Adverse events associated with benznidazole treatment for Chagas disease in children and adults
Bibliographic record
Abstract
AIM: Chagas disease (ChD) is a neglected disease affecting approximately 7 million individuals in Latin America. Benznidazole (BZ) is the most commonly used treatment. Therefore, understanding the adverse effects of BZ is crucial for devising targeted monitoring and interventions to enhance patient management. METHODS: A retrospective cohort study of patients with ChD treated with BZ to identify and characterize BZ adverse drug reactions (ADRs). RESULTS: 518 patients were enrolled: 449 children (median age: 4yrs, range 1mo-17.75yrs) and 69 adults (median age: 25yrs, range 18-59). A 75% of pediatric patients received a median dose of BZ of 6.6 mg/kg/day (IQR25–75 = 5.7-7.3) for at least 60 days. Adult patients received a median BZ dose of 5.6 mg/kg/day (IQR25–75 = 5.2-6.1) for a median duration of 31 days (IQR25–75 = 30-60). Overall, 152/518 (29.34%) patients developed BZ-related ADRs, with an incidence of 116/449 (25.83%) in children and 36/69 (52.17%) in adults (OR = 0.32, CI95 = 0.19 to 0.54, p < 0.001). The study identified 240 ADRs, primarily mild to moderate, but severe ADRs occurred in 1.11% of children and 1.45% of adults. The skin was the most affected system in both groups. A 10.23% of patients abandoned treatment (53/518). Adults discontinued treatment more frequently than children (OR = 3.36 CI95 = 1.7 to 6.4, p < 0.001). CONCLUSION: Our study supports the safety of BZ for ChD in children and adults. Avoiding BZ treatment due to safety concerns does not seem to be supported by the evidence.
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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 | 0.004 |
| 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 | 0.001 |
| 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 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".