Comparison of the FXG™: RESP (Asp+) real-time PCR assay with direct immunofluorescence and calcofluor white staining for the detection of<i>Pneumocystis jirovecii</i>in respiratory specimens
Bibliographic record
Abstract
We compared the FXG™: RESP (Asp +) real-time PCR assay (Myconostica Ltd) with two microscopic staining methods (direct immunofluorescence [IFA] and calcofluor white) for the detection of Pneumocystis jirovecii in 411 respiratory specimens submitted for P. jirovecii examination. We considered the specimen to be microscopically positive if the organism could be visualized through the use of either IFA or calcofluor white. A second, published real-time PCR assay targeting the cdc2 gene of P. jirovecii was used to adjudicate those specimens that were microscopically negative but Myconostica PCR positive. The Myconostica PCR positive samples were deemed to be true positives if they were concordant with microscopically positive results or if they were positive by the second PCR assay. As a result, the Myconostica PCR assay was found to be more sensitive than the two microscopy methods in detecting P. jirovecii (10.5% true positivity rate by PCR, 8.0% by immunofluorescence, and 7.1% by calcofluor white). The Myconostica PCR assay showed 93.5% sensitivity, 95.1% specificity, 70.5% positive predictive value, and 99.1% negative predictive value. Its high negative predictive value suggests a role of the Myconostica PCR assay in ruling out Pneumocystis pneumonia.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".