Long-term non-institutionalized survival and rehospitalization after surgical aortic and mitral valve replacements in a large provincial cardiac surgery centre
Bibliographic record
Abstract
OBJECTIVES: Long-term quality of life following open surgical valve replacement is an increasingly important outcome to patients and their caregivers. This study examines non-institutionalized survival and rehospitalization within our surgical aortic valve replacement (AVR) and mitral valve replacement (MVR) populations. METHODS: A retrospective single-centre study of all consecutive open surgical valve replacements between 1995 and 2014 was undertaken. Clinical data were linked to provincial administrative data for 3219 patients who underwent AVR, MVR or double (aortic and mitral) valve replacement with or without concomitant coronary artery bypass grafting (CABG). Non-institutionalized survival and cumulative incidence of rehospitalization was examined up to 15 years. RESULTS: Follow-up was complete for 96.9% of the 2146 patients who underwent AVR ± CABG (66.7% of the overall cohort), 878 who underwent MVR ± CABG (27.3%) and 195 who underwent double (aortic and mitral) valve replacement ± CABG (6.0%) with a median follow-up time of 5.6 years. Overall non-institutionalized survival was 35.4% at 15 years, and the cumulative incidence of rehospitalization was 34.4%, 63.2% and 87.0% at 1, 5 and 15 years, respectively, without significant differences between valve procedure cohorts. Both non-institutionalized survival and cumulative incidence of rehospitalization improved in more recent eras, despite increasing age and comorbidities. CONCLUSIONS: Non-institutionalized survival and rehospitalization data for up to 15 years suggest good functional outcomes long after surgical AVR and/or MVR. Continued improvements are seen in these metrics over the past 2 decades. This provides a unique insight into the quality of life after surgical valve replacement in the ageing demographics with valvular heart disease.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".