Drug-induced fall risk in older patients: A pharmacovigilance study of FDA adverse event reporting system database

Falls are one of the major causes of mortality and morbidity in older adults. Every year, an estimated 30-40% of patients over the age of 65 will fall at least once. Falls lead to moderate to severe injuries, fear of falling, loss of independence and death in a third of those patients. The direct costs alone from fall related injuries are a staggering 0.1% of all healthcare expenditures in the United States and up to 1.5% of healthcare costs in European countries. This figure does not include the indirect costs of loss of income both to the patient and caregiver, the intangible losses of mobility, confidence, and functional independence. Numerous studies have attempted to define the risk factors for falls in older adults. The present review provides a brief summary and update of the relevant literature, summarizing demographic and modifiable risk factors. The major risk factors identified are impaired balance and gait, polypharmacy, and history of previous falls. Other risk factors include advancing age, female gender, visual impairments, cognitive decline especially attention and executive dysfunction, and environmental factors. Recommendations for the clinician to manage falls in older patients are also summarized. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

There is increasing recognition that the use of certain medications contributes to falls in seniors. Our objective was to update a previously completed meta-analysis looking at the association of medication use and falling to include relevant drug classes and new studies that have been completed since a previous meta-analysis. Studies were identified through a systematic search of English-language articles published from 1996 to 2007. We identified studies that were completed on patients older than 60 years, looking at the association between medication use and falling. Bayesian methods allowed us to combine the results of a previous meta-analysis with new information to estimate updated Bayesian odds ratios (ORs) and 95% credible intervals (95% CrIs) Of 11 118 identified articles, 22 met our inclusion criteria. Meta-analyses were completed on 9 unique drug classes, including 79 081 participants, with the following Bayesian unadjusted OR estimates: antihypertensive agents, OR, 1.24 (95% CrI, 1.01-1.50); diuretics, OR, 1.07 (95% CrI, 1.01-1.14); beta-blockers, OR, 1.01 (95% CrI, 0.86-1.17); sedatives and hypnotics, OR, 1.47 (95% CrI, 1.35-1.62); neuroleptics and antipsychotics, OR, 1.59 (95% CrI, 1.37-1.83); antidepressants, OR, 1.68 (95% CrI, 1.47-1.91); benzodiazepines, OR, 1.57 (95% CrI, 1.43-1.72); narcotics, OR, 0.96 (95% CrI, 0.78-1.18); and nonsteroidal anti-inflammatory drugs, OR, 1.21 (95% CrI, 1.01-1.44). The updated Bayesian adjusted OR estimates for diuretics, neuroleptics and antipsychotics, antidepressants, and benzodiazepines were 0.99 (95% CrI, 0.78-1.25), 1.39 (95% CrI, 0.94-2.00), 1.36 (95% CrI, 1.13-1.76), and 1.41 (95% CrI, 1.20-1.71), respectively. Stratification of studies had little effect on Bayesian OR estimates, with only small differences in the stratified ORs observed across population (for beta-blockers and neuroleptics and antipsychotics) and study type (for sedatives and hypnotics, benzodiazepines, and narcotics). An increased likelihood of falling was estimated for the use of sedatives and hypnotics, neuroleptics and antipsychotics, antidepressants, benzodiazepines, and nonsteroidal anti-inflammatory drugs in studies considered to have "good" medication and falls ascertainment. The use of sedatives and hypnotics, antidepressants, and benzodiazepines demonstrated a significant association with falls in elderly individuals.

The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS, formerly AERS) is a database that contains information on adverse event and medication error reports submitted to the FDA. Besides those from manufacturers, reports can be submitted from health care professionals and the public. The original system was started in 1969, but since the last major revision in 1997, reporting has markedly increased. Data mining algorithms have been developed for the quantitative detection of signals from such a large database, where a signal means a statistical association between a drug and an adverse event or a drug-associated adverse event, including the proportional reporting ratio (PRR), the reporting odds ratio (ROR), the information component (IC), and the empirical Bayes geometric mean (EBGM). A survey of our previous reports suggested that the ROR provided the highest number of signals, and the EBGM the lowest. Additionally, an analysis of warfarin-, aspirin- and clopidogrel-associated adverse events suggested that all EBGM-based signals were included in the PRR-based signals, and also in the IC- or ROR-based ones, and that the PRR- and IC-based signals were in the ROR-based ones. In this article, the latest information on this area is summarized for future pharmacoepidemiological studies and/or pharmacovigilance analyses.