Adverse Events Associated with High‐Dose Ribavirin: Evidence from the Toronto Outbreak of Severe Acute Respiratory Syndrome
Bibliographic record
Abstract
STUDY OBJECTIVES: To distinguish adverse events related to ribavirin therapy from those attributable to severe acute respiratory syndrome (SARS), and to determine the rate of potential ribavirin-related adverse events. DESIGN: Retrospective cohort study. SETTING: Hospitals in Toronto, Ontario, Canada. PATIENTS: A cohort of 306 patients with confirmed or probable SARS, 183 of whom received ribavirin and 123 of whom did not, between February 23, 2003, and July 1, 2003. Of the 183 treated patients, 155 (85%) received very high-dose ribavirin; the other 28 treated patients received lower-dose regimens. MEASUREMENTS AND MAIN RESULTS: Data on all patients with SARS admitted to hospitals in Toronto were abstracted from charts and electronic databases onto a standardized form by trained research nurses. Logistic regression was used to evaluate the association between ribavirin use and each adverse event (progressive anemia, hypomagnesemia, hypocalcemia, bradycardia, transaminitis, and hyperamylasemia) after adjusting for SARS-related prognostic factors and corticosteroid use. In the primary logistic regression analysis, ribavirin use was strongly associated with anemia (odds ratio [OR] 3.0, 99% confidence interval [CI] 1.5-6.1, p<0.0001), hypomagnesemia (OR 21, 99% CI 5.8-73, p<0.0001), and bradycardia (OR 2.3, 99% CI 1.0-5.1, p=0.007). Hypocalcemia, transaminitis, and hyperamylasemia were not associated with ribavirin use. The risk of anemia, hypomagnesemia, and bradycardia attributable to ribavirin use was 27%, 45%, and 17%, respectively. CONCLUSIONS: High-dose ribavirin is associated with a high rate of adverse events. The use of high-dose ribavirin is appropriate only for the treatment of infectious diseases for which ribavirin has proven clinical efficacy, or in the context of a clinical trial. Ribavirin should not be used empirically for the treatment of viral syndromes of unknown origin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".