Heart Failure Hospitalization Following Surgical or Transcatheter Aortic Valve Implantation in Low-Risk Aortic Stenosis
Bibliographic record
Abstract
AIMS: In low-risk patients with severe aortic stenosis (AS), sutureless surgical aortic valve replacement (SU-SAVR) may be an alternative to transcatheter aortic valve implantation (TAVI). The risk of heart failure hospitalization (HFH) after aortic valve replacement (AVR) in this population is incompletely characterized. This study aims to investigate the incidence, predictors, and outcomes of HFH in patients undergoing SU-SAVR versus TAVI. METHODS AND RESULTS: Patients referred for AVR between 2013 and 2020 at two centres were consecutively included. The decision for SU-SAVR or TAVI was determined by a multidisciplinary Heart Team. Cox regression and competing risk analysis were conducted to assess adverse events. Of 594 patients (mean age 77.5 ± 6.4, 59.8% male), 424 underwent SU-SAVR, while 170 underwent TAVI. Following a mean follow-up of 34.1 ± 23.1 months, HFH occurred in 112 (27.8%) SU-SAVR patients and in 8 (4.8%) TAVI patients (P < 0.001). The SU-SAVR cohort exhibited higher all-cause mortality (138 [32.5%] patients compared with 30 [17.6%] in the TAVI cohort [P < 0.001]). These differences remained significant after sensitivity analyses with 1:1 propensity score matching for baseline variables. SU-SAVR with HFH was associated with increased all-cause mortality (61.6% vs. 23.1%, P < 0.001). Independent associates of HFH in SU-SAVR patients included diabetes, atrial fibrillation, chronic obstructive pulmonary disease, lower glomerular filtration rate and lower left ventricular ejection fraction. SU-SAVR patients with HFH had a 12-month LVEF of 59.4 ± 12.7. CONCLUSIONS: In low-risk AS, SU-SAVR is associated with a higher risk of HFH and all-cause mortality compared to TAVI. In patients with severe AS candidate to SU-SAVR or TAVI, TAVI may be the preferred intervention.
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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) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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".