Results of international assistance for a paediatric heart surgery programme in a single Ukrainian centre
Bibliographic record
Abstract
BACKGROUND: Surgery for CHD has been slow to develop in parts of the former Soviet Union. The impact of an 8-year surgical assistance programme between an emerging centre and a multi-disciplinary international team that comprised healthcare professionals from developed cardiac programmes is analysed and presented.Material and methodsThe international paediatric assistance programme included five main components - intermittent clinical visits to the site annually, medical education, biomedical engineering support, nurse empowerment, and team-based practice development. Data were analysed from visiting teams and local databases before and since commencement of assistance in 2007 (era A: 2000-2007; era B: 2008-2015). The following variables were compared between periods: annual case volume, operative mortality, case complexity based on Risk Adjustment for Congenital Heart Surgery (RACHS-1), and RACHS-adjusted standardised mortality ratio. RESULTS: A total of 154 RACHS-classifiable operations were performed during era A, with a mean annual case volume by local surgeons of 19.3 at 95% confidence interval 14.3-24.2, with an operative mortality of 4.6% and a standardised mortality ratio of 2.1. In era B, surgical volume increased to a mean of 103.1 annual cases (95% confidence interval 69.1-137.2, p<0.0001). There was a non-significant (p=0.84) increase in operative mortality (5.7%), but a decrease in standardised mortality ratio (1.2) owing to an increase in case complexity. In era B, the proportion of local surgeon-led surgeries during visits from the international team increased from 0% (0/27) in 2008 to 98% (58/59) in the final year of analysis. CONCLUSIONS: The model of assistance described in this report led to improved adjusted mortality, increased case volume, complexity, and independent operating skills.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".