Evaluation of Allplex™ GI-Parasite Assay—A Multiplex Real Time PCR for the Diagnosis of Intestinal Protozoa: A Multicentric Italian Study
Bibliographic record
Abstract
Background: The microscopic examination of stool samples remains the reference method for the diagnosis of intestinal protozoal infections; however, this technique is time consuming and requires experienced and well-trained operators. Therefore, there is a growing interest in molecular diagnostic techniques, including commercial PCR assays. The aim of this multicentric study was to evaluate a commercial real-time PCR for the detection of intestinal protozoa in fecal samples. Methods: The samples were routinely examined using conventional techniques, such as macro- and microscopic examination after concentration, Giemsa or Trichromic stain, Giardia duodenalis, Entamoeba histolytica/dispar or Cryptosporidium spp. antigens research, and amoebae culture. The samples were frozen by the participating laboratories, retrospectively extracted and examined with one-step real-time PCR multiplex using the Allplex™ GI-Parasite Assay (Seegene Inc., Seoul, Korea). Results: A total of 368 samples were analyzed from 12 Italian laboratories. Compared to traditional techniques, the sensibility and specificity of the real-time PCR kit were as follows: 100% and 100% for Entamoeba histolytica, 100% and 99.2% for Giardia duodenalis, 97.2% and 100% for Dientamoeba fragilis, and 100% and 99.7% for Cryptosporidium spp., respectively. Conclusions: The Allplex™ GI-Parasite Assay exhibited excellent performance in the detection of the most common enteric protozoa.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".