BACKGROUND: The aim of this study was to use a signal detection method to examine the prevalence of, and patient characteristics associated with, medication with potential to impair cognition and cholinesterase inhibitor use in patients with Alzheimer's disease. METHODS: A cross-sectional study was conducted of 1,954 patients with a diagnosis of probable or possible Alzheimer's disease. Concurrent medications were measured, specifically: (1) a medication with potential to impair cognition or (2) a cholinesterase inhibitor. Predictor variables included age, gender, ethnic group, education, age of symptom onset, number of prescriptions, number of medical diagnoses, Mini-Mental State Examination (MMSE), Blessed-Roth Dementia Rating Scale (BRDRS), probable versus possible AD diagnosis. RESULTS: Fifteen percent of the Alzheimer's disease patients were on a medication with potential to impair cognition, and 44% were on a cholinesterase inhibitor. Patient characteristics associated with the prescription of a medication with potential to impair cognition included total number of prescription medications, low education, low MMSE, older age, reported lack of vitamin use, and more medical diagnoses. Patient characteristics associated with the prescription of a cholinesterase inhibitor included reported use of vitamins, the total number of prescription medications, fewer medical diagnoses, lower age of symptom onset, and higher education. CONCLUSIONS: Determining the patient characteristics associated with the prescription of a medication with potential to impair cognition can help clinicians identify patients who are at risk for drug-related morbidity. Patient characteristics unassociated with dementia appear to influence the prescription of cholinesterase inhibitors. Signal detection analysis is well suited to this type of research.
BACKGROUND: The aim of this study was to use a signal detection method to examine the prevalence of, and patient characteristics associated with, medication with potential to impair cognition and cholinesterase inhibitor use in patients with Alzheimer's disease. METHODS: A cross-sectional study was conducted of 1,954 patients with a diagnosis of probable or possible Alzheimer's disease. Concurrent medications were measured, specifically: (1) a medication with potential to impair cognition or (2) a cholinesterase inhibitor. Predictor variables included age, gender, ethnic group, education, age of symptom onset, number of prescriptions, number of medical diagnoses, Mini-Mental State Examination (MMSE), Blessed-Roth Dementia Rating Scale (BRDRS), probable versus possible AD diagnosis. RESULTS: Fifteen percent of the Alzheimer's diseasepatients were on a medication with potential to impair cognition, and 44% were on a cholinesterase inhibitor. Patient characteristics associated with the prescription of a medication with potential to impair cognition included total number of prescription medications, low education, low MMSE, older age, reported lack of vitamin use, and more medical diagnoses. Patient characteristics associated with the prescription of a cholinesterase inhibitor included reported use of vitamins, the total number of prescription medications, fewer medical diagnoses, lower age of symptom onset, and higher education. CONCLUSIONS: Determining the patient characteristics associated with the prescription of a medication with potential to impair cognition can help clinicians identify patients who are at risk for drug-related morbidity. Patient characteristics unassociated with dementia appear to influence the prescription of cholinesterase inhibitors. Signal detection analysis is well suited to this type of research.
Authors: M H Beers; J G Ouslander; S F Fingold; H Morgenstern; D B Reuben; W Rogers; M J Zeffren; J C Beck Journal: Ann Intern Med Date: 1992-10-15 Impact factor: 25.391
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