Multicentre experience on the diagnostic yield of PCR testing for bacterial pathogens in sterile site infections
Bibliographic record
Abstract
Background: Infections in sterile body sites are serious despite their low incidence. Accurate diagnosis is crucial for effective antimicrobial management. This study assessed the diagnostic yield of multiplex polymerase chain reaction (PCR) in identifying bacterial pathogens in sterile site specimens other than blood and cerebrospinal fluid. Methods: Bacterial pathogen PCR panels were independently developed and validated by the laboratories at the Hamilton Regional Laboratory Medicine Program (HRLMP) in Canada and Sidra Medicine in Qatar. Retrospective culture and PCR data for the periods of July 2022 to November 2023 and September 2021 to February 2023 were extracted from the laboratory information systems of HRLMP and Sidra Medicine, respectively. The diagnostic yield of PCR between different groups was compared using the McNemar test or chi-square test. Results: Validation studies showed 100% sensitivity for PCR assays in both laboratories, with varying specificity due to the detection of additional pathogens by PCR. Combining post-implementation data from both laboratories, 38.7% of 512 specimens were PCR-positive for target organisms, compared to 6.1% by culture. While the diagnostic yield of PCR was significantly higher than that of culture in both adult and paediatric populations ( p < .001), HRLMP data indicated a significantly higher diagnostic yield of PCR in the paediatric population compared to adults (64.7% versus 17.4%; p < .001). The most commonly PCR-detected pathogens were Streptococcus pneumoniae, Streptococcus pyogenes, and Staphylococcus aureus, with pleural fluid being the most frequently positive specimen type. Conclusion: This study supports using PCR alongside culture to enhance pathogen detection and improve the management of sterile site infections, particularly in paediatric 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 | 0.030 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".