Affiliation:
1. Department of Cardiovascular Medicine Mayo Clinic Rochester MN
2. Division of Pulmonary and Critical Care Medicine Department of Internal Medicine Mayo Clinic Rochester MN
3. Department of Health Sciences Research Mayo Clinic Rochester MN
4. Department of Anesthesiology and Perioperative Medicine Mayo Clinic Rochester MN
5. TIMI Study Group Cardiovascular Division Brigham and Women's Hospital and Harvard Medical School Boston MA
Abstract
Background
There are no risk scores designed specifically for mortality risk prediction in unselected cardiac intensive care unit (
CICU
) patients. We sought to develop a novel
CICU
‐specific risk score for prediction of hospital mortality using variables available at the time of
CICU
admission.
Methods and Results
A database of
CICU
patients admitted from January 1, 2007 to April 30, 2018 was divided into derivation and validation cohorts. The top 7 predictors of hospital mortality were identified using stepwise backward regression, then used to develop the Mayo
CICU
Admission Risk Score (M‐
CARS
), with integer scores ranging from 0 to 10. Discrimination was assessed using area under the receiver‐operator curve analysis. Calibration was assessed using the Hosmer–Lemeshow statistic. The derivation cohort included 10 004 patients and the validation cohort included 2634 patients (mean age 67.6 years, 37.7% females). Hospital mortality was 9.2%. Predictor variables included in the M‐
CARS
were cardiac arrest, shock, respiratory failure, Braden skin score, blood urea nitrogen, anion gap and red blood cell distribution width at the time of
CICU
admission. The M‐
CARS
showed a graded relationship with hospital mortality (odds ratio 1.84 for each 1‐point increase in M‐
CARS
, 95%
CI
1.78–1.89). In the validation cohort, the M‐
CARS
had an area under the receiver‐operator curve of 0.86 for hospital mortality, with good calibration (
P
=0.21). The 47.1% of patients with M‐
CARS
<2 had hospital mortality of 0.8%, and the 5.2% of patients with M‐
CARS
>6 had hospital mortality of 51.6%.
Conclusions
Using 7 variables available at the time of
CICU
admission, the M‐
CARS
can predict hospital mortality in unselected
CICU
patients with excellent discrimination.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Cardiology and Cardiovascular Medicine
Cited by
49 articles.
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