Superior Vena Cava Flow in Preterm Infants and Neonatal Outcomes: A Systematic Review
Bibliographic record
Abstract
Superior vena cava (SVC) flow has been considered a surrogate marker of systemic blood flow in neonates. We conducted a systematic review to evaluate the association between low SVC flow recorded during the early neonatal period and neonatal outcomes. We searched the following databases (until December 9, 2020; updated October 21, 2022): PROSPERO, OVID Medline, OVID EMBASE, Cochrane Library (CDSR and Central), Proquest Dissertations and Theses Global, and SCOPUS using controlled vocabulary and key words representing the concepts "superior vena cava" and "flow" and "neonate." Results were exported to COVIDENCE review management software. The search retrieved 593 records after the removal of duplicates, of which 11 studies (nine cohorts) met the inclusion criteria. The majority of the studies included infants born at <30 weeks of gestation. The included studies were assessed as high risk of bias in terms of the incomparability of the study groups, with infants in the low SVC flow group noted to be more immature than those in the normal SVC flow group or subjected to different cointerventions. We did not conduct meta-analyses in view of the significant clinical heterogeneity noted in the included studies. We found little evidence to suggest that SVC flow in the early neonatal period is an independent predictor for adverse clinical outcomes in preterm infants. Included studies were assessed at high risk of bias. We conclude that SVC flow interpretation for prognostication or for making treatment decisions should be restricted to the research setting for now. We highlight the need for strengthened methods in future research studies. KEY POINTS: · We studied whether low SVC flow in the early neonatal period is a marker for adverse outcomes in preterm infants.. · There is insufficient evidence to conclude that low SVC flow is a valid predictor of adverse outcomes.. · There is insufficient evidence to conclude that SVC flow-directed hemodynamic management improves clinical outcomes..
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".