Feasibility of manual white blood cell counts as a predictor of neonatal sepsis in a low-resource setting
Bibliographic record
Abstract
BACKGROUND: Manual white blood cell (WBC) differential counts as a predictor for neonatal sepsis development in a low-resource setting have not been thoroughly evaluated. We hypothesized that manual differentiation (specifically immature:total [I:T] neutrophil ratios) would be feasible and useful as an adjunct to predict early-onset neonatal sepsis (EONS). Secondarily, we hypothesized that vaccination with bacillus Calmette-Guérin (BCG) and oral polio vaccine (OPV) could alter WBC differential counts and thus might reduce its predictive performance. METHODS: We performed a prospective cohort study within a randomized trial, randomizing healthy, high-risk newborns admitted to the nursery at the national hospital in Guinea-Bissau 1:1 to BCG+OPV at admission or at discharge (usual practice). Thin capillary blood films were prepared at 2 d of age in a subset of 268 neonates. WBC counts were assessed by microscopy and neonates were followed up for sepsis development within 2 weeks. RESULTS: Ninety-eight percent (264/268) of smears provided interpretable reads. Of the 264 children, 136 had been randomized to receive BCG+OPV prior to sampling; the remaining 128 were vaccinated at discharge. The I:T ratio (average 0.017) was lower among children who did not develop clinical sepsis but did not predict sepsis (p=0.70). Only three children had an I:T ratio >0.2 (associated with a higher probability of clinical sepsis in previous studies) but did not develop sepsis. Immunization did not alter WBC composition. CONCLUSIONS: Manual WBC differentials are feasible in low-resource settings. WBC differentials are not affected by standard newborn immunization. However, the I:T ratio had no value in predicting subsequent development of sepsis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".