Clinical Utility of CSF Correction Factors for Traumatic Lumbar Puncture in Adults
Bibliographic record
Abstract
Objectives: To identify indicators of false pleocytosis in adults with traumatic lumbar puncture (LP), and determine specificities and sensitivities of commonly used CSF correction factors. Methods: Adults who underwent 4-tube CSF collection were reviewed. Study inclusion required elevated tube 1 red blood cell (RBC) count, tube 1 pleocytosis, and normalized tube 4 RBC count. Tube 4 white blood cell (WBC) count served as the reference standard. Specificities and sensitivities of 3 correction factors (1 WBC:500 RBC, 1 WBC:1000 RBC, and 1 WBC:1500 RBC) were calculated. Results: One hundred ninety-five adults were included. Among them, 106 (54%) had false tube 1 pleocytosis; these patients had a significantly higher median CSF RBC count and lower median CSF WBC count than those with true tube 1 pleocytosis. Specificities and sensitivities of correction factors ranged from 71.7% to 29.2% and 84.3% to 97.8%, respectively; 1 WBC:500 RBC had highest specificity for pleocytosis, while 1 WBC:1500 RBC had highest sensitivity. Irrespective of correction factor used, false-positive and false-negative determinations of pleocytosis were usually mild (≤20 WBCs/μL). Discussion: Indicators of false pleocytosis in adults with traumatic LP include bloodier CSF and milder pleocytosis, suggesting that correction factors are most useful in such cases. Across correction factors, an expected specificity/sensitivity tradeoff is observed. Corrected CSF WBC counts suggesting only mild pleocytosis should be interpreted cautiously.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".