Systematic Review and Meta-analysis of the Pharmacokinetics of Benznidazole in the Treatment of Chagas Disease
Bibliographic record
Abstract
ABSTRACT Chagas disease is a neglected parasitic illness affecting approximately 8 million people, predominantly in Latin America. Benznidazole is the drug of choice for treatment, although its availability has been limited. A paucity of knowledge of the pharmacokinetic properties of this drug has contributed to its limited availability in several jurisdictions. The objective of this study was to conduct a systematic literature review and a Bayesian meta-analysis of pharmacokinetic studies to improve estimates of the basic pharmacokinetic properties of benznidazole. A systematic search of the Embase, Medline, LILACS, and SciELO (Scientific Electronic Library Online) databases was conducted. Eligible studies reported patient-level data from single-100-mg-dose pharmacokinetic evaluations of benznidazole in adults or otherwise provided data relevant to the estimation of pharmacokinetic parameters which could be derived from such studies. A Bayesian hierarchical model was used for analysis. Secondary data (i.e., data from studies that did not include patient-level, single-100-mg-dose data) were used for the generation of empirical priors for the Bayesian analysis. The systematic search identified nine studies for inclusion. Nine pharmacokinetic parameters were estimated, including the area under the concentration-time curve (AUC), the maximum concentration of drug in plasma ( C max ), the time to C max , the elimination rate constant ( k el ), the absorption rate constant ( K a ), the absorption and elimination half-lives, the apparent oral clearance, and the apparent oral volume of distribution. The results showed consistency across studies. AUC and C max were 51.31 mg · h/liter (95% credible interval [CrI], 45.01, 60.28 mg · h/liter) and 2.19 mg/liter (95% CrI, 2.06, 2.33 mg/liter), respectively. K a and k el were 1.16 h −1 (95% CrI, 0.59, 1.76 h −1 ) and 0.052 h −1 (95% CrI, 0.045, 0.059 h −1 ), respectively, with the corresponding absorption and elimination half-lives being 0.60 h (95% CrI, 0.38, 1.11 h) and 13.27 h (95% CrI, 11.79, 15.42 h), respectively. The oral clearance and volume of distribution were 2.04 liters/h (95% CrI, 1.77, 2.32 liters/h) and 39.19 liters (95% CrI, 36.58, 42.17 liters), respectively. A Bayesian meta-analysis was used to improve the estimates of the standard pharmacokinetic parameters of benznidazole. These data can inform clinicians and policy makers as access to this drug increases.
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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 | 0.020 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.030 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".