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Categorization and association analysis of risk factors for adverse drug events

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European Journal of Clinical Pharmacology Aims and scope Submit manuscript

Abstract

Purpose

Adverse drug events (ADE) are among the leading causes of morbidity and hospitalization. This review analyzes risk factors for ADE, particularly their categorizations and association patterns, the prevalence, severity, and preventability of ADE, and method characteristics of reviewed studies.

Methods

Literature search was conducted via PubMed, Science Direct, CINAHL, and MEDLINE. A review was conducted of research articles that reported original data about specific risk factors for ADE since 2000. Data analyses were performed using Excel and R.

Results

We summarized 211 risk factors for ADE, and grouped them into five main categories: patient-, disease-, medication-, health service-, and genetics-related. Among them, medication- and disease-related risk factors were most frequently studied. We further classified risk factors within each main category into subtypes. Among them, polypharmacy, age, gender, central nervous system agents, comorbidity, service utilization, inappropriate use/change use of drugs, cardiovascular agents, and anti-infectives were most studied subtypes. An association analysis of risk factors uncovered many interesting patterns. The median prevalence, preventability, and severity rate of reported ADE was 19.5% (0.29%~86.2%), 36.2% (2.63%~91%), and 16% (0.01%~47.4%), respectively.

Conclusions

This review introduced new categories and subtypes of risk factors for ADE. The broad and in-depth coverage of risk factors and their association patterns elucidate the complexity of risk factor analysis. Managing risk factors for ADE is crucial for improving patient safety, particularly for the elderly, comorbid, and polypharmacy patients. Some under-explored risk factors such as genetics, mental health and wellness, education, lifestyle, and physical environment invite future research.

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Acknowledgements

The authors would like to thank one reviewer for her assistance in annotating a subset of research articles. The authors would also like to thank another reviewer who provided consultation for several subtypes of risk factors.

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    Lina Zhou & Anamika Paul Rupa

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LZ: data annotation and categorization; idea conceiving and study design; analysis and interpretation of the data; and preparation, review, revisions, and approval of the manuscript. AR: collection, management, annotation, analysis, and interpretation of the data; and preparation, revisions, and approval of the manuscript.

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Zhou, L., Rupa, A.P. Categorization and association analysis of risk factors for adverse drug events. Eur J Clin Pharmacol 74, 389–404 (2018). https://doi.org/10.1007/s00228-017-2373-5

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