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Introduction <p>People with HIV are living longer, but frailty may increase vulnerability to adverse drug interactions, particularly with sedative medications.</p> Aim <p>To describe sedative co-medication patterns across frailty states using network-based analysis, and to identify key medications driving interaction complexity.</p> Method <p>This cross-sectional study analyzed 321 participants using sedatives from the Positive Brain Health Now Cohort (mean age: 53&#xa0;years), categorized as robust (30.2%), prefrail (47.0%), or frail (22.7%). Sedative use was classified using the Sedative Load Model, and frailty was assessed with a modified Fried Frailty Phenotype. Co-medication networks were constructed for robust, prefrail, and frail groups, with metrics such as Neighborhood Shift Scores (NESH) and ΔBetweenness used to evaluate network dynamics. Edge-level Observed-to-Expected ratios highlighted significant drug pairings and interaction risks.</p> Results <p>Frail individuals exhibited the most interconnected sedative network (graph density: 0.24; average degree: 7.31) followed by prefrail (graph density: 0.18; average degree: 6.67) and robust groups (graph density: 0.13; average degree: 4.61). Medications with high network influence included mirtazapine (robust-to-prefrail: NESH = 2.05; ΔBetweenness = 0.23), gabapentin (robust-to-frail: NESH = 2.46, ΔBetweenness = 0.10), and pregabalin (prefrail-to-frail: NESH = 2.55; ΔBetweenness = 0.71). High-risk sedative pairs in frail individuals included hydromorphone–clonazepam (Observed-to-Expected ratio: 3.07; interaction severity: D), amitriptyline–oxycodone (Observed-to-Expected ratio: 1.92; severity: D), and quetiapine–citalopram (Observed-to-Expected ratio: 2.12; severity: D). Prefrail individuals had intermediate-risk combinations, including clobazam–levetiracetam (Observed-to-Expected ratio: 81.5; severity: C), and gabapentin–hydroxyzine (Observed-to-Expected ratio: 3.58; severity: D). Robust individuals showed fewer and lower-risk patterns, such as amitriptyline–pregabalin (Observed-to-Expected ratio: 4.00; severity: C). Network differences reflect increasing polypharmacy and adverse interaction risks with advancing frailty.</p> Conclusion <p>Sedative co-medication patterns vary meaningfully across frailty states in people with HIV. Frailty is associated with more complex networks and a greater likelihood of high-risk drug interactions. Medications influencing these patterns can help identify opportunities for safer prescribing. The prefrail stage may offer a timely window for interventions aimed at minimizing polypharmacy and improving safety in middle-aged and older adults with HIV.</p>

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Sedative co-medication patterns across frailty states in people with HIV: a network-based study

  • 期刊论文

  • 发表日期：

    2025年7月15日

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  • Henry Ukachukwu Michael,
  • Marie-Josée Brouillette,
  • Robyn Tamblyn,
  • Lesley K. Fellows,
  • Nancy E. Mayo

摘要

Introduction

People with HIV are living longer, but frailty may increase vulnerability to adverse drug interactions, particularly with sedative medications.

Aim

To describe sedative co-medication patterns across frailty states using network-based analysis, and to identify key medications driving interaction complexity.

Method

This cross-sectional study analyzed 321 participants using sedatives from the Positive Brain Health Now Cohort (mean age: 53 years), categorized as robust (30.2%), prefrail (47.0%), or frail (22.7%). Sedative use was classified using the Sedative Load Model, and frailty was assessed with a modified Fried Frailty Phenotype. Co-medication networks were constructed for robust, prefrail, and frail groups, with metrics such as Neighborhood Shift Scores (NESH) and ΔBetweenness used to evaluate network dynamics. Edge-level Observed-to-Expected ratios highlighted significant drug pairings and interaction risks.

Results

Frail individuals exhibited the most interconnected sedative network (graph density: 0.24; average degree: 7.31) followed by prefrail (graph density: 0.18; average degree: 6.67) and robust groups (graph density: 0.13; average degree: 4.61). Medications with high network influence included mirtazapine (robust-to-prefrail: NESH = 2.05; ΔBetweenness = 0.23), gabapentin (robust-to-frail: NESH = 2.46, ΔBetweenness = 0.10), and pregabalin (prefrail-to-frail: NESH = 2.55; ΔBetweenness = 0.71). High-risk sedative pairs in frail individuals included hydromorphone–clonazepam (Observed-to-Expected ratio: 3.07; interaction severity: D), amitriptyline–oxycodone (Observed-to-Expected ratio: 1.92; severity: D), and quetiapine–citalopram (Observed-to-Expected ratio: 2.12; severity: D). Prefrail individuals had intermediate-risk combinations, including clobazam–levetiracetam (Observed-to-Expected ratio: 81.5; severity: C), and gabapentin–hydroxyzine (Observed-to-Expected ratio: 3.58; severity: D). Robust individuals showed fewer and lower-risk patterns, such as amitriptyline–pregabalin (Observed-to-Expected ratio: 4.00; severity: C). Network differences reflect increasing polypharmacy and adverse interaction risks with advancing frailty.

Conclusion

Sedative co-medication patterns vary meaningfully across frailty states in people with HIV. Frailty is associated with more complex networks and a greater likelihood of high-risk drug interactions. Medications influencing these patterns can help identify opportunities for safer prescribing. The prefrail stage may offer a timely window for interventions aimed at minimizing polypharmacy and improving safety in middle-aged and older adults with HIV.