Mini-FLOTAC, Kato-Katz and McMaster: three methods, one goal; highlights from north Argentina
Bibliographic record
Abstract
BACKGROUND: Copro-parasitological diagnosis is still a challenge in management of helminth infections at individual and community levels in resource-limited settings.The aim of our study was to compare the performance of three quantitative techniques: Kato-Katz, McMaster and Mini-FLOTAC methids. The study was carried out in Oran, Northern Argentina. METHODS: 200 schoolchildren were enrolled to provide a single stool sample, which was tested for helminth infections with Kato-Katz, McMaster and Mini-FLOTAC methods. The Mini-FLOTAC was performed with two flotation solutions (FS2 saturated saline and FS7 zinc sulphate). Preparation and reading time for each of the three methods was calculated both when processing single and multiple samples. RESULTS: Out of 193 schoolchildren examined, 40% were positive for any helminth infection by any method; the most prevalent was Hymenolepis nana (23%) followed by Ascaris lumbricoides (17%) and a third group of less prevalent helminths: Enterobius vermicularis, Trichuris trichiura and hookworms (11% all together). Mini-FLOTAC FS2 was more sensitive than FS7 for H. nana (93% vs 78%) and for other helminths (85% vs 80%), whereas FS7 was more sensitive for A. lumbricoides (87% vs 61%). Kato-Katz method was more sensitive than McMaster method for A. lumbricoides (84% vs 48%) and for other helminths (48% vs 43%) except for H. nana (49% vs 61%). As for egg counts, Mini-FLOTAC FS2 reported 904 eggs per gram of faeces (EPG) for H. nana (vs 457 with McMaster and 111 with Kato-Katz) and 1177 EPG for A. lumbricoides (vs 1315 with Kato-Katz and 995 with McMaster); FS2 detected the highest EPG for both H.nana and A.lumbricoides (904 vs 568 and 1177 vs 643 respectively), the differences were not statistically significant. The technique feasibility was calculated: Kato-Katz mean time was 48 minutes/sample, Mini-FLOTAC 13 minutes/sample and McMaster 7 minutes/sample. However, especially for Kato-Katz and Mini-FLOTAC, the mean time (min/sample) decreased significantly when processing multiple samples. CONCLUSIONS: Mini-FLOTAC is a promising technique for helminth diagnosis, it is more sensitive than Kato-Katz and McMaster for H. nana and as sensitive as Kato-Katz and more sensitive than McMaster for A. lumbricoides identification. Egg counts differences although relevant, did not reach statistical significance.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".