Does Extreme Leukocytosis Predict Serious Bacterial Infections in Infants in the Post-Pneumococcal Vaccine Era? The Experience of a Large, Tertiary Care Pediatric Hospital
Bibliographic record
Abstract
BACKGROUND: Extreme leukocytosis, defined as a peripheral white blood cell count greater than 25,000/mm, may alarm clinicians and prompt extensive evaluation in infants with fever, especially in the pediatric emergency department. METHODS: We reviewed data from children aged 3 to 36 months with extreme leukocytosis, fever and the risk of serious bacterial infections (SBI) at our institution from July 2010 to December 2012, a period after the universal introduction of pneumococcal vaccine. RESULTS: Serious bacterial infection was recorded in 57 (39%) of the 147 infants. The most common SBI were segmental or lobar pneumonia, in 28 (19%) patients, and urinary tract infection in 16 (10.9%) patients. Three patients had positive blood cultures, corresponding to a bacteremia rate of 2%. C-reactive protein was significantly higher in the SBI group than in the non-SBI group. CONCLUSIONS: All well-looking febrile infants with white blood cell greater than 25,000/mm should undergo a chest radiograph unless there are clear physical findings that indicate a different etiology. Urine culture should be considered in women. C-reactive protein can have an added value in the differential diagnosis.
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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 | 0.001 |
| 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".