Cardiovascular outcomes and trends of Transcatheter vs. Surgical aortic valve replacement among octogenarians with heart failure: A Propensity Matched national cohort analysis
Bibliographic record
Abstract
Background: Heart failure (HF) is a complex clinical syndrome with symptoms and signs that result from any structural or functional impairment of ventricular filling or ejection of blood. Limited data is available regarding the in-hospital outcomes of TAVR compared to SAVR in the octogenarian population with HF. Methods: The National Inpatient Sample (NIS) database was used to compare TAVR versus SAVR among octogenarians with HF. The primary outcome was in-hospital mortality. The secondary outcome included acute kidney injury (AKI), cerebrovascular accident (CVA), post-procedural stroke, major bleeding, blood transfusions, sudden cardiac arrest (SCA), cardiogenic shock (CS), and mechanical circulatory support (MCS). Results: A total of 74,995 octogenarian patients with HF (TAVR-HF n = 64,890 (86.5%); SAVR n = 10,105 (13.5%)) were included. The median age of patients in TAVR-HF and SAVR-HF was 86 (83-89) and 82 (81-84) respectively. TAVR-HF had lower percentage in-hospital mortality (1.8% vs. 6.9%;p < 0.001), CVA (2.5% vs. 3.6%; p = 0.009), SCA (9.9% vs. 20.2%; p < 0.001), AKI (17.4% vs. 40.8%); p < 0.001), major transfusion (26.4% vs 67.3%; p < 0.001), CS (1.8% vs 9.8%; p < 0.001), and MCS (0.8% vs 7.3%; p < 0.001) when compared to SAVR-HF. Additionally, post-procedural stroke and major bleeding showed no significant difference. The median unmatched total charges for TAVR-HF and SAVR-HF were 194,561$ and 246,100$ respectively. Conclusion: In this nationwide observational analysis, TAVR is associated with an improved safety profile for octogenarians with heart failure (both preserved and reduced ejection fraction) compared to SAVR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".