Sex Differences in Mortality and Predictive Value of Intensive Care Unit-Based Scores when Applied to the Cardiac Intensive Care Unit

Background: Sex disparities in outcome in patients with cardiovascular disease (CVD) were previously reported. Limited data exists regarding sex differences in outcome and predictive accuracy of commonly used intensive care unit (ICU) scoring systems when applied to cardiac intensive care unit (CICU) patients.

Methods: We reviewed medical records of patients admitted to CICU of an academic tertiary care center from January 1, 2011 to December 31, 2016. We analyzed sex differences in mortality and the performance of commonly used ICU-based scoring systems in predicting overall in-hospital mortality and among major diagnoses subgroups. Calibration was assessed by Hosmer – Lemeshow (HL) test. Discrimination was assessed using the c statistic .

Results: Among 6963 patients, 2713 (39%) were women. Overall in-hospital and CICU mortality rates were similar in women and men (9.1% vs 9.4%, p=0.67 and 5.9% vs 6%, p=0.88, respectively) and across age and major diagnoses subgroups. Overall, Acute Physiology and Chronic Health Evaluation (APACHE) III and Sequential Organ Failure Assessment (SOFA) had poor calibration (HL p value <0.001), while Simplified Acute Physiology Score (SAPS) II performed better (HL p value 0.09), in both women and men. All three scores had good discrimination (c statistics >0.8). In the subgroups of women and men with acute myocardial infarction and heart failure, all three scores had good calibration (HL p >0.001) and discrimination (c statistic >0.8) while in other subgroups of major diagnoses, especially those with higher mortality, the calibration varied among scores and women vs men and discrimination was poor.

Conclusions: In an academic tertiary care CICU, no sex differences in mortality were seen across a wide range of CVD diagnoses. The mortality predictive value of the available ICU-based scoring systems is limited in women and men and variable among subgroups of diagnoses emphasizing that tailored CICU risk scores models are needed.