A Readmission Risk Score for Transcatheter Aortic Valve Replacement: An Analysis of 200,000 Patients

被引:2
作者
Aranda-Michel, Edgar [1 ]
Kilner, Dustin [2 ]
Toma, Catalin [2 ]
Serna-Gallegos, Derek [1 ,2 ]
Yousef, Sarah [1 ]
Brown, James [1 ]
Diaz-Castrillon, Carlos E. [1 ]
Makani, Amber [2 ]
Sultan, Ibrahim [1 ,2 ,3 ]
机构
[1] Univ Pittsburgh, Dept Cardiothorac Surg, Div Cardiac Surg, Pittsburgh, PA USA
[2] Univ Pittsburgh, Heart & Vasc Inst, Med Ctr, Pittsburgh, PA USA
[3] Univ Pittsburgh, Heart & Vasc Inst, Ctr Heart Valve Dis, Med Ctr,Dept Cardiothorac Surg,Div Cardiac Surg, 5200 Ctr Ave,Suite 715, Pittsburgh, PA 15232 USA
关键词
HCUP; National database; Risk score; 30 day readmissions; TAVR; Endovascular Valvular replacement; Valvular disease; MORTALITY;
D O I
10.1016/j.carrev.2023.02.025
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective: The objective of this study was to leverage a national database of TAVR procedures to create a risk model for 30-day readmissions. Methods: The National Readmissions Database was reviewed for all TAVR procedures from 2011 to 2018. Previous ICD coding paradigms created comorbidity and complication variables fromthe index admission. Univariate analysis included any variables with a P-value of <= 0.2. A bootstrapped mixed-effects logistic regression was run using the hospital ID as a randomeffect variable. By bootstrapping, a more robust estimate of the variables' effect can be generated, reducing the risk of model overfitting. The odds ratio of variables with a P-value <0.1 was turned into a risk score following the Johnson scoring method. A mixed- effect logistic regression was run using the total risk score, and a calibration plot of the observed to expected readmission was generated. Results: A total of 237,507 TAVRswere identified, with an in-hospitalmortality of 2.2 %. A total of 17.4 % % of TAVR patients were readmitted within 30 days. The median age was 82with 46 % of the population being women. The risk score values ranged from-3 to 37 corresponding to a predicted readmission risk between 4.6 % and 80.4 %, respectively. Discharge to a short-termfacility and being a resident of the hospital statewere themost significant predictors of readmission. The calibration plot shows good agreement between the observed and expected readmission rates with an underestimation at higher probabilities. Conclusion: The readmission risk model agreeswith the observed readmissions throughout the study period. The most significant risk factorswere being a resident of the hospital state and discharge to a short-termfacility. This suggests that using this risk score in conjunction with enhanced post-operative care in these patients could reduce readmissions and associated hospital costs, improving outcomes. (c) 2023 Elsevier Inc. All rights reserved.
引用
收藏
页码:8 / 12
页数:5
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