The changing landscape of aortic valve replacement in the usa.
Adolescent; Female; Humans; Male; Adult; Aged; Treatment Outcome; Risk Factors; United States; Aged 80 and over; Aortic Valve; Aortic Valve Stenosis; Transcatheter Aortic Valve Replacement
AIMS: The aim of this study was to analyse the real-world national data on parallel utilisation of transcatheter (TAVR) and surgical (SAVR) aortic valve replacement. METHODS AND RESULTS: We queried an all-payer, administrative United States in-patient database to identify all AVR hospitalisations in patients aged ≥18 years from January 2012 to December 2016 and examined the temporal changes in the number of AVR procedures and in-hospital mortality. A total of 463,675 AVRs were performed - 363,275 (78.4%) SAVR and 100,400 (21.6%) TAVR. AVR linearly increased (from 78,985 in 2012 to 103,415 in 2016; +30.9%; ptrend<0.001) largely due to a marked increase in TAVR (from 7,655 to 33,545; +338%; ptrend<0.001), whereas the absolute number of SAVRs remained relatively stable (from 71,330 to 69,870; -1%; ptrend<0.001). The number of TAVRs increased in all pre-specified age groups (<75, 75-79, 80-85, and ≥85 years; ptrend<0.001 for all). In contrast, the number of SAVRs increased modestly in patients aged <75 years (ptrend<0.001) and declined in those aged 75-79 years, 80-84 years, or ≥85 years (ptrend<0.001 for all). Age- and sex-adjusted in-hospital mortality after isolated (aOR 1.00 [0.95-1.05]; ptrend=0.96) or combined SAVR (aOR 1.01 [0.97-1.05]; ptrend=0.66) remained unchanged during the study period, whereas in-hospital mortality after TAVR declined (aOR 0.75 [0.70-0.79]; ptrend<0.001). Similar trends in in-hospital mortality were seen in the age subgroups. CONCLUSIONS: The number of AVRs markedly increased in the USA from 2012 to 2016, mainly due to the widespread adoption of TAVR, whereas the number of SAVRs remained relatively stable. In-hospital mortality after TAVR declined, whereas that after SAVR has remained unchanged.
Gupta T; Kolte D; Khera S; Goel K; Villablanca PA; Kalra A; Abbott JD; Elmariah S; Fonarow GC; Rihal CS; Garcia MJ; Weisz G; Bhatt DL
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
2019
2019-12-06
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
journalArticle
<a href="http://doi.org/10.4244/EIJ-D-19-00381" target="_blank" rel="noreferrer noopener">10.4244/EIJ-D-19-00381</a>
PMID: 31403460
Derivation and external validation of a simple risk tool to predict 30-day hospital readmissions after transcatheter aortic valve replacement.
Humans; Treatment Outcome; Risk Factors; Time Factors; Aortic Valve; Patient Readmission; Aortic Valve Stenosis; Transcatheter Aortic Valve Replacement
AIMS: Patients undergoing transcatheter aortic valve replacement (TAVR) possess a higher risk of recurrent healthcare resource utilisation due to multiple comorbidities, frailty, and advanced age. We sought to devise a simple tool to identify TAVR patients at increased risk of 30-day readmission. METHODS AND RESULTS: We used the Nationwide Readmissions Database from January 2013 to September 2015. Complex survey methods and hierarchical regression in R were implemented to create a prediction tool to determine probability of 30-day readmission. Boot-strapped internal validation and cross-validation were performed to assess model accuracy. External validation was performed using a single-centre data set. Of 39,305 patients who underwent endovascular TAVR, 6,380 (16.2%) were readmitted within 30 days. The final 30-day readmission risk prediction tool included the following variables: chronic kidney disease, end-stage renal disease on dialysis (ESRD), anaemia, chronic lung disease, chronic liver disease, atrial fibrillation, length of stay, acute kidney injury, and discharge disposition. ESRD (OR 2.11, 95% CI: 1.7-2.63), length of stay ≥5 days (OR 1.64, 95% CI: 1.50-1.79), and short-term hospital discharge disposition (OR 1.81, 95% CI: 1.2-2.7) were the strongest predictors. The c-statistic of the prediction model was 0.63. The c-statistic in the external validation cohort was 0.69. On internal calibration, the tool was extremely accurate in predicting readmissions up to 25%. CONCLUSIONS: A simple and easy-to-use risk prediction tool utilising standard clinical parameters identifies TAVR patients at increased risk of 30-day readmission. The tool may consequently inform hospital discharge planning, optimise transitions of care, and reduce resource utilisation.
Khera S; Kolte D; Deo VS; Kalra A; Gupta T; Abbott JD; Kleiman NS; Bhatt DL; Fonarow GC; Khalique OK; Kodali S; Leon MB; Elmariah S
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
2019
2019-06-20
Copyright © 2019. Published by Elsevier Inc.
journalArticle
<a href="http://doi.org/10.4244/EIJ-D-18-00954" target="_blank" rel="noreferrer noopener">10.4244/EIJ-D-18-00954</a>
PMID: 30803938