Diagnostic test accuracy of point-of-care procalcitonin to diagnose serious bacterial infections in children
Bibliographic record
Abstract
BACKGROUND: The National Institute for Health and Care Excellence (NICE) have called for research into the role of biomarkers, and specifically procalcitonin (PCT), for the early diagnosis of serious bacterial infections (SBI) in children. The aim of this study was to compare the diagnostic test accuracy of C-reactive protein (CRP) and PCT for the diagnosis of SBI in children. METHODS: Data was collected prospectively from four UK emergency departments (ED) between November 2017 and June 2019. Consecutive children under 18 years of age with fever and features of possible sepsis and/or meningitis were eligible for inclusion. The index tests were PCT and CRP and the reference standard was the confirmation of SBI. RESULTS: 213 children were included in the final analysis. 116 participants (54.5%) were male, and the median age was 2 years, 9 months. Parenteral antibiotics were given to 100 (46.9%), three (1.4%) were admitted to a paediatric intensive care unit and there were no deaths. There were ten (4.7%) confirmed SBI. The area under the curve for PCT and CRP for the detection of SBI was identical at 0.70. CONCLUSIONS: There was no difference in the performance of PCT and CRP for the recognition of SBI in this cohort. TRIAL REGISTRATION: Registered at https://www.clinicaltrials.gov (trial registration: NCT03378258 ) on the 19th of December 2017.
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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 | 0.011 |
| 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".