regression and was internally validated by fivefold cross-validation. The model was externally validated in a separate prospective cohort from the Centre for Primary Care Research (CPCR) study of ADES. The cross-validated and externally validated model performance was evaluated by discrimination and calibration.
resultsThe final prediction model, ADAPTiP, included nine predictors: age, chronic lung disease, the primary presenting complaints of respiratory, bleeding and gastrointestinal disorders and syncope on hospital admission and antithrombotics, diuretics, and renin-angiotensin-aldosterone system drug classes. ADAPTiP demonstrated good performance with cross-validated area under the curve of 0.75 [95% CI 0.72;79] and 0.83 [95% CI 0.80;0.87] in the external validation.
conclusionUsing accessible information from medical records, ADAPTiP can help clinicians to identify those older people at risk of an ADR/ADE who should be monitored and/or have their medications reviewed to avoid potentially harmful prescribing.
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