Aortic valve replacement for aortic stenosis in France – influence of centers' volumes on TAVR adoption rate and outcomes
Bibliographic record
Abstract
Abstract Aims Over the last decade, transcatheter aortic valve replacement (TAVR) became extensively used, now being the recommended as first line procedure for aortic valve replacement (AVR) in selected patients' populations. It is unknown whether TAVR adoption rate and variability in outcomes is influenced by centers' volume. Methods From a French administrative hospital-discharge database, we collected all AVR performed in France between 2007 and 2019. Centers were stratified to terciles based on their annual SAVR per year per center during 2007–2009 (“pre TAVR era”). Results There was 218,489 AVRs (153,747 SAVR and 74,732 TAVR) performed in 46 centers between 2007–2019. Number of total AVR and even more so number of number of TAVR significantly and linearly increased from 2007 to 2019 in all terciles but faster in the high volume tercile (+17, +17 and +31 AVR/center/year in the low, middle and high terciles respectively, P [ANCOVA]<0.001; +11, + 19 and +33 TAVR/center/year in the low, medium and high tercile respectively, P [ANCOVA] <0.00, Figure 1). The age of patients underwent TAVR remained grossly unchanged in all three terciles, however, the Charlson index declined from 2010 to 2019 (from 1.35±1.42 to 0.65±1.04, from 1.21±1.40 to 0.65±1.05 and from 1.53±1.58 to 0.81±1.21, in the low, middle and high terciles, P for trend <0.001, 0.021, and <0.001, respectively). Charlson score in the years 2017–2019, was higher in the high than middle and low terciles (0.87±1.22, 0.76±1.11 and 0.65±1.04, respectively, P<0.0001). The in-hospital mortality rate for TAVR significantly declined from 2010 to 2019 for TAVR in all terciles (from 8.3% to 2.1%, from 7.5% to 2.5% and from 8.2% to 2.1% for low, middle and high TAVR terciles, respectively; p for trend = 0.002, 0.001 and <0.001, respectively, Figure 2). Average mortality in 2017–2019 was similar in all terciles (2.3%, 2.5% and 2.2% for low, middle and high terciles, respectively, P=0.47). After adjusting for age, sex and Charlson score, mortality was higher in the low tercile compared with middle and high terciles (OR 1.15, P<0.001, confidence interval [CI] 1.0–1.2, and OR 1.18, P<0.001, CI 1.1–1.2, respectively). Conclusions From 2007 to 2019 total AVR linearly increased, mostly due to increase in TAVR, irrespective of centers' volume, but increase rate was higher in high volume centers. A constant decline in patients risk profile, with a striking decrease in mortality rate, was observed in all volume terciles. High-volume centers patients' have higher risk profile, with adjusted mortality slightly lower than medium and low volume centers. Funding Acknowledgement Type of funding sources: None.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".