Use of Point-of-Care Ultrasonography in the NICU for Diagnostic and Procedural Purposes
Bibliographic record
Abstract
Point-of-care ultrasonography (POCUS) refers to the use of portable imaging performed by the provider clinician at the bedside for diagnostic, therapeutic, and procedural purposes. POCUS could be considered an extension of the physical examination but not a substitute for diagnostic imaging. Use of POCUS in emergency situations can be lifesaving in the NICU if performed in a timely fashion for cardiac tamponade, pleural effusions, pneumothorax, etc, with potential for enhancing quality of care and improving outcomes. In the past 2 decades, POCUS has gained significant acceptance in clinical medicine in many parts of the world and in many subspecialties. Formal accredited training and certification programs are available for neonatology trainees as well as for many other subspecialties in Canada, Australia, and New Zealand. Although no formal training program or certification is available to neonatologists in Europe, POCUS is widely available to providers in NICUs. A formal institutional POCUS fellowship is now available in Canada. In the United States, many clinicians have the skills to perform POCUS and have incorporated it in their daily clinical practice. However, appropriate equipment remains limited, and many barriers exist to POCUS program implementation. Recently, the first international evidence-based POCUS guidelines for use in neonatology and pediatric critical care were published. Considering the potential benefits, a recent national survey of neonatologists confirmed that the majority of clinicians were inclined to adopt POCUS in their clinical practice if the barriers could be resolved. This technical report describes many potential POCUS applications in the NICU for diagnostic and procedural purposes.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".