The Impact of Congenital Cardiac Surgery Fellowship on Training and Practice
Bibliographic record
Abstract
BACKGROUND: In 2007, congenital cardiac surgery became a recognized fellowship by the American Council of Graduate Medical Education (ACGME). Beginning in 2023, the fellowship transitioned from a 1-year to a 2-year program. Our objective is to provide current benchmarks by surveying current training programs and assessing characteristics contributing to career success. METHODS: This was a survey-based study in which tailored questionnaires were distributed to program directors (PDs) and graduates of the ACGME accredited training programs. Data collection included responses to multiple-choice and open-ended questions relevant to didactics, operative training, training center characteristics, mentorship, and employment characteristics. Results were analyzed using summary statistics and subgroup and multivariable analyses. RESULTS: The survey yielded responses from 13 of 15 PDs (86%) and 41 of 101 graduates (41%) from ACGME accredited programs. Perceptions among PDs and graduates were somewhat discordant, with PDs more optimistic than graduates. Of PDs, 77% (n = 10) believed current training adequately prepares fellows and is successful in securing employment for graduates. The responses from graduates demonstrated 30% (n = 12) were dissatisfied with operative experience and 24% (n = 10) with overall training. Being supported during the first 5 years of practice was significantly associated with retention in congenital cardiac surgery and greater practicing case volumes. CONCLUSIONS: Dichotomous views exist between graduates and PDs regarding success in training. Mentorship during the early career was associated with increased case volumes, career satisfaction, and retention in the congenital cardiac surgery field. Educational bodies should incorporate these elements during training and after graduation.
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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 | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".