Adverse events associated with benznidazole treatment for Chagas disease in children and adults
Bibliographic record
Abstract
AIMS: Chagas disease (ChD) affects approximately 7 million people in Latin America, with benznidazole being the most commonly used treatment. METHODS: Data from a retrospective cohort study in Argentina, covering January 1980 to July 2019, was reanalysed to identify and characterize benznidazole-related adverse drug reactions (ADRs). RESULTS: The study included 518 patients: 449 children and 69 adults (median age in children: 4 years; adults: 25 years; age ranges: 1 month-17.75 years and 18-59 years, respectively). The median benznidazole doses received were 6.6 mg/kg/day for at least 60 days in children and 5.6 mg/kg/day for a median of 31 days in adults. Overall, 29.34% (152/518) of patients developed benznidazole-related ADRs, with an incidence of 25.83% (116/449) in children and 52.17% (36/69) in adults (odds ratio [OR] = 0.32, 95% confidence interval [CI] = 0.19-0.54, P < .001). The incidence rate was 177 cases per 1000 person-years (95% CI = 145-214) in children and 537 per 1000 person-years (95% CI = 360-771) in adults. There were 240 ADRs identified, primarily mild to moderate. Severe ADRs occurred in 1.11% (5/449) of children and 1.45% (1/69) of adults. The skin was the most affected system. A total of 10.23% (53/518) of patients discontinued treatment. More adults than children discontinued treatment (OR = 3.36, 95% CI = 1.7-6.4, P < .001). CONCLUSIONS: Although 29.34% of patients experienced ADRs, most were mild to moderate, indicating a manageable safety profile for benznidazole. While optimized dosing schedules and new drugs are needed, avoiding benznidazole solely due to safety concerns is not justified.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".