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Drug-related hospital admissions in older adults: comparison of the Naranjo algorithm and an adjusted version of the Kramer algorithm

  • Mertens, Beatrijs; 150369;
  • Hias, Julie;
  • Hellemans, Laura;
  • Walgraeve, Karolien;
  • Spriet, Isabel; 44833;
  • Tournoy, Jos; 34369;
  • Van der Linden, Lorenz Roger; 60507;
Publication Date
Mar 21, 2022
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PURPOSE: Drug-related admissions (DRAs) are an important cause of preventable harm in older adults. Multiple algorithms exist to assess causality of adverse drug reactions, including the Naranjo algorithm and an adjusted version of the Kramer algorithm. The performance of these tools in assessing DRA causality has not been robustly shown. This study aimed to evaluate the ability of the adjusted Kramer algorithm to adjudicate DRA causality in geriatric inpatients. METHODS: DRAs were assessed in a convenience sample of patients admitted to the acute geriatric wards of an academic hospital. DRAs were identified by expert consensus and causality was evaluated using the Naranjo and the adjusted Kramer algorithms. Positive agreement with expert consensus was calculated for both algorithms. A multivariable logistic regression analysis was performed to explore determinants for a DRA. RESULTS: A total of 218 geriatric inpatients was included of whom 65 (29.8%) experienced a DRA. Positive agreement was 72.3% (95% confidence interval (CI), 59.6-82.3%) and 100% (95% CI, 93.0-100%) for the Naranjo and the adjusted Kramer algorithm, respectively. Diuretics were the main culprits and most DRAs were attributed to a fall (n = 18; 27.7%). A fall-related principal diagnosis was independently associated with a DRA (odds ratio 20.11; 95% CI, 5.60-72.24). CONCLUSION: The adjusted Kramer algorithm demonstrated a higher positive agreement with expert consensus in assessing DRA causality in geriatric inpatients compared to the Naranjo algorithm. Our results further support implementation of the adjusted Kramer algorithm as part of a standardized DRA assessment in older adults. / status: published

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