Clinical impact of cerebrospinal fluid Gram stain and culture testing: A retrospective cohort study
Bibliographic record
Abstract
Background: Stewardship of microbiological tests can improve laboratory efficiency. One indicator of appropriate test stewardship is test impact on patient management decisions. We sought to assess the impact of cerebrospinal fluid (CSF) Gram stain and culture results on treatment decisions. Our hypothesis was that CSF Gram stain and culture have low impact on patient management. Methods: CSF specimens received at a tertiary microbiology laboratory between January 1, 2013, and December 31, 2013, were included. Clinical information and data on antibiotic treatment before CSF collection, antibiotic treatment after CSF Gram stain results, and antibiotic treatment after CSF culture results were collected. Ethics approval for secondary use of data was obtained. Results: We received 242 CSF specimens for Gram stain and culture during the study period; 120 were excluded (84 from children, 2 from indwelling ventricular drains, 12 collected at outside hospitals, 21 data missing, 1 duplicate). No Gram stains or cultures were positive among patients not already treated empirically. The number needed to test to influence treatment was 17 for Gram stain (11 for abnormal cytochemistry, 29 for normal cytochemistry) and 6 for culture (3 for abnormal cytochemistry, 6 for normal cytochemistry). Conclusions: CSF Gram stain and culture are rarely positive and are being performed on inappropriate specimens. CSF results never prompt physicians to start treatment, so results are affecting not outcome but antibiotic stewardship. Negative CSF culture often leads to discontinuation of antibiotics. Labs could consider rejecting CSF Gram stain if cytochemistry is normal.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".