Utility of Targeted Neonatal Echocardiography in the Management of Neonatal Illness
Bibliographic record
Abstract
OBJECTIVES: To describe the impact of targeted neonatal echocardiography on management of neonatal illness in a tertiary perinatal center neonatal intensive care unit (NICU). METHODS: We conducted a retrospective analysis of consecutive targeted neonatal echocardiographic studies that were performed over an 18-month period in a regional perinatal center NICU in Canada. All studies were performed with a cardiovascular ultrasound machine and transducer and read on a workstation with storage and analysis software. Reporting was done on a standardized document, and any management change resulting from targeted neonatal echocardiography was documented. RESULTS: A total of 303 consecutive targeted neonatal echocardiographic studies were performed on 129 neonates. The mean gestational age ± SD was 27.8 ± 4.3 weeks (range, 23-41 weeks), and the mean birth weight ± SD was 1196 ± 197 g (range, 490- 4500 g). The median number of studies per neonate was 2 (range, 1-8), with most repeated studies for a patent ductus arteriosus (PDA). The most common indication for echocardiography was assessment of a PDA (52.1%), followed by early global hemodynamic assessment of very low birth weight (16.2%) and pulmonary hypertension (12.2%). Of the 303 studies, 126 (41.5%) resulted in management changes. The contribution to management was significantly related to the timing of echocardiography. Around half of the echocardiographic examinations during first the week of life resulted in management changes, compared to 22% of studies after 1 week of age (P = .002). Patent ductus arteriosus management accounted for almost half of the interventions. CONCLUSIONS: Targeted neonatal echocardiography is a valuable tool in the NICU and can contribute substantially to hemodynamic management in the first week of life, PDA management in the first 2 weeks of life, and cases of hypotension or shock at any time during the hospital stay.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".