Outlet strut fracture of Bjork-Shiley convexo concave heart valves: the UK cohort study
Bibliographic record
Abstract
OBJECTIVE: To investigate the risk of outlet strut fracture (OSF) in Björk-Shiley convexo concave (BSCC) valves in relation to patients' clinical and valve characteristics. DESIGN: A cohort of 2977 patients with 3325 valves with a follow up of 18 years. SETTING: 38 cardiac implantation centres in the UK. RESULTS: 56 OSF events were reported with 43 occurring in mitral and 13 in aortic valves. The overall OSF rate was 0.17%/year. No dominant clinical factor of risk was found, but multiple regression analysis identified age, body surface area, valve size, shop order fracture rate, and manufacturing period as risk factors for OSF. A 4% (95% confidence interval (CI) 2% to 6%) decrease in the risk of OSF was observed for each advancing year of age and a fivefold (95% CI 2 to 13) increase in risk for a 0.5 m(2) increase in body surface area. The association between the risk of OSF and valve size was not constant over time. Excess risks among 31 mm and 33 mm sizes (mainly mitral valves) decreased over time while that for 23 mm (almost all aortic valves) increased. The risk of OSF increased by 40% (95% CI 20% to 50%) for a unit increase in the fracture rate of other valves in the same batch. For valves manufactured during 1981 to 1984 the risk of OSF was 4 (95% CI 2 to 12) times greater than for valves manufactured before 1981. CONCLUSIONS: The OSF rates for 60 degrees BSCC valves observed in the UK are the highest among all monitored populations. The changing patterns of mitral and aortic valve OSF rates over time observed in this study have not been identified previously and highlight the need for continued monitoring of patients with the BSCC valve.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".