International Fetal Cardiac Intervention Registry
Bibliographic record
Abstract
BACKGROUND: Invasive fetal cardiac intervention (FCI) has been reported in single-institution series, promoting technical and physiologic success. OBJECTIVES: This study describes the creation of an international registry of cases presenting for FCI, intended to compile technical and outcome data from a multicenter cohort. METHODS: For this initial analysis, the entire database of the International Fetal Cardiac Intervention Registry (IFCIR) was queried for details of diagnoses, procedures, and outcomes. Maternal-fetal dyads from January 2001 through June 2014 were included. RESULTS: Eighteen institutions submitted data by data harvest. Of 370 cases entered, 245 underwent FCI: 100 aortic valvuloplasties from a previous single-center report (excluded from additional reporting here), an additional 86 aortic and 16 pulmonary valvuloplasties, 37 atrial septal cases, and 6 unclassified cases. FCI did not appear to affect overall survival to hospital discharge. Among live-born infants with a fetal diagnosis of aortic stenosis/evolving hypoplastic left heart syndrome, more than twice as many were discharged with biventricular circulation after successful FCI versus those meeting institutional criteria but without any or successful FCI (42.8% vs. 19.4%, respectively). When fetal deaths were counted as treatment failures, the percentages were similar: biventricular circulation at discharge was 31.3% versus 18.5% for those discharged with univentricular palliation. Survival to discharge for live-born fetuses with atrial restriction was similar to that of those undergoing technically successful versus unsuccessful FCI (63.6% vs. 46.7%, respectively), although criteria for diagnosis were nonuniform. CONCLUSIONS: We describe the contents of the IFCIR and present post-natal data to suggest potential benefit to fetal therapy among pregnancies considered for possible intervention and support proposals for additional work.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.013 |
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".