Point of care ultrasound (POCUS) protocol for systematic assessment of the crashing infant - Expert consensus statement of the international crashing infant working group
Bibliographic record
Abstract
Abstract Purpose Sudden expected deterioration is common in neonates. The established resuscitation guidelines provide excellent framework to stabilize these infants. However, physical examination in sick neonates is limited in identifying underlying pathology. The purpose of crashing infant protocol (CIP) is specifically to design an ultrasound guided adjunct approach for use in neonatal emergencies, and it can be applied in both term and pre-term neonates in any emergency clinical setting such as neonatal intensive care unit (NICU), post-natal ward, delivery room, emergency room or during transport. Methods An expert consensus was reached using a modified anonymous electronic Delphi strategy for the voting process. The statement guidelines have been prepared according to the international Appraisal of Guidelines, Research and Evaluation (AGREE). Results A total of 20 recommendations on the use of POCUS in the crashing infant were assessed. There was strong agreement from all panelists on 16 recommendations and agreement on 4 recommendations. Conclusions The newly proposed CIP and recommendations can be used as an adjunct to the current neonatal resuscitation guidelines. The CIP protocol is proposed based upon preidentified steps focused on gaining information regarding pathophysiology in infants with unexplained clinical deterioration or those not responding to the standard resuscitation.
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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 | 0.224 | 0.215 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".