[논문]Characterizing tramadol users with potentially inappropriate co-medications: A latent class analysis among older adults

Yang, Bo Ram; Um, Hye-Yeon; Lee, Min Taek; Kim, Myo Song; Jung, Sun-Young

doi:10.1371/journal.pone.0246426

[해외논문] Characterizing tramadol users with potentially inappropriate co-medications: A latent class analysis among older adults 원문보기

PLoS ONE, v.16 no.2, 2021년, pp.e0246426 -

Yang, Bo Ram (College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea) , Um, Hye-Yeon (Department of Statistics, Ewha Womans University, Seoul, Republic of Korea) , Lee, Min Taek (College of Pharmacy, Chung-Ang University, Seoul, Republic of Korea) , Kim, Myo Song (College of Pharmacy, Chung-Ang University, Seoul, Republic of Korea) , Jung, Sun-Young (College of Pharmacy, Chung-Ang University, Seoul, Republic of Korea)

Abstract ▼ AI-Helper

BackgroundAlthough tramadol is an effective weak opioid analgesic, careful monitoring of potential central nervous system adverse reactions in older adults is needed, especially when used with concomitant medications which may trigger the adverse effects. We aimed to characterize tramadol users with potentially inappropriate co-medications in older adults using a latent class analysis (LCA).MethodPatients aged 65 years or older using tramadol and receiving potentially inappropriate co-medications were included from a nationwide healthcare claims database. We defined antidepressants, first-generation antihistamines, and anxiolytics as potentially inappropriate co-medications. We applied an LCA for grouping tramadol users based on the common characteristics of medication use and healthcare utilization, and each patient was probabilistically assigned to a class. Patients’ characteristics in different latent classes were compared. Potential adverse drug reactions (ADRs) was defined as the any visits for emergency department after the occurrence of potentially inappropriate co-medications. Logistic regression analysis was used to examine the association between latent classes and potential ADRs.ResultsWe identified four distinct latent classes of tramadol users representing different patterns of co-medications: multiple potential drug-drug interaction (pDDI) combination users, antihistamines-tramadol users, antidepressants-tramadol users, and anxiolytics-tramadol users. Multiple pDDI combination users showed high proportion of regular tramadol use, tended to visit more medical institutions, and had a high Charlson comorbidity score. The duration of use of potentially inappropriate co-medications with tramadol was the longest in multiple pDDI combination users and the shortest in antihistamines-tramadol users.When compared with antihistamines-tramadol users, increased potential ADR risk was observed in multiple pDDI combination users (adjusted odds ratio (OR), 1.81; 95% confidence interval (CI), 1.75–1.88), antidepressants-tramadol users (1.24; 1.19–1.29), and anxiolytics-tramadol users (1.04; 1.00–1.08).ConclusionsFour distinct classes were identified among older adults using tramadol and potentially inappropriate co-medications. Differences in potential ADR risk were observed between these classes. These findings may help to identify patients at a high risk for ADRs owing to potentially inappropriate co-medications with tramadol.

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