40 Non-Conventional PEEP Ventilation and Regional Blood Flows in Hypoplastic Left Heart Infants
Bibliographic record
Abstract
It is suggested that the use of non-conventional positive end-expiratory pressure (PEEP) ventilatory strategies increases pulmonary vascular resistance and improves the balance of Qp/Qs in pre-operative infants with HLHS. We questioned whether a non-conventional ventilator strategy improved regional vascular hemodynamics in the anterior cerebral and splanchnic vascular beds. Term infants with HLHS and unbalanced circulations were randomised to either a low (<4 cm H2O) or high PEEP (>8) ventilation during stabilisation prior to Norwood procedure. PEEP was adjusted to obtain saturations of 75–85%. Doppler blood flow velocity (BFV) measurements of the celiac (CA), superior mesenteric (SMA) and anterior cerebral (ACA) arteries were performed prior to and one hour after the intervention. Average velocity (AV) and Pulsatility Index (PI) were calculated for each vessel by an investigator blinded to study group. Ten infants with HLHS were studied. Celiac PI and AV changed significantly (*p<0.04) in the low PEEP group. Due to the small sample size the power was less than the desirable level. These interesting preliminary data suggest that a non-conventional low-PEEP ventilatory strategy may improve celiac artery BFV in pre-operative infants with HLHS. Further study of a larger population is required before concluding a beneficial effect of non-conventional ventilation on regional hemodynamics in pre-operative HLHS infants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".