ArticleSAGE open medicine2017
Medication use and falls: Applying Beers criteria to medication review in Parkinson's disease.
Article in SAGE open medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Polypharmacy and Hyperpolypharmacy in Older Individuals with Parkinson's Disease: A Systematic Review and Meta-Analysis.Gerontology · 2022Pooled it
- Acupuncture-Related Therapies as a Potential Adjuvant Option for Parkinson's Disease: Effects on Symptom Management, Medication Use, and Mortality.Parkinson's disease · 2026Article
- Proof of Concept in Artificial-Intelligence-Based Wearable Gait Monitoring for Parkinson's Disease Management Optimization.Biosensors · 2022Article
- Characterization of potentially inappropriate medications use in Indian elderly population and their impact on quality of life using Beers criteria.Aging medicine (Milton (N.S.W)) · 2022Article
- American Geriatrics Society-Beers Criteria and adverse drug reactions: a comparative cross-sectional study of Nigerian and South African older inpatients.Clinical interventions in aging · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesOur goal was to assess the association between potentially inappropriate medication use and risk of falls in the Parkinson's disease population.
methodsThis was a retrospective cohort study conducted at an outpatient Parkinson's Disease Treatment Center. Individuals 65 years of age or older, diagnosed with Parkinson's disease who attended at least three visits in 2015 for physical, occupational therapy, or physician's visits were included in the study. Electronic medical records were utilized to perform chart reviews, and medications were analyzed to identify prescription medications, combination preparations, over-the-counter medications, and dietary supplements. The goal of this study was to test the following hypothesis: elderly individuals with Parkinson's disease who take multiple potentially inappropriate medications are more likely to experience a fall compared to elderly individuals with Parkinson's disease who do not take multiple potentially inappropriate medications.
resultsA higher mean number of prescription medications were associated with falls in elderly Parkinson's disease patients (6.53 vs 5.21, p < 0.01). Polypharmacy (taking five or more prescription and nonprescription medications) was not significantly associated with falls. Patients taking potentially inappropriate medications specifically contraindicated for those with a history of falls and fractures were more likely to report falls (p < 0.04). Analysis of the specific therapeutic medication categories demonstrated no significant differences between those who did and did not report falls.
conclusionA future prospective study at Parkinson's disease center should include an electronic medical record-based intervention to reduce the total number of medications, as well as to minimize the use of high-risk medications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.