Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

A Machine Learning Approach to Identify Predictors of Potentially Inappropriate Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Use in Older Adults with Osteoarthritis

Bibliographic Data

ID15464621
AuthorsJayeshkumar Patel (0000-0001-7507-8054, West Virginia University, corresponding author), Amit Ladani (0000-0003-0294-2280, West Virginia University), Nethra Sambamoorthi (Northwestern University), Traci LeMasters (0000-0002-6998-2650, West Virginia University), Nilanjana Dwibedi (0000-0003-3724-8651, West Virginia University), Usha Sambamoorthi (0000-0001-8311-1360, West Virginia University)
Year2020
Volume18
Issue1
Pages155-155
Publication date2020-12-28
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph18010155
PMID33379288
OpenAlexW3118192269
LanguageEN
Citations received1
References cited37

Evidence from some studies suggest that osteoarthritis (OA) patients are often prescribed non-steroidal anti-inflammatory drugs (NSAIDs) that are not in accordance with their cardiovascular (CV) or gastrointestinal (GI) risk profiles. However, no such study has been carried out in the United States. Therefore, we sought to examine the prevalence and predictors of potentially inappropriate NSAIDs use in older adults (age > 65) with OA using machine learning with real-world data from Optum De-identified Clinformatics ® Data Mart. We identified a retrospective cohort of eligible individuals using data from 2015 (baseline) and 2016 (follow-up). Potentially inappropriate NSAIDs use was identified using the type (COX-2 selective vs. non-selective) and length of NSAIDs use and an individual's CV and GI risk. Predictors of potentially inappropriate NSAIDs use were identified using eXtreme Gradient Boosting. Our study cohort comprised of 44,990 individuals (mean age 75.9 years). We found that 12.8% individuals had potentially inappropriate NSAIDs use, but the rate was disproportionately higher (44.5%) in individuals at low CV/high GI risk. Longer duration of NSAIDs use during baseline (AOR 1.02; 95% CI:1.02-1.02 for both non-selective and selective NSAIDs) was associated with a higher risk of potentially inappropriate NSAIDs use. Additionally, individuals with low CV/high GI (AOR 1.34; 95% CI:1.20-1.50) and high CV/low GI risk (AOR 1.61; 95% CI:1.34-1.93) were also more likely to have potentially inappropriate NSAIDs use. Heightened surveillance of older adults with OA requiring NSAIDs is warranted

Alternative medicine · Cohort · Cohort study · Osteoarthritis · Pharmacoepidemiology · Proportional hazards model · Retrospective cohort study · Antiplatelet Therapy and Cardiovascular Diseases · Inflammatory mediators and NSAID effects · Medicine · Osteoarthritis Treatment and Mechanisms · Internal Medicine · Pharmacology

  • Analgesic Effectiveness of Physical Therapy Combining the Use of Electromagnetic Fields with Light Radiation Emitted by LEDs along with the Use of Topical Herbal Ointment in Patients with Gonarthrosis

    Open Access•Katarzyna Janczewska, Kamil Koszela et al.•International Journal of…•2023

  • American Geriatrics Society 2019 Updated AGS Beers Criteria® for Potentially Inappropriate Medication Use in Older Adults

    Open Access•By the American Geriatrics Society Beers Criteria® Update Expert Panel•Journal of the American…•2019

Citations per year0.33
Citation span2023 - 2023 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae