A comparison of the diagnostic capability of Kato-Katz and real-time PCR for the assessment of treatment efficacy of ivermectin and albendazole combination against T. trichiura infections
Bibliographic record
Abstract
BACKGROUND: Trichuris trichiura is humans' second most prevalent soil-transmitted helminth (STH) infection after Ascaris lumbricoides, affecting approximately 460 million people worldwide. Despite its sub-optimal sensitivity, especially in low prevalence and infection intensity settings, the modified Kato-Katz (K-K) is still recommended as a diagnostic method by the World Health organization (WHO) guidelines. METHODOLOGY/PRINCIPAL FINDINGS: Within a randomized clinical trial (RCT) comprising four treatment arms with two different anthelmintics, the present study reports an important secondary research objective to determine the diagnostic agreement between K-K and real-time PCR evaluating treatment efficacy against T. trichiura. The parasitological results were analyzed, including cure rates (CR) of a subgroup of 94 participants positive at baseline for T. trichiura eggs for both techniques. The single-dose albendazole (ALB) arm resulted in significantly lower CRs than experimental arms of albendazole/ivermectin (ALB/IVM) combinations. The overall diagnostic agreement between both techniques was 88.7% [κ = 0.8 (P<0.001)]. Concordance between eggs per gram and Ct values was moderate, with the discordance source likely stemming from lighter infection intensities. CONCLUSIONS AND SIGNIFICANCE: These findings indicate that real-time PCR is a suitable alternative for CR estimation in helminthiasis clinical trials. It also highlights the need to identify the most accurate diagnostic tools for RCTs, that would benefit from guiding principles to achieve harmonization across studies and are not necessarily the same as those used for epidemiological surveys. TRIAL REGISTRATION: Clinical Trials.gov (NCT04041453).
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".