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Background: One-time assessment of the Society for Cardiovascular Angiography and Interventions (SCAI) shock classification robustly predicts mortality in the cardiac intensive care unit (CICU). We sought to determine whether serial SCAI shock classification could improve risk stratification., Methods and Results: Unique admissions to a single academic level 1 CICU from 2015 to 2018 were included in this retrospective cohort study. Electronic health record data were used to assign the SCAI shock stage during 4-hour blocks of the first 24 hours of CICU admission. Shock was defined as hypoperfusion (SCAI shock stage C, D, or E). In-hospital death was evaluated using logistic regression. Among 2918 unique CICU patients, 1537 (52.7%) met criteria for shock during ≥1 block, and 266 (9.1%) died in the hospital. The SCAI shock stage on admission was: A, 37.6%; B, 31.5%; C, 25.9%; D, 1.8%; and E, 3.3%. Patients who met SCAI criteria for shock on admission (first 4 hours) and those with worsening SCAI shock stage after admission were at higher risk for in-hospital death. Each higher admission (adjusted odds ratio, 1.36 [95% CI, 1.18-1.56]; area under the receiver operating characteristic curve, 0.70), maximum (adjusted odds ratio, 1.59 [95% CI, 1.37-1.85]; area under the receiver operating characteristic curve, 0.73) and mean (adjusted odds ratio, 2.42 [95% CI, 1.99-2.95]; area under the receiver operating characteristic curve, 0.78) SCAI shock stage was incrementally associated with a higher in-hospital mortality rate. Discrimination was highest for the mean SCAI shock stage ( P <0.05). Each additional 4-hour block meeting SCAI criteria for shock predicted a higher mortality rate (adjusted odds ratio, 1.15 [95% CI, 1.07-1.24])., Conclusions: Dynamic assessment of shock using serial SCAI shock classification assignment can improve mortality risk stratification in CICU patients by quantifying the magnitude and duration of shock.

Background: Shock and preshock are defined on the basis of the presence of hypotension, hypoperfusion, or both. We sought to determine the hemodynamic underpinnings of shock and preshock noninvasively using transthoracic echocardiography (TTE)., Methods and Results: We included Mayo Clinic cardiac intensive care unit patients from 2007 to 2015 with TTE within 1 day of admission. Hypotension and hypoperfusion at the time of cardiac intensive care unit admission were used to define 4 groups. TTE findings were evaluated across these groups, and in-hospital mortality was evaluated according to TTE findings in each group. We included 5375 patients with a median age of 69.2 years (36.8% women). The median left ventricular ejection fraction was 50%. Groups based on hypotension and hypoperfusion were assigned as follows: no hypotension or hypoperfusion, 59.7%; isolated hypotension, 15.3%; isolated hypoperfusion, 16.4%; and both hypotension and hypoperfusion, 8.7%. Most TTE variables of interest varied across these groups, with worse biventricular function, lower forward flow, and higher filling pressures as the degree of hemodynamic compromise increased. In-hospital mortality occurred in 8.2%, and inpatient deaths had more TTE parameter abnormalities. In-hospital mortality increased with the degree of hemodynamic compromise, and a marked gradient in in-hospital mortality was observed when the clinical classification of shock and preshock was combined with TTE findings reflecting worse biventricular function, lower forward flow, or higher filling pressures., Conclusions: Substantial differences in cardiac function are observed between cardiac intensive care unit patients with preshock and shock using TTE, and the combination of the clinical and TTE hemodynamic assessment provides robust mortality risk stratification.

Background Impaired right ventricular (RV) pulmonary artery coupling has been associated with higher mortality in patients with chronic heart disease, but few studies have examined this metric in critically ill patients. We sought to evaluate the association between RV pulmonary artery coupling, defined by the ratio of tricuspid annular peak systolic tissue Doppler velocity (TASV)/estimated RV systolic pressure (RVSP), and mortality in cardiac intensive care unit patients. Methods and Results Using a database of unique cardiac intensive care unit admissions from 2007 to 2018, we included patients with TASV/RVSP ratio measured within 1 day of hospitalization. Hospital mortality was analyzed using multivariable logistic regression, and 1-year mortality was analyzed using multivariable Cox proportional-hazards analysis. We included 4259 patients with a mean age of 69±15 years (40.1% women). Admission diagnoses included acute coronary syndrome in 56%, heart failure in 52%, respiratory failure in 24%, and cardiogenic shock in 12%. The mean TASV/RVSP ratio was 0.31±0.14, and in-hospital mortality occurred in 7% of patients. Higher TASV/RVSP ratio was associated with lower in-hospital mortality (adjusted unit odds ratio, 0.68 per each 0.1-unit higher ratio; 95% CI, 0.58-0.79; P <0.001) and lower 1-year mortality among hospital survivors (adjusted unit hazard ratio, 0.83 per each 0.1-unit higher ratio; 95% CI, 0.77-0.90; P <0.001). Stepwise decreases in hospital and 1-year mortality were observed in each higher TASV/RVSP quintile. The TASV/RVSP ratio remained associated with mortality after adjusting for left ventricular systolic and diastolic function. Conclusions A low TASV/RVSP ratio is associated with increased short-term and long-term mortality among cardiac intensive care unit patients, emphasizing importance of impaired RV pulmonary artery coupling as a determinant of poor prognosis. Further study is required to determine whether interventions to optimize RV pulmonary artery coupling can improve outcomes.

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.

Background Abnormal serum sodium levels have been associated with higher mortality among patients with acute coronary syndromes and heart failure. We sought to describe the association between sodium levels and mortality among unselected cardiac intensive care unit (CICU) patients. Methods and Results We retrospectively reviewed consecutive adult patients admitted to our cardiac intensive care unit from 2007 to 2015. Hyponatremia and hypernatremia were defined as admission serum sodium <135 and >145 mEq/L, respectively. In-hospital mortality was assessed by multivariable regression, and postdischarge mortality was evaluated by Cox proportional-hazards analysis. We included 9676 patients with a mean age of 68±15 years (37.5% females). Hyponatremia occurred in 1706 (17.6%) patients, and hypernatremia occurred in 322 (3.3%) patients; these groups had higher illness severity and a greater number of comorbidities. Risk of hospital mortality was higher with hyponatremia (15.5% versus 7.5%; unadjusted odds ratio, 2.41; 95% CI, 2.06-2.82; P <0.001) or hypernatremia (17.7% versus 8.6%; unadjusted odds ratio, 2.82; 95% CI, 2.09-3.80; P <0.001), with a J-shaped relationship between admission sodium and mortality. After multivariate adjustment, only hyponatremia was significantly associated with in-hospital mortality (adjusted odds ratio, 1.42; 95% CI, 1.14-1.76; P =0.002). Among hospital survivors, risk of postdischarge mortality was higher in patients with hyponatremia (adjusted hazard ratio, 1.28; 95% CI, 1.17-1.41; P <0.001) or hypernatremia (adjusted hazard ratio, 1.36; 95% CI, 1.12-1.64; P =0.002). Conclusions Hyponatremia and hypernatremia on admission to the cardiac intensive care unit are associated with increased unadjusted short- and long-term mortality. Further studies are needed to determine whether correcting abnormal sodium levels can improve outcomes in cardiac intensive care unit patients.

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.

Background: Optimal methods of mortality risk stratification in patients in the cardiac intensive care unit (CICU) remain uncertain. We evaluated the ability of the Sequential Organ Failure Assessment (SOFA) score to predict mortality in a large cohort of unselected patients in the CICU., Methods and Results: Adult patients admitted to the CICU from January 1, 2007, to December 31, 2015, at a single tertiary care hospital were retrospectively reviewed. SOFA scores were calculated daily, and Acute Physiology and Chronic Health Evaluation (APACHE)-III and APACHE-IV scores were calculated on CICU day 1. Discrimination of hospital mortality was assessed using area under the receiver-operator characteristic curve values. We included 9961 patients, with a mean age of 67.5±15.2 years; all-cause hospital mortality was 9.0%. Day 1 SOFA score predicted hospital mortality, with an area under the receiver-operator characteristic curve value of 0.83; area under the receiver-operator characteristic curve values were similar for the APACHE-III score, and APACHE-IV predicted mortality ( P >0.05). Mean and maximum SOFA scores over multiple CICU days had greater discrimination for hospital mortality ( P <0.01). Patients with an increasing SOFA score from day 1 and day 2 had higher mortality. Patients with day 1 SOFA score <2 were at low risk of mortality. Increasing tertiles of day 1 SOFA score predicted higher long-term mortality ( P <0.001 by log-rank test)., Conclusions: The day 1 SOFA score has good discrimination for short-term mortality in unselected patients in the CICU, which is comparable to APACHE-III and APACHE-IV. Advantages of the SOFA score over APACHE include simplicity, improved discrimination using serial scores, and prediction of long-term mortality., (© 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.)