Multimorbidity and Mortality Models to Predict Complications Following Percutaneous Coronary Interventions

Mandeep Singh, Rajiv Gulati, Bradley R. Lewis, Zhaoliang Zhou, Mohamad Alkhouli, Paul Andrew Friedman, Malcolm R. Bell

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Previous percutaneous coronary intervention risk models were focused on single outcome, such as mortality or bleeding, etc, limiting their applicability. Our objective was to develop contemporary percutaneous coronary intervention risk models that not only determine in-hospital mortality but also predict postprocedure bleeding, acute kidney injury, and stroke from a common set of variables. Methods: We built risk models using logistic regression from first percutaneous coronary intervention for any indication per patient (n=19 322, 70.6% with acute coronary syndrome) using the Mayo Clinic registry from January 1, 2000 to December 31, 2016. Approval for the current study was obtained from the Mayo Foundation Institutional Review Board. Patients with missing outcomes (n=4183) and those under 18 (n=10) were removed resulting in a sample of 15 129. We built both models that included procedural and angiographic variables (Models A) and precatheterization model (Models B). Results: Death, bleeding, acute kidney injury, and stroke occurred in 247 (1.6%), 650 (4.3%), 1184 (7.8%), and 67 (0.4%), respectively. The C statistics from the test dataset for models A were 0.92, 0.70, 0.77, and 0.71 and for models B were 0.90, 0.67, 0.76, and 0.71 for in-hospital death, bleeding, acute kidney injury, and stroke, respectively. Bootstrap analysis indicated that the models were not overfit to the available dataset. The probabilities estimated from the models matched the observed data well, as indicated by the calibration curves. The models were robust across many subgroups, including women, elderly, acute coronary syndrome, cardiogenic shock, and diabetes. Conclusions: The new risk scoring models based on precatheterization variables and models including procedural and angiographic variables accurately predict in-hospital mortality, bleeding, acute kidney injury, and stroke. The ease of its application will provide useful prognostic and therapeutic information to both patients and physicians.

Original languageEnglish (US)
Pages (from-to)577-586
Number of pages10
JournalCirculation: Cardiovascular Interventions
Volume15
Issue number7
DOIs
StatePublished - Jul 1 2022

Keywords

  • acute coronary syndrome
  • morbidity
  • mortality
  • percutaneous coronary interventions
  • risk

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

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