Development and Validation of a <i>Pneumocystis jirovecii</i> Real‐time Polymerase Chain Reaction Assay for Diagnosis of <i>Pneumocystis</i> Pneumonia
Bibliographic record
Abstract
BACKGROUND: Pneumocystis jirovecii (PJ), a pathogenic fungus, causes severe interstitial Pneumocystis pneumonia (PCP) among immunocompromised patients. A laboratory-developed real-time polyermase chain reaction (PCR) assay was validated for PJ detection to improve diagnosis of PCP. METHODS: Forty stored bronchoalveolar lavage (BAL) samples (20 known PJ positive [PJ+] and 20 known PJ negative [PJ-]) were initially tested using the molecular assay. Ninety-two sequentially collected BAL samples were then analyzed using an immunofluorescence assay (IFA) and secondarily tested using the PJ real-time PCR assay. Discrepant results were resolved by retesting BAL samples using another real-time PCR assay with a different target. PJ real-time PCR assay performance was compared with the existing gold standard (ie, IFA) and a modified gold standard, in which a true positive was defined as a sample that tested positive in two of three methods in a patient suspected to have PCP. RESULTS: Ninety of 132 (68%) BAL fluid samples were collected from immunocompromised patients. Thirteen of 92 (14%) BALs collected were PJ+ when tested using IFA. A total of 40 BAL samples were PJ+ in the present study including: all IFA positive samples (n=13); all referred PJ+ BAL samples (n=20); and seven additional BAL samples that were IFA negative, but positive using the modified gold standard. Compared with IFA, the PJ real-time PCR had sensitivity, specificity, and positive and negative predictive values of 100%, 91%, 65% and 100%, respectively. Compared with the modified gold standard, PJ real-time PCR had a sensitivity, specificity, and positive and negative predictive values of 100%. CONCLUSION: PJ real-time PCR improved detection of PJ in immunocompromised patients.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".