Does prenatal diagnosis of hypoplastic left heart syndrome make a difference? – A systematic review
Bibliographic record
Abstract
OBJECTIVE: Hypoplastic left heart syndrome is frequently diagnosed prenatally with variable benefit. We performed a systematic review to evaluate the impact of fetal diagnosis; the primary objective was to evaluate impact on mortality. METHODS: Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Seven databases were searched. Meta-analysis was performed using a random effects model to evaluate the effect of fetal diagnosis on mortality. RESULTS: Literature search revealed 2124 titles and abstracts for screening; 21 full texts were reviewed. Six studies and one abstract were included. Preoperative mortality in 609 neonates (228 prenatal and 381 postnatal) was evaluated. There were 11 deaths in prenatally diagnosed neonates versus 16 deaths in postnatally diagnosed neonates (OR 0.67, 95% CI 0.22-2.01, p = 0.48). Neonates with fetal diagnosis had less preoperative acidosis (mean difference 0.07, 95% CI 0.05, 0.1, p < 0.01) and required less inotropic support (OR 0.16, 95% CI 0.04, 0.7, p = 0.01). Post Stage I, there were 47 deaths in 227 prenatally diagnosed neonates versus 78 deaths in 299 postnatally diagnosed neonates (OR 0.84, 95% CI 0.43, 1.62, p = 0.59). CONCLUSIONS: There is no significant impact of prenatal diagnosis of hypoplastic left heart syndrome on preoperative or post Stage I mortality. Neonates with prenatal diagnosis were hemodynamically more stable. © 2016 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".