ObjectivesTo compare the effect of using different anticholinergic drug scales and different models of cognitive decline in longitudinal studies.DesignLongitudinal cohort study.SettingOutpatient clinics, Quebec, Canada.ParticipantsIndividuals aged 60 and older without dementia or depression (n = 102).MeasurementsUsing baseline and 1-year follow-up data, four measures of anticholinergic burden (anticholinergic component of the Drug Burden Index (DBI-Ach), Anticholinergic Cognitive Burden (ACB), Anticholinergic Drug Scale (ADS), and Anticholinergic Risk Scale (ARS)) were applied. Three models of cognitive decline (worsening of raw neuropsychological test scores, Reliable Change Index (RCI), and a standardized regression based measure (SRB)) were compared in relation to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria for the onset of a new mild neurocognitive disorder. The consistency of associations was examined using logistic regression.ResultsThe frequency of identifying individuals with an increase in anticholinergic burden over 1 year varied from 18% with the DBI-Ach to 23% with the ACB. The frequency of identifying cognitive decline ranged from 8% to 86% using different models. The raw change score had the highest sensitivity (0.91), and the RCI the highest specificity (0.93) against DSM-V criteria. Memory decline using the SRB method was associated with an increase in ACB (odds ratio (OR) = 5.3, 95% confidence interval (CI) = 1.1–25.8), ADS (OR = 5.7, 95% CI = 1.1–27.7), and ARS (OR = 6.5, 95% CI = 1.34–32.3). An increase in the DBI-Ach was associated with a decline on memory testing using the raw change score method (OR = 4.2, 95% CI = 1.8–15.4) and on the Trail-Making Test Part B using SRB (OR = 2.9, 95% CI = 1.1–8.0). No associations were observed using the DSM-V criteria or RCI method.ConclusionThe choice of different methods for defining drug exposure and cognitive decline will have a significant effect on the results of pharmacoepidemiological studies.
BackgroundSeveral medication classes may contribute to urinary symptoms in older adults. The purpose of this study was to determine the prevalence of use of these medications in a clinical cohort of incontinent patients.MethodsA cross-sectional study was conducted among 390 new patients aged 60 years and older seeking care for incontinence in specialized outpatient geriatric incontinence clinics in Quebec, Canada. The use of oral estrogens, alpha-blocking agents, benzodiazepines, antidepressants, antipsychotics, ACE inhibitors, loop diuretics, NSAIDs, narcotics and calcium channel blockers was recorded from each patient’s medication profile. Lower urinary tract symptoms and the severity of incontinence were measured using standardized questionnaires including the International Consultation on Incontinence Questionnaire. The type of incontinence was determined clinically by a physician specialized in incontinence. Co-morbidities were ascertained by self-report. Logistic regression analyses were used to detect factors associated with medication use, as well as relationships between specific medication classes and the type and severity of urinary symptoms.ResultsThe prevalence of medications potentially contributing to lower urinary tract symptoms was 60.5%. Calcium channel blockers (21.8%), benzodiazepines (17.4%), other centrally active agents (16.4%), ACE inhibitors (14.4%) and estrogens (12.8%) were most frequently consumed. Only polypharmacy (OR = 4.9, 95% CI = 3.1-7.9), was associated with medication use contributing to incontinence in analyses adjusted for age, sex, and multimorbidity. No associations were detected between specific medication classes and the type or severity of urinary symptoms in this cohort.ConclusionThe prevalence of use of medications potentially causing urinary symptoms is high among incontinent older adults. More research is needed to determine whether de-prescribing these medications results in improved urinary symptoms.
*Background: In view of the multiple co-morbidities, the elderly patients receiving drugs are prone to suffer with drug interactions since they receive a greater number of drugs. Objective: The study was undertaken to determine the prevalence of drug interactions, as well as their predictors. Method: The prescriptions of a total of 1510 inpatients were collected prospectively for 1.5 years from inpatients wards of public tertiary care teaching hospital. All the prescriptions were checked for drug interactions using the Micromedex® Drug-Reax database-2010 and Stockley's Drug Interactions. Regression analyses sought to determine predictors for the drug interaction. Results: The patients, with the average age of 67.2 ±0.2 years, were prescribed an average of 9.15 ±0.03 medications. It was found that out of 1510 prescriptions of inpatients, 126 (8.3%) prescriptions had one or more than one drug interaction. All the identified interactions were severe in nature. The top most interacting drugs were acetylsalicylic acid and anticoagulant (n=59). The second top most interacting drug combination was clopidogrel and proton pump inhibitors (n=51). The most commonly involved drugs in interactions were C (cardiovascular system) and A (alimentary tract and metabolism). Using multivariate binary logistic regression, multiple drugs (Odds Ratio=4.5; 95% Confidence Interval: -2.38 -9.47) and multiple diagnoses (Odds Ratio=2.6; were found to be significant predictors for drug interaction.
Conclusion:The results of this study substantiate the occurrence of severe drug interactions among Indian elderly inpatients. In order to provide safer pharmaceutical care, the active involvement of clinical pharmacists is a potential option.
The findings of this study provide evidence that provision of unbiased evidenced based information is the best possible means for improvement of pharmacotherapy in older patients.
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