Prediction of Bacteremia and Bacterial Meningitis Among Febrile Infants Aged 28 Days or Younger
Bibliographic record
Abstract
Importance: Fever in the first month of life is often the only sign of life-threatening invasive bacterial infection, specifically bacteremia or bacterial meningitis. Most international guidelines recommend routine lumbar punctures for all febrile infants 28 days or younger to rule out bacterial meningitis. Clinical prediction rules may allow for select testing, but limited information exists on their performance to identify infants at low risk for invasive bacterial infections. Objective: To evaluate the diagnostic accuracy of the updated Pediatric Emergency Care Applied Research Network (PECARN) prediction rule for identifying febrile infants 28 days or younger with bacteremia or bacterial meningitis. Design, Setting, and Participants: This pooled analysis of 4 published prospective cohort studies from pediatric emergency departments across 6 countries within the global Pediatric Emergency Research Network included previously healthy, non-ill-appearing, full-term (≥37 weeks' gestation) infants aged 28 days or younger with a temperature greater than or equal to 38.0 °C who underwent urine, blood, and serum testing. Exposure: Infants were classified as low risk if they had a negative urinalysis/dipstick test result, serum procalcitonin less than or equal to 0.5 ng/mL, and blood absolute neutrophil count less than or equal to 4000/mm3. Main Outcomes and Measures: Meta-analytic methods were applied to assess diagnostic accuracy (sensitivity, specificity, and positive and negative predictive values) of the PECARN rule for detection of infants with invasive bacterial infections (bacteremia or bacterial meningitis). Results: Among 1537 infants 28 days or younger (905 male, 1324 hospitalized, 1080 with lumbar punctures), 69 (4.5%) had invasive bacterial infections, including 11 (0.7%) with bacterial meningitis. Overall, 632 (41.1%) met low-risk criteria. The prediction rule had a sensitivity of 94.2% (95% CI, 85.6%-97.8%), specificity of 41.6% (95% CI, 36.7%-46.7%), positive predictive value of 6.9% (95% CI, 4.8%-9.9%), and negative predictive value of 99.4% (95% CI, 98.1%-99.8%) for invasive bacterial infections. In a secondary analysis of 2531 infants from the 2 US-based cohorts from which the rule was originally derived and the 4 validation cohorts, 96 (3.8%) had invasive bacterial infections, 22 (0.9%) had bacterial meningitis, and 1079 (42.6%) were classified as low risk; rule performance was similar. No infants with bacterial meningitis were misclassified in the primary or secondary analyses. Conclusions and Relevance: The updated PECARN rule had high sensitivity but lower specificity for identifying febrile infants 28 days or younger with invasive bacterial infections in this study, with no missed cases of bacterial meningitis. These results may support shared decision-making regarding select vs routine use of lumbar puncture among infants classified as being at low risk of invasive bacterial infections.
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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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.019 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".