Risk factors for adverse drug reactions in older inpatients of geriatric wards at admission: Multicenter study
Why this work is in the frame
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Bibliographic record
Abstract
AIM: To investigate the characteristics of adverse drug reactions (ADR) and their risk factors among very old patients in five geriatric wards in Japan. METHODS: A retrospective observational multicenter study was carried out to investigate factors related to ADR in older inpatients from geriatric wards of five university hospitals in Japan. Data including drugs profile and short-form comprehensive geriatric assessment were obtained from medical charts. ADR were identified from geriatrician's reports. For each ADR, symptoms and causal drugs were clarified, and factors associated with ADR were analyzed statistically. RESULTS: In 1155 patients (52.5% women, mean age 82.8 ± 7.0 years), the proportion with ADR was 15.4%. There was a great variety of signs and symptoms of ADR, and a great variety of drugs suspected to be the cause of ADR. On multiple logistic regression analysis, ADR was significantly associated with an increase in drugs (odds ratio 1.11, 95% CI 1.07-1.16) and emergency admission (odds ratio 2.76, 95% CI 1.82-4.15). Receiver operating characteristic curve analysis showed that the optimal cut-off number of drugs for predicting ADR was ≥7. CONCLUSIONS: In geriatric inpatients, polypharmacy (especially ≥7 drugs) and emergency admission were associated with ADR. Because there was a great variety of ADR in the study, clinicians must consider reviewing all drugs to prevent adverse drugs reactions during admission in this vulnerable population. Geriatr Gerontol Int 2019; ••: ••-••. Geriatr Gerontol Int 2020; 20: 144-149.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it