Aortic valve replacement in over 70- and over 80-year olds: 5-year cohort study
Bibliographic record
Abstract
BACKGROUND: Demand for aortic valve intervention remains high, and together with the recent introduction of transcatheter aortic valve implantation, this motivates a review of surgical aortic valve replacement in elderly recipients. METHODS: Consecutive patients over 70 years of age having isolated aortic valve replacement during 2007-11 were retrospectively identified and divided into 70-79 and ≥ 80 years age groups for analyses. RESULTS: 62 octogenarians and 121 septuagenarians were eligible. Among octogenarians, a lower proportion were in Canadian Cardiovascular Society angina class 3-4 (3.2% vs. 14.0%, p = 0.022) and fewer had diabetes (11.3% vs. 24.8%, p = 0.034), but a higher proportion had infective endocarditis (6.5% vs. 0%, p = 0.012), and EuroSCORE II was higher (4.9% vs. 3.7%, p < 0.001). Despite this, operative mortality was lower in octogenarians (0% vs. 7.4%, p = 0.029), although hospital stay (11.7 vs. 8.9 days, p = 0.026) was longer. One-, 3-, and 5-year survival rates were 95.2%, 90.1%, and 75.3% for octogenarians and 89.2%, 81.7%, and 70.2% for septuagenarians (p = 0.398). Canadian Cardiovascular Society angina class 3-4 and the presence of other valvular stenosis or regurgitation were independent predictors of mortality. CONCLUSION: Octogenarians had lower operative mortality despite a higher predicted risk preoperatively. Other factors beyond age and EuroSCORE, such as frailty, may be important in deciding whether elderly patients should undergo aortic valve replacement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".