Predictors of 1-year drug-related admissions in older multimorbid hospitalized adults.
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BORIS DOI
Date of Publication
May 2022
Publication Type
Article
Division/Institute
Contributor
Dalleur, Olivia | |
Spinewine, Anne | |
Maanen, Clara Drenth-van | |
Knol, Wilma | |
O'Mahony, Denis | |
Donzé, Jacques |
Series
Journal of the American Geriatrics Society
ISSN or ISBN (if monograph)
0002-8614
Publisher
Wiley-Blackwell
Language
English
Publisher DOI
PubMed ID
35064571
Uncontrolled Keywords
Description
BACKGROUND
Identifying patients at high risk of drug-related hospital admission (DRA) may help to efficiently target preventive interventions. We developed a score to predict DRAs in older patients with multimorbidity and polypharmacy.
METHODS
We used participants from the multicenter European OPERAM trial ("Optimising PharmacothERapy in the Mutlimorbid Elderly"). We assessed the association between easily identifiable predictors and 1-year DRAs by univariable logistic regression. Variables with p-value< 0.20 were taken forward to backward regression. We retained all variables with p < 0.05 in the model. We assessed the C-statistic, calibration (observed/predicted proportions), and overall accuracy (scaled Brier score, <0.25 indicating a useful model) of the score, and internally validated it by tenfold cross-validation.
RESULTS
Within 1 year, 435/1879 (23.2%) patients (mean age 79.4 years) had a DRA. The score included seven variables: previous hospitalizations, non-elective admission, hypertension, cirrhosis with portal hypertension, chronic kidney disease, diuretic, oral corticosteroid. The C-statistic was 0.64 (95% CI 0.61-0.67). Patients with <1 point had a 12.4% predicted and observed risk of DRA, while those with >3 points had a 40.4% predicted and 38.9% observed risk of DRA. The scaled Brier score was 0.05. Calibration showed an adequate match between predicted and observed proportions.
CONCLUSION
Comorbidities related to drug metabolism, specific medications, non-elective admission, and a history of hospitalization, were associated with a higher risk of DRA. Awareness of these associations and the score we developed may help identify patients most likely to benefit from preventive interventions.
Identifying patients at high risk of drug-related hospital admission (DRA) may help to efficiently target preventive interventions. We developed a score to predict DRAs in older patients with multimorbidity and polypharmacy.
METHODS
We used participants from the multicenter European OPERAM trial ("Optimising PharmacothERapy in the Mutlimorbid Elderly"). We assessed the association between easily identifiable predictors and 1-year DRAs by univariable logistic regression. Variables with p-value< 0.20 were taken forward to backward regression. We retained all variables with p < 0.05 in the model. We assessed the C-statistic, calibration (observed/predicted proportions), and overall accuracy (scaled Brier score, <0.25 indicating a useful model) of the score, and internally validated it by tenfold cross-validation.
RESULTS
Within 1 year, 435/1879 (23.2%) patients (mean age 79.4 years) had a DRA. The score included seven variables: previous hospitalizations, non-elective admission, hypertension, cirrhosis with portal hypertension, chronic kidney disease, diuretic, oral corticosteroid. The C-statistic was 0.64 (95% CI 0.61-0.67). Patients with <1 point had a 12.4% predicted and observed risk of DRA, while those with >3 points had a 40.4% predicted and 38.9% observed risk of DRA. The scaled Brier score was 0.05. Calibration showed an adequate match between predicted and observed proportions.
CONCLUSION
Comorbidities related to drug metabolism, specific medications, non-elective admission, and a history of hospitalization, were associated with a higher risk of DRA. Awareness of these associations and the score we developed may help identify patients most likely to benefit from preventive interventions.
File(s)
| File | File Type | Format | Size | License | Publisher/Copright statement | Content | |
|---|---|---|---|---|---|---|---|
| Aubert_JAmGeriatrSoc_2022.pdf | text | Adobe PDF | 637.47 KB | published |