Molecular prevalence of <i>Entamoeba histolytica/dispar</i> infection among patients attending four health centres in north-west Ethiopia
Bibliographic record
Abstract
The prevalence of amoebiasis is often overestimated owing to its epidemiological overlap with the non-pathogenic Entamoeba dispar To provide evidence for this conjecture, a cross-sectional study was conducted from November 2013 to January 2015. A range of 180-200 µg of semi-solid and formed stools and 200 µL of diarrhoeic stool samples were used for DNA extraction from microscopically E. histolytica/dispar positive samples using the QIAamp® DNA Stool Mini Kit according to manufacturers' instructions. Nested PCR targeting 18S ribosomal RNA gene was used. In 422 microscopically positive E. histolytica/dispar stools, molecular prevalence revealed that E. histolytica infestation was present in only 1.7% (95% confidence interval [CI], 0.47-2.93) and E. dispar was found in 42.2% (95% CI, 37.49-46.91), while 56.2% (95% CI, 51.47-60.93) had neither E. histolytica nor E. dispar (P < 0.001). We conclude that infestation with E. histolytica is rarer in our study areas than was previously believed. Hence, accurate differentiation of E. histolytica and E. dispar is crucial.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".