Dataset Information

Sex differences in crude mortality rates and predictive value of intensive care unit-based scores when applied to the cardiac intensive care unit.

ABSTRACT:

Background

Limited data exists regarding sex differences in outcome and predictive accuracy of intensive care unit-based scoring systems when applied to cardiac intensive care unit patients.

Methods

We reviewed medical records of patients admitted to cardiac intensive care unit from 1 January 2011-31 December 2016. Sex differences in mortality rates and the performance of intensive care unit-based scoring systems in predicting in-hospital mortality were analyzed. Calibration was assessed by the Hosmer-Lemeshow test and locally weighted scatterplot smoothing curves. Discrimination was assessed using the c statistic and receiver-operating characteristic curve.

Results

Among 6963 patients, 2713 (39%) were women. Overall in-hospital and cardiac intensive care unit 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 in age and major diagnosis subgroups. Of the scoring systems, Acute Physiology and Chronic Health Evaluation III and Sequential Organ Failure Assessment had poor calibration (Hosmer-Lemeshow p value <0.001), while Simplified Acute Physiology Score II performed better (Hosmer-Lemeshow p value 0.09), in both women and men. All scores had good discrimination (C statistics >0.8). In the subgroups of acute myocardial infarction and heart failure patients, all scores had good calibration (Hosmer-Lemeshow p>0.001) and discrimination (C statistic >0.8) while in diagnosis subgroups with highest mortality, the calibration varied among scores and by sex, and discrimination was poor.

Conclusions

No sex differences in mortality were seen in cardiac intensive care unit patients. The mortality predictive value of intensive care unit-based scores is limited in both sexes and variable among different subgroups of diagnoses.

SUBMITTER: Herscovici R

PROVIDER: S-EPMC8079168 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background The cardiac intensive care unit (CICU) population is no longer composed of only patients with acute coronary syndromes, and includes those with acute heart failure and multiple comorbidities. We hypothesized that the GWTG-HF (Get With The Guidelines-Heart Failure) risk score that predicts inpatient mortality in hospitalized patients with heart failure would predict mortality in CICU patients. Methods and Results We retrospectively analyzed CICU patients at a tertiary care hospital from 2007 to 2015. The GWTG-HF risk score was calculated at CICU admission. As a secondary analysis, the EFFECT (Enhanced Feedback for Effective Cardiac Treatment), OPTIMIZE-HF (Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure), and ADHERE (Acute Decompensated Heart Failure National Registry) risk scores were calculated. Kaplan-Meier survival analysis and the area under the receiver operating characteristic curve value were determined for inpatient and 1-year mortality. The GWTG-HF risk score was calculated in 9532 (95%) patients, with a median value of 40 (interquartile range, 35-47). Inpatient mortality occurred in 824 (8.6%) patients, and 2075 (21.8%) patients died by 1 year. Patients who died in hospital had a significantly higher mean GWTG-HF score (47.7 versus 40.2; P<0.001). Inpatient and 1-year mortality increased in each GWTG-HF risk score quartile (P<0.0001). Discrimination of the GWTG-HF, EFFECT, OPTIMIZE-HF, and ADHERE risk scores was assessed using area under the receiver operating characteristic curve values for hospital mortality, and were similar for all risk scores (0.72-0.74; P>0.05). The Hosmer-Lemeshow statistic suggested poor calibration for hospital mortality by the GWTG-HF risk score (P<0.001). Conclusions The GWTG-HF risk score and other heart failure prediction tools demonstrate good discrimination for inpatient and 1-year mortality in a heterogeneous cohort of CICU patients. Our study emphasizes that prognostic variables overlap in cardiac patients, regardless of the admission diagnosis.