Prevalence of Cutaneous Adverse Drug Reactions in Southwest China: An 11-Year Retrospective Survey on In-patients of a Dermatology Ward
Bibliographic record
Abstract
BACKGROUND: An update of the information about the prevailing trend of cutaneous adverse drug reactions (CADRs) is important for clinicians. OBJECTIVE: The objective of the study was to survey the prevalence of CADRs in Southwest China over the past 11 years. METHODS: The clinical and laboratory data of all inpatients admitted with a diagnosis of CADRs to the dermatology ward of Southwest Hospital during the past 11 years were retrospectively investigated. RESULTS: In the 547 recruited patients, the most common clinical pattern was maculopapular eruptions (n = 277), followed by fixed drug eruptions (n = 84) and acute urticaria (n = 44). In 206 cases with single medication intake, the 3 most common culprit drugs were acetaminophen (n = 44), penicillins (n = 44), and cephalosporins (n = 30). The frequency of urticaria in the elderly (≥60 years old) (n = 117) was significantly lower than that in younger patients (<60 years old) (n = 430) (P = 0.046), whereas erythema multiforme was much more common in the elderly (P = 0.038). As compared with younger patients, allopurinol was the most common culprit drug in the elderly. CONCLUSIONS: In contrast to previous studies, our study showed that the prevalence profiles of CADRs in the elderly are quite different from those in younger population. Acetaminophen was the most common culprit drug for total CADRs, which should be alerted as an important public health problem.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".