Utilisation of neonatologist‐performed echocardiography in shock among neonatologists with interest in haemodynamic: International survey
Bibliographic record
Abstract
AIM: Neonatologist-performed echocardiography (NPE) is recommended during shock. We aimed to assess factors associated with NPE utilisation in the NICU and physiological information obtained during management of shock. METHODS: An Internet-based survey, sent to neonatologists with interest in haemodynamics, studying NPE utilisation in shock management through a real clinical case and correlating its use with responders' training and NICU settings. RESULTS: Fifty-nine completed surveys were received from the United Kingdom: 38%, Western Europe: 32%, Canada: 23% and other countries: 7%. Whilst managing the given clinical case, 90% of responders expected first NPE to exclude congenital heart disease-although only 61% could exclude it confidently (71% in trained clinicians vs. 29% without training; p < 0.01). NPE utilisation prior to initiate treatment was significantly correlated with mean number of neonatologists able to perform NPE in the NICU (4.9 vs. 2.9 neonatologists per unit; p = 0.02). Similarly, for ongoing therapeutic guidance, NPE was more used in trained clinicians (p < 0.01). 88% and 81% of responders studied a combination of multiple parameters to assess filling and systemic flow, respectively. CONCLUSION: Neonatologist-performed echocardiography during shock management differs with previous training and number of doctors able to perform echocardiography in NICU. This study highlighted the need for enhanced training implementation.
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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 | 0.001 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".