Predicting 1-Year Mortality on Admission Using the Mayo Cardiac Intensive Care Unit Admission Risk Score

Mayo Clin Proc. 2021 Sep;96(9):2354-2365. doi: 10.1016/j.mayocp.2021.01.031. Epub 2021 Aug 5.

Abstract

Objective: To determine whether the Mayo Cardiac Intensive Care Unit (CICU) Admission Risk Score (M-CARS) accurately predicts 1-year mortality.

Methods: We retrospectively reviewed adult CICU patients admitted from January 1, 2007, through April 30, 2018, and calculated M-CARS using admission data. We examined the association between admission M-CARS, as continuous and categorical variables, and 1-year mortality.

Results: This study included 12,428 unique patients with a mean age of 67.6±15.2 years (4686 [37.7%] female). A total of 2839 patients (22.8%) died within 1 year of admission, including 1149 (9.2%) hospital deaths and 1690 (15.0%) of the 11,279 hospital survivors. The 1-year survival decreased incrementally as a function of increasing M-CARS (P<.001), and all components of M-CARS were significant predictors of 1-year mortality (P<.001). The 1-year survival among hospital survivors decreased incrementally as a function of increasing M-CARS for scores below 3 (all P<.001); however, there was no further decrease in 1-year survival for hospital survivors with M-CARS of 3 or more (P=.99). The M-CARS components associated with 1-year mortality among hospital survivors included blood urea nitrogen, red blood cell distribution width, Braden skin score, and respiratory failure (all P<.001).

Conclusion: M-CARS predicted 1-year mortality among CICU admissions, with a plateau effect at high M-CARS of 3 or more for hospital survivors. Significant added predictors of 1-year mortality among hospital survivors included markers of frailty and chronic illness.

Publication types

  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cardiovascular Diseases / mortality*
  • Coronary Care Units / statistics & numerical data*
  • Female
  • Hospital Mortality
  • Humans
  • Male
  • Middle Aged
  • Proportional Hazards Models
  • Retrospective Studies
  • Risk Assessment / methods*
  • Risk Factors
  • Survival Analysis