Real-Time PCR Assay Provides Reliable Assessment of Intrapartum Carriage of Group B <i>Streptococcus</i>
Bibliographic record
Abstract
The objective of this study was to determine the reliability of the real-time PCR assay for determining the group B Streptococcus (GBS) status of women in labor. In this prospective study we compared the results of culture and PCR testing of vaginal and rectal samples collected by nursing staff when women were in labor. Patients' charts were also reviewed to obtain relevant information about pregnancy risk factors. Our results demonstrated a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 90.5%, 96.1%, 86.4%, and 97.4%, respectively, for rapid PCR. Of the 196 women evaluated, 29 (14.8%) presented with unknown GBS status, 11 (37.9%) of whom received unnecessary intrapartum antibiotics. The rapid real-time PCR test was robust and was able to reliably detect the presence of GBS in women in labor within 1 h of specimen submission to the laboratory. We recommend that the rapid PCR test be targeted to women who present in labor with unknown GBS status. In cases where the laboratory does not offer 24-h availability of testing, sample collection followed by PCR testing the next morning is still valuable and provides reliable results 24 to 48 h faster than culture and will aid appropriate decision-making regarding continuing or stopping antibiotics for neonates of women with unknown GBS status.
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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 | 0.003 | 0.012 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".