Incidence, risk factors and risk prediction of hospital-acquired suspected adverse drug reactions: a prospective cohort of Ugandan inpatients
Bibliographic record
Abstract
OBJECTIVES: To determine the incidence and risk factors of hospital-acquired suspected adverse drug reactions (ADRs) among Ugandan inpatients. We also constructed risk scores to predict and qualitatively assess for peculiarities between low-risk and high-risk ADR patients. METHODS: Prospective cohort of consented adults admitted on medical and gynaecological wards of the 1790-bed Mulago National Referral Hospital. Hospital-acquired suspected ADRs were dichotomised as possible (possible/probable/definite) or not and probable (probable/definite) or not, using the Naranjo scale. Risk scores were generated from coefficients of ADR risk-factor logistic regression models. RESULTS: The incidence of possible hospital-acquired suspected ADRs was 25% (194/762, 95% CI: 22% to 29%): 44% (85/194) experienced serious possible ADRs. The risk of probable ADRs was 11% (87/762, 95% CI 9% to 14%): 46% (40/87) had serious probable ADRs. Antibacterials-only (51/194), uterotonics-only (21/194), cardiovascular drugs-only (16/194), antimalarials-only (12/194) and analgesics-only (10/194) were the most frequently implicated. Treatment with six or more conventional medicines during hospitalisation (OR=2.31, 95% CI 1.29 to 4.15) and self-reported herbal medicine use during the 4 weeks preadmission (OR=1.96, 95% CI 1.22 to 3.13) were the risk factors for probable hospital-acquired ADRs. Risk factors for possible hospital-acquired ADRs were: treatment with six or more conventional medicines (OR=2.72, 95% CI 1.79 to 4.13), herbal medicine use during the 4 weeks preadmission (OR=1.68, 95% CI 1.16 to 2.43), prior 3 months hospitalisation (OR=1.57, 95% CI 1.09 to 2.26) and being on gynaecological ward (OR=2.16, 95% CI 1.36 to 3.44). More drug classes were implicated among high-risk ADR-patients, with cardiovascular drugs being the most frequently linked to possible ADRs. CONCLUSIONS: The risk of hospital-acquired suspected ADRs was higher with preadmission herbal medicine use and treatment with six or more conventional medicines during hospitalisation. Our risk scores should be validated in large-scale studies and tested in routine clinical care.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".