ReviewPharmacy (Basel, Switzerland)2026
Prevalence and Association of Polypharmacy and Potentially Inappropriate Medications Among Older Adults with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis.
Review in Pharmacy (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
4 authors.
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Abstract
Older adults with type 2 diabetes mellitus (T2DM) are at high risk of polypharmacy and potentially inappropriate medication (PIM) use because of multimorbidity and complex treatment regimens. This systematic review and meta-analysis (PRISMA 2020; PROSPERO CRD420251149348) aimed to estimate the prevalence of polypharmacy and PIM use, describe PIM burden and patterns, and summarize the co-occurrence of PIMs among those with polypharmacy. On 7 September 2025, we searched PubMed, Scopus, Embase, Web of Science, and MEDLINE using a structured search strategy based on the PICO framework. Observational studies of older adults (≥65 years) with T2DM reporting polypharmacy and PIMs were included. Risk of bias was assessed using the JBI checklist, and prevalence estimates were synthesized using a random-effects meta-analysis. Five studies (13,350 participants) were included. Polypharmacy prevalence ranged from 43.6% to 95.3%, while PIM prevalence ranged from 23.4% to 74%. The co-occurrence of PIMs among polypharmacy users ranged from 39.6% to 74%. Commonly reported PIM classes included long-acting sulfonylureas, proton pump inhibitors, and benzodiazepines. Overall, polypharmacy and PIM use were frequently reported among older adults with T2DM; however, the wide variation in prevalence across studies indicates substantial clinical and methodological heterogeneity. These findings highlight the need for structured medication review and clinical context-based medication optimization beyond numerical thresholds.
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