Temporal Changes in Mortality After Transcatheter and Surgical Aortic Valve Replacement: Retrospective Analysis of US Medicare Patients (2012–2019)
Notice bibliographique
Résumé
Background The treatment of aortic stenosis is evolving rapidly. Pace of change in the care of patients undergoing transcatheter aortic valve replacement (TAVR) and surgical aortic valve replacement (SAVR) differs. We sought to determine differences in temporal changes in 30-day mortality, 30-day readmission, and length of stay after TAVR and SAVR. Methods and Results We conducted a retrospective cohort study of patients treated in the United States between 2012 and 2019 using data from the Medicare Data Set Analytic File 100% Fee for Service database. We included consecutive patients enrolled in Medicare Parts A and B and aged ≥65 years who had SAVR or transfemoral TAVR. We defined 3 study cohorts, including all SAVR, isolated SAVR (without concomitant procedures), and elective isolated SAVR and TAVR. The primary end point was 30-day mortality; secondary end points were 30-day readmission and length of stay. Statistical models controlled for patient demographics, frailty measured by the Hospital Frailty Risk Score, and comorbidities measured by the Elixhauser Comorbidity Index (ECI). Cox proportional hazard models were developed with TAVR versus SAVR as the main covariates with a 2-way interaction term with index year. We repeated these analyses restricted to full aortic valve replacement hospitals offering both SAVR and TAVR. The main study cohort included 245 269 patients with SAVR and 188 580 patients with TAVR, with mean±SD ages 74.3±6.0 years and 80.7±6.9 years, respectively, and 36.5% and 46.2% female patients, respectively. Patients with TAVR had higher ECI scores (6.4±3.6 versus 4.4±3) and were more frail (55.4% versus 33.5%). Total aortic valve replacement volumes increased 61% during the 7-year span; TAVR volumes surpassed SAVR in 2017. The magnitude of mortality benefit associated with TAVR increased until 2016 in the main cohort (2012: hazard ratio [HR], 0.76 [95% CI, 0.67-0.86]; 2016: HR, 0.39 [95% CI, 0.36-0.43]); although TAVR continued to have lower mortality rates from 2017 to 2019, the magnitude of benefit over SAVR was attenuated. A similar pattern was seen with readmission, with a lower risk of readmission from 2012 to 2016 for patients with TAVR (2012: HR, 0.68 [95% CI, 0.63-0.73]; 2016: HR, 0.43 [95% CI, 0.41-0.45]) followed by a lesser difference from 2017 to 2019. Year over year, TAVR was associated with increasingly shorter lengths of stay compared with SAVR (2012: HR, 1.91 [95% CI, 1.84-1.98]; 2019: HR, 5.34 [95% CI, 5.22-5.45]). These results were consistent in full aortic valve replacement hospitals. Conclusions The rate of improvement in TAVR outpaced SAVR until 2016, with the recent presence of U-shaped phenomena suggesting a narrowing gap between outcomes. Future longitudinal research is needed to determine the long-term implications of lowering risk profiles across treatment options to guide case selection and clinical care.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».