Cri du Chat Syndrome and Congenital Heart Disease: A Review of Previously Reported Cases and Presentation of an Additional 21 Cases From the Pediatric Cardiac Care Consortium
Bibliographic record
Abstract
OBJECTIVES: To analyze the cases submitted to the Pediatric Cardiac Care Consortium (PCCC) database from 1982 to 2002 to determine the frequency and distribution of congenital heart disease (CHD) found in this population, to review the literature for previously published accounts of CHD in this population, and to review current genotype-phenotype associations for cri du chat (CDC) syndrome with CHD. METHODS: We performed a retrospective review of the 98422 CHD cases submitted to the PCCC between 1982 and 2002, to find patients who had a noncardiac diagnosis of CDC syndrome. RESULTS: A total of 21 patients (15 female and 6 male patients) were identified. Although some patients had multiple cardiac anomalies, they were categorized according to primary diagnoses on the basis of the most hemodynamically significant component. The patient groups were ventricular septal defect (n = 6), patent ductus arteriosus (n = 6), tetralogy of Fallot (n = 5), pulmonary valve atresia with ventricular septal defect (n = 2), pulmonary valve stenosis (n = 1), and double-outlet right ventricle (n = 1). Eighteen of the 21 patients underwent surgical repair of their defects. There was 1 late operative death. To determine whether the observed frequency of these cardiac defects among patients with CDC syndrome was comparable to that of the general population of patients with CHD, data for all cases submitted to the PCCC from 1982 to 2002 were used. Use of these numbers to determine expected frequencies for these defects showed significantly greater proportions of patients with these specific lesions among the patients with CDC syndrome. CONCLUSIONS: Currently there is no clear understanding of the genomic cause of the prevalence of these defects in the population with CDC syndrome, although CHD has been noted among patients with other deletion syndromes.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".