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The free energy change for a reaction that occurs under the standard conditions of 1 bar pressure and at 298 K is called the standard free energy change. Since free energy is a state function, its value depends only on the conditions of the initial and final states of the system. A convenient and common approach to the calculation of free energy changes for physical and chemical reactions is by use of widely available compilations of standard state thermodynamic data. One method involves the...
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A buffer can prevent a sudden drop or increase in the pH of a solution after the addition of a strong acid or base up to its buffering capacity; however, such addition of a strong acid or base does result in the slight pH change of the solution. The small pH change can be calculated by determining the resulting change in the concentration of buffer components, i.e., a weak acid and its conjugate base or vice versa. The concentrations obtained using these stoichiometric calculations can be used...
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Four-Dimensional Computed Tomography-Guided Valve Sizing for Transcatheter Pulmonary Valve Replacement
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Calculating Risk for Poor Outcomes After Transcatheter Aortic Valve Replacement.

Suzanne V Arnold1

  • 1Saint Luke's Mid America Heart Institute/University of Missouri-Kansas City, Kansas City, MO.

Journal of Clinical Outcomes Management : JCOM
|August 21, 2019
PubMed
Summary
This summary is machine-generated.

Understanding transcatheter aortic valve replacement (TAVR) risks is crucial. Key patient factors like functional status and comorbidities significantly impact TAVR outcomes and recovery expectations.

Keywords:
TAVRaortic valve stenosispostoperative complicationsrisk factors

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Area of Science:

  • Cardiology
  • Interventional Cardiology
  • Health Outcomes Research

Background:

  • Transcatheter aortic valve replacement (TAVR) is a common procedure for aortic stenosis.
  • Accurate risk stratification is essential for patient selection and outcome prediction.
  • Existing risk models have limitations in guiding TAVR versus surgical decisions.

Purpose of the Study:

  • To review available tools for TAVR risk assessment.
  • To identify knowledge gaps in TAVR risk estimation.
  • To inform patient expectations regarding TAVR outcomes.

Main Methods:

  • Literature review of TAVR risk prediction models.
  • Analysis of validated risk models for short-term and long-term outcomes.

Main Results:

  • Two American College of Cardiology models estimate short-term mortality risk (6-variable clinical, 41-variable quality improvement).
  • Neither model should guide TAVR vs. surgical valve replacement decisions.
  • A validated model predicts 1-year mortality or poor quality of life post-TAVR.
  • Key risk factors include poor functional status, home oxygen use, renal insufficiency, atrial fibrillation, ADL dependencies, and dementia.

Conclusions:

  • Patient factors significantly influence TAVR outcomes.
  • Understanding these factors is vital for setting realistic recovery expectations.
  • Discussing risks and recovery uncertainty with patients and families is recommended.