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Record W3078516117 · doi:10.1093/pch/pxaa068.073

74 MULTICENTER VALIDATION OF CORRECTION FACTORS FOR CEREBROSPINAL FLUID LABORATORY VALUES IN YOUNG INFANTS WITH A TRAUMATIC LUMBAR PUNCTURE

2020· article· en· W3078516117 on OpenAlexaff
Sarah Rogers, Jocelyn Gravel, Gregory Anderson, Jesse Papenburg, Caroline Quach, Brett Burstein

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsMontreal Children's HospitalCentre Hospitalier Universitaire Sainte-JustineUniversity of Manitoba
Fundersnot available
KeywordsMedicineLumbar punctureCerebrospinal fluidCSF pleocytosisPleocytosisMeningitisPediatricsCohortLumbarBacterial meningitisCohort studyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Abstract Background The evaluation of fever among infants in the first months of life remains one of the most common problems in pediatric healthcare. Approximately 10% harbor potentially life-threatening infections including bacterial meningitis, frequently necessitating invasive cerebrospinal fluid (CSF) testing by lumbar puncture (LP). LPs are often traumatic leading to uninterpretable results and consequently, broad-spectrum antibiotic exposure and prolonged hospitalization. Several strategies have been proposed to identify low-risk infants with traumatic LPs, including recently-derived correction factors, however studies validating the safety and diagnostic utility of such approaches are lacking. Objectives To evaluate the test characteristics and misclassification rates of recently described ratio-based correction methods for the interpretation of CSF results among young infants with traumatic LPs. Design/Methods We undertook a multicenter cohort study of infants aged ≤60 days with a traumatic LP performed at two urban tertiary Pediatric hospitals from 2006 to 2018. Traumatic LPs were defined as CSF specimens with ≥10,000 RBCs/mm3, and for infants aged ≤28 days and 29-60 days, pleocytosis was defined as ≥20 and ≥10 WBC/mm3, respectively, and abnormal protein ≥1.15 and ≥0.89 g/L, respectively. CSF WBCs and protein were adjusted downward for traumatic LPs using RBC ratio-based correction methods (newly derived 877:1, commonly used 500 and 1000:1, peripheral RBC:WBC ratio, and newly derived 1000 RBCs:0.011g/L protein). Descriptive statistics are presented with sensitivity, specificity, and negative predictive values of unadjusted and adjusted CSF for predicting culture-proven bacterial meningitis. Results Of 4,912 LPs meeting inclusion criteria, 437 (8.9%) were traumatic, among which 4 (0.9%) were positive for bacterial meningitis. Compared to uncorrected CSF WBC counts, both 877 and 1000 correction factors classified fewer infants with pleocytosis (38.0% and 42.6% vs 81.7%). These correction factors both maintained 100% sensitivity and 100% negative predictive value, and performed with greater specificity for bacterial meningitis than the uncorrected WBC count (62.6% and 58.0% vs 18.5%). No infants with bacterial meningitis were misclassified using either 877 or 1000:1 correction factors. CSF 500:1 and peripheral RBC:WBC correction ratios performed with the lowest sensitivity and negative predictive values and both misclassified 1 infant with bacterial meningitis. Corrected CSF protein outperformed uncorrected protein in specificity (66.8% vs 33.9%), but did not add diagnostic value when used in combination with WBC correction ratios. Conclusion Correction of the CSF WBC count substantially reduced the number of infants classified with CSF pleocytosis. The newly-derived 877:1 correction factor performed with the best test characteristics, safely reclassifying nearly half of all infants with a traumatic LP. It may be appropriate to use a correction factor in the evaluation of CSF cell counts in traumatic LPs in order to more effectively risk-stratify febrile young infants, reduce antibiotic exposure and admission duration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.042
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.276
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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