Gestational Age, Birth Weight, and Outcomes Six Years After the Norwood Procedure
Bibliographic record
Abstract
BACKGROUND: Preterm delivery and low birth weight (LBW) are generally associated with worse outcomes in hypoplastic left heart syndrome (HLHS), but an individual preterm or small neonate may do well. We sought to explore the interactions between gestational age, birth weight, and birth weight for gestational age with intermediate outcomes in HLHS. METHODS: We analyzed survival, growth, neurodevelopment, length of stay, and complications to age 6 years in subjects with HLHS from the Single Ventricle Reconstruction trial. Univariate and multivariable survival and regression analyses examined the effects and interactions of LBW (<2500 g), weight for gestational age, and gestational age category. RESULTS: = 219) delivery. Small for gestational age (SGA) was present in 41% of subjects, but only 14% had LBW. Preterm, compared with term, delivery was associated with an increased risk of death or transplant at age 6 years (all: hazard ratio = 2.58, confidence interval = 1.43-4.67; Norwood survivors: hazard ratio = 1.96, confidence interval = 1.10-3.49) independent of LBW and weight for gestational age. Preterm delivery, early-term delivery, LBW, and SGA were each associated with lower weight at 6 years. Neurodevelopmental outcomes were worst in the LBW cohort. CONCLUSIONS: Preterm delivery in HLHS was associated with worse survival, even beyond Norwood hospitalization. LBW, SGA, and early-term delivery were associated with worse growth but not survival. LBW was associated with worse neurodevelopment, despite similar length of stay and complications. These data suggest that preterm birth and LBW (although often concomitant) are not equivalent, impacting clinical outcomes through mechanisms independent of perioperative course complexity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".