Association of comorbid burden with clinical outcomes after transcatheter aortic valve implantation
Bibliographic record
Abstract
OBJECTIVES: To investigate the association of the CharlsonComorbidity Index (CCI) with clinical outcomes after transcatheter aortic valve implantation (TAVI). BACKGROUND: Patients undergoing TAVI have high comorbid burden; however, there is limited evidence of its impact on clinical outcomes. METHODS: Data from 1887 patients from the UK, Canada, Spain, Switzerland and Italy were collected between 2007 and 2016. The association of CCI with 30-day mortality, Valve Academic Research Consortium-2 (VARC-2) composite early safety, long-term survival and length of stay (LoS) was calculated using logistic regression and Cox proportional hazard models, as a whole cohort and at a country level, through a two-stage individual participant data (IPD) random effect meta-analysis. RESULTS: =0.16 to 0.29), and approximately 50% of patients classed as low risk from four risk prediction models still presented with a CCI ≥3. Per-unit increases in total CCI were not associated with increased odds of 30-day mortality (OR 1.09, 95% CI 0.96 to 1.24) or VARC-2 early safety (OR 1.04, 95% CI 0.96 to 1.14) but were associated with increased hazard of long-term mortality (HR 1.10, 95% CI 1.05 to 1.16). The two-stage IPD meta-analysis indicated that CCI was not associated with LoS (HR 0.97, 95% CI 0.93 to 1.02). CONCLUSION: In this multicentre international study, patients undergoing TAVI had significant comorbid burden. We found a weak correlation between the CCI and well-established preoperative risks scores. The CCI had a moderate association with long-term mortality up to 5 years post-TAVI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".