OP047 Topic: AS24–Resuscitation, Stabilization & Transport: Rapid Response Teams/ECMO Transport/Air Transport/Telemedicine/Other: VALIDITY OF VARIOUS PEDIATRIC EARLY WARNING SCORES (PEWS) IN MALNOURISHED CHILDREN IN THE EMERGENCY ROOM
Bibliographic record
Abstract
Aims & Objectives: Pediatric Early Warning Scores (PEWS) for malnourished children in low-middle income countries have never been validated. This study examined the potential of common PEWS to predict clinical worsening in malnourished infants at risk of sepsis and death. Methods: Five PEWS were prospectively validated. Over a year, malnourished children aged≤12 years who visited the ER were enrolled. PEWS was used to examine clinical parameters and follow children for 48 hours or until clinical deterioration, which included PICU transfers, cardiac arrest, the development of shock, and intubation or mortality. The validity of PEWS was expressed by ROC curves. Results: 3724 children were screened, and 1326 malnourished children were enrolled. Out of these, 361 (27.2%) deteriorated, and 965 (72.7%) were discharged. The area under ROC for predicting clinical deterioration was good for Cardiac Children Hospital Early Warning Score (CCHEWS; AUROC 0.819, 95% CI: 0.796-0.841) and Brighton (AUROC 0.813, 95% CI: 0.789-0.838), moderate for Cardiff and Vale (AUROC 0.752, 95% CI: 0.723-0.781) and poor for Birmingham and Toronto (AUROC 0.694, 95% CI: 0.659-0.729) and Bedside PEWS (BPEWS; AUROC 0.559, 95% CI: 0.524-0.529). CCHEWS had the highest sensitivity, and the Birmingham-Toronto score had the highest specificity. None of the scores had high specificity or sensitivity. Conclusions: Although CCHEWS and Brighton could detect clinical deterioration, they had low sensitivity, positive predictive value, and diagnostic accuracy. None of the scores are comprehensive or reliable enough for malnourished patients, thus, limiting their application. Keywords: Pediatric Early Warning Scores; PEWS; Malnourished Children
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 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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.012 |
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".