Abstract
BackgroundOlder patients are at an increased risk of developing adverse drug reactions (ADR). Of particular concern are the oldest old, which constitute an increasingly growing population. Having a validated clinical tool to identify those older patients at risk of developing an ADR during hospital stay would enable healthcare staff to put measures in place to reduce the risk of such an event developing. The current study aimed to (1) develop and (2) validate an ADR risk prediction model.MethodsWe used a combination of univariate analysis and multivariate binary logistic regression to identify clinical risk factors for developing an ADR in a population of older people from a UK teaching hospital. The final ADR risk model was then validated in a European population (European dataset).ResultsSix-hundred-ninety patients (median age 85 years) were enrolled in the development stage of the study. Ninety-five reports of ADR were confirmed by independent review in these patients. Five clinical variables were identified through multivariate analysis and included in our final model; each variable was attributed a score of 1. Internal validation produced an AUROC of 0.74, a sensitivity of 80%, and specificity of 55%. During the external validation stage the AUROC was 0.73, with sensitivity and specificity values of 84% and 43% respectively.ConclusionsWe have developed and successfully validated a simple model to use ADR risk score in a population of patients with a median age of 85, i.e. the oldest old. The model is based on 5 clinical variables (≥8 drugs, hyperlipidaemia, raised white cell count, use of anti-diabetic agents, length of stay ≥12 days), some of which have not been previously reported.
Highlights
Over the 50 years, many societies throughout the world are set to face an ‘ageing population’, with its associated burden of disease and disability
Patient recruitment was further hindered by an outbreak of Norovirus and Clostridium difficile infection on two of the study wards which restricted access to patients on the grounds of infection control
The model was found to have an AUROC of 0.74, suggesting that the ability of the Brighton Adverse Drug Reactions Risk (BADRI) model to predict adverse drug reactions (ADR) is better than chance alone (0.5)
Summary
Over the 50 years, many societies throughout the world are set to face an ‘ageing population’, with its associated burden of disease and disability. In the US, the proportion of the population aged 65 years or over in 1998 was 13% [1]. By 2012 that proportion had risen to 15%, and is projected to rise to 22% by the year 2060 [2]. The oldest old (those aged 85 or over) will see a considerable rise in the size of their population, which is set to increase from 6 million in 2012 to 18 million in 2060 (an increase of just under 200%). The oldest old (.85 years) will see the largest relative rise in their population of over 5 times between the years 1985 and 2035 [3]. Older patients are at an increased risk of developing adverse drug reactions (ADR). The current study aimed to (1) develop and (2) validate an ADR risk prediction model
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