Monogenic Syndromes with Congenital Heart Diseases in Newborns (Diagnostic Clues for Neonatologists): A Critical Analysis with Systematic Literature Review
Bibliographic record
Abstract
Congenital heart disease (CHD), the most common major congenital anomaly, is associated with a genetic syndrome (chromosomal anomalies, genomic disorders, or monogenic disease) in 30% of patients. The aim of this systematic review was to evaluate if, in the neonatal setting, clinical clues that orient the diagnostic path can be identified. For this purpose, we revised the most frequent dysmorphic features described in newborns with CHD, comparing those associated with monogenic syndromes (MSG) with the ones reported in newborns with genomic disorders. For this systematic review according to PRISMA statement, we used PubMed, Medline, Google Scholar, Scopus database, and search terms related to CHD and syndrome. We found a wide range of dysmorphisms (ocular region, ears, mouth, and/or palate and phalangeal anomalies) detected in more than half of MSGs were found to be associated with CHDs, but those anomalies are also described in genomic rearrangements syndromes with equal prevalence. These findings confirmed that etiological diagnosis in newborns is challenging, and only the prompt and expert recognition of features suggestive of genetic conditions can improve the selection of appropriate, cost-effective diagnostic tests. However, in general practice, it is crucial to recognize clues that can suggest the presence of a genetic syndrome, and neonatologists often have the unique opportunity to be the first to identify abnormalities in the neonate.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.024 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".