Rates of Intracardiac Umbilical Venous Catheter Placement in Neonates
Bibliographic record
Abstract
OBJECTIVES: To review umbilical venous catheter (UVC) placement in neonates who underwent targeted neonatal echocardiography (TNE) and to correlate catheter tip placement on TNE and anteroposterior thoracoabdominal radiography. METHODS: We conducted a retrospective analysis of 51 neonates who had UVC positions assessed by TNE and radiography in a neonatal intensive care unit (NICU). A single operator performed all TNE examinations. The final radiographic catheter placement was taken from the image closest to the time of echocardiography. Fisher exact, χ(2), and t tests were used as appropriate. RESULTS: Among the 51 neonates who had catheters placed for 24 hours or more, TNE was performed on 48 in the first 48 hours, 2 at day 6, and 1 at day 9. Thirty-six neonates were extremely low birth weight (ELBW; <1000 g). Twenty-nine had good catheter tip positions, and 22 had catheters inside the heart (10 in the right atrium [RA], 3 at the foramen ovale, and 9 in the left atrium [LA]). Twenty neonates with catheter tips in the heart were ELBW, including 8 with catheters in the LA. The ELBW neonates were more likely to have catheters in the heart than non-ELBW neonates (20 of 36 versus 2 of 15; P= .01; odds ratio [OR], 8.1; confidence interval [CI], 1.59-41.3). Good placement on TNE varied widely in relation to thoracic vertebral landmarks on radiography: from the T7-8 interspace to T11. When radiography showed a catheter tip at T9-T10, there was no difference in the proportion of neonates with a good catheter position versus malposition (8 of 22 versus 8 of 29; P = .55; OR, 0.67; CI, 0.20-2.19). CONCLUSIONS: A high proportion of ELBW neonates in a busy NICU had UVCs placed with the tips in the RA or LA despite common placement practices. We recommend adding TNE to radiography to position UVCs, especially in ELBW neonates.
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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 | 0.001 | 0.000 |
| 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".