Literature DB >> 30219155

Modifiable Predictors of In-Hospital Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement.

Oluwaseun A Akinseye1, Muhammad Shahreyar1, Chioma C Nwagbara1, Mannu Nayyar1, Salem A Salem1, Mohamed Morsy1, Rami N Khouzam1, Uzoma N Ibebuogu2.   

Abstract

BACKGROUND: Transcatheter aortic valve replacement (TAVR) has become an acceptable therapy for patients with severe aortic valve stenosis at high or prohibitive surgical risk. Attempts are ongoing to validate risk prediction models for in-hospital mortality after TAVR. Our aim was to define modifiable risk factors predictive of in-hospital mortality after TAVR.
METHODS: We identified patients who underwent TAVR from the 2012 database of the National Inpatient Sample. Patients who died during the index hospitalization were compared to those that were successfully discharged. The predictors of in-hospital mortality were analyzed using multivariate logistic regression.
RESULTS: A total of 1,360 patients (mean age 81 ± 8.8 years, whites 80.1%, blacks 3.5%) had TAVR and 68 (5%) died during hospitalization (χ2 [1, n = 1,360] = 1,101.6, P < 0.001). The average length of hospital stay was 8.33 ± 6.7 days. The positive predictors of in-hospital mortality in the unadjusted model were comorbidities such as congestive heart failure, coagulopathy, fluid and electrolyte disorder, weight loss and history of drug abuse. Hypertension was a negative predictor of in-hospital mortality. Following multivariate analysis and adjustment for possible confounders, fluid and electrolyte disorder was the only significant positive predictor of in-hospital mortality (odds ratio = 1.89, CI: 1.11-3.22, P = 0.019). The odds of in-hospital mortality were reduced in patients with hypertension (odds ratio = 0.45, CI: 0.26-0.78, P = 0.004).
CONCLUSIONS: Fluid and electrolyte disturbance could be a modifiable predictor of in-hospital mortality following TAVR. Efforts should be geared towards reducing its occurrence in this patient population.
Copyright © 2018 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  In-hospital mortality; National Inpatient Sample; Risk factors; Severe aortic stenosis; Transcatheter aortic valve replacement

Mesh:

Year:  2018        PMID: 30219155     DOI: 10.1016/j.amjms.2018.04.008

Source DB:  PubMed          Journal:  Am J Med Sci        ISSN: 0002-9629            Impact factor:   2.378


  2 in total

1.  Machine learning models predict total charges and drivers of cost for transcatheter aortic valve replacement.

Authors:  Agam Bansal; Chandan Garg; Essa Hariri; Nicholas Kassis; Amgad Mentias; Amar Krishnaswamy; Samir R Kapadia
Journal:  Cardiovasc Diagn Ther       Date:  2022-08

2.  Temporal Trend, Prevalence, Predictors, and Outcomes of Pericardial Diseases in Patients Undergoing Transcatheter Aortic Valve Repair.

Authors:  Kashyap Shah; Matthew Krinock; Harshith Thyagaturu; Rezwan Munshi; Ayushi Pandya; Sarah Falta; John Hippen; Michael Durkin
Journal:  Cureus       Date:  2021-07-01
  2 in total

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