Diamond-Forrester classification using echocardiography haemodynamic assessment in cardiac intensive care unit patients.

AIMS: We sought to determine whether the Diamond-Forrester classification using non-invasive haemodynamic measurements by 2-D and Doppler echocardiography would predict hospital mortality in cardiac intensive care unit (CICU) patients. METHODS AND RESULTS: We retrospectively analysed unique patients admitted to the CICU at Mayo Clinic Rochester from 2007 to 2018. Doppler-derived cardiac index (CI) and ratio of mitral valve E velocity to medial mitral annulus e' velocity (E/e' ratio) were used to classify patients into four profiles: Profile I (warm/dry), Profile II (warm/wet), Profile III (cold/dry), and Profile IV (cold/wet). Logistic regression was used to determine predictors of hospital mortality, and Cox proportional-hazards analysis was used to determine predictors of mortality during one year of follow-up. We included 4563 patients with a mean age of 68.3 ± 14.3 years, including 36.2% female patients. The distribution of each profile was as follows: I, 47.4%; II, 36.2%; III, 7.9%; IV, 8.5%. A total of 5.8% patients died during hospitalization, and 18.1% died by 1 year. Patients with either low CI or elevated E/e' ratio had higher in-hospital and 1 year mortality. Patients with elevated E/e' ratio (i.e. Profiles II and IV) had an increased risk of death during hospitalization and at 1 year after multivariate adjustment (adjusted hazard ratio 1.72 and 2.17 for 1 year mortality, respectively, compared with Profile I, P < 0.01). CONCLUSIONS: Simple Doppler echocardiographic assessment can be used to identify haemodynamic profiles defined by the Diamond-Forester classification in patients admitted in CICU. These profiles predict outcomes and may be used to guide therapy in critically ill patients.

Noninvasive Hemodynamic Assessment of Shock Severity and Mortality Risk Prediction in the Cardiac Intensive Care Unit.

OBJECTIVES: This study sought to define the 2-dimensional and Doppler echocardiographic hemodynamics associated with each Society for Cardiovascular Angiography and Interventions (SCAI) stage, and to determine their association with mortality. BACKGROUND: The SCAI shock stages classification stratifies mortality risk in cardiac intensive care unit (CICU) patients, but the echocardiographic and hemodynamic parameters that define these SCAI shock stages are unknown. METHODS: Unique CICU patients admitted from 2007 to 2015 who had a transthoracic echocardiogram within 1 day of CICU admission were included. Echocardiographic variables were evaluated as a function of SCAI shock stage. Multivariable logistic regression determined the association between echocardiographic parameters with adjusted hospital mortality. RESULTS: We included 5,453 patients with a median age of 69.3 years (interquartile range: 58.2 to 79.0 years) (37% women), and a median left ventricular ejection fraction (LVEF) of 50% (interquartile range: 35% to 61%). Higher SCAI shock stages were associated with lower LVEF and worse systemic hemodynamics. Hospital mortality was higher in patients with LVEF <40%, cardiac index <1.8 l/min/m2, stroke volume index <35 ml/m2, cardiac power output <0.6 W, or medial early mitral valve inflow velocity to early diastolic annular velocity (E/e') ratio >15 (particularly in SCAI shock Stages A to C). After multivariable adjustment, only stroke volume index <35 ml/m2 (adjusted odds ratio: 2.0; 95% confidence interval: 1.4 to 3.0; p < 0.001) and E/e' ratio >15 (adjusted odds ratio: 1.52; 95% confidence interval: 1.04 to 2.23; p = 0.03) remained associated with higher hospital mortality. CONCLUSIONS: Noninvasive 2-dimensional and Doppler echocardiographic parameters correlate with the SCAI shock stages and improve risk stratification for hospital mortality in CICU patients. Low stroke volume index and high E/e' ratio demonstrated the strongest association with hospital mortality.

Predictive value of individual Sequential Organ Failure Assessment sub-scores for mortality in the cardiac intensive care unit.

PURPOSE: To determine the impact of Sequential Organ Failure Assessment (SOFA) organ sub-scores for hospital mortality risk stratification in a contemporary cardiac intensive care unit (CICU) population. MATERIALS AND METHODS: Adult CICU admissions between January 1, 2007 and December 31, 2015 were reviewed. The SOFA score and organ sub-scores were calculated on CICU day 1; patients with missing SOFA sub-score data were excluded. Discrimination for hospital mortality was assessed using area under the receiver-operator characteristic curve (AUROC) values, followed by multivariable logistic regression. RESULTS: We included 1214 patients with complete SOFA sub-score data. The mean age was 67 ± 16 years (38% female); all-cause hospital mortality was 26%. Day 1 SOFA score predicted hospital mortality with an AUROC of 0.72. Each SOFA organ sub-score predicted hospital mortality (all p <0.01), with AUROC values of 0.53 to 0.67. On multivariable analysis, only the cardiovascular, central nervous system, renal and respiratory SOFA sub-scores were associated with hospital mortality (all p <0.01). A simplified SOFA score containing the cardiovascular, central nervous system and renal sub-scores had an AUROC of 0.72. CONCLUSIONS: In CICU patients with complete SOFA sub-score data, risk stratification for hospital mortality is determined primarily by the cardiovascular, central nervous system, renal and respiratory SOFA sub-scores.

Incremental costs of high intensive care utilisation in patients hospitalised with heart failure.

AIMS: Registries have reported large inter-hospital differences in intensive care unit admission rates for patients with acute heart failure, but little is known about the potential economic impact of over-admission of low-risk patients with heart failure to higher cost intensive care units. We described the variability in intensive care unit admission practices, the provision of critical care therapies, and estimated the potential national cost savings if all hospitals adopted low intensive care unit admission practices for patients admitted with heart failure. METHODS: Using a national population health dataset, we identified 349,693 heart failure admission hospitalisations with a primary diagnosis of heart failure between 2007 and 2016. Hospitals were categorised as low (first quartile), medium (second and third quartile) and high (fourth quartiles) intensive care unit utilisation. RESULTS: The mean intensive care unit admission rate was 16.4% (inter-hospital range 0.3-51%) including 5.4% in low, 14.5% in medium and 30% in high utilisation hospitals. Intensive care unit therapies in low, medium and high intensive care unit utilisation hospitals were 54.5%, 45.1% and 24.1% (P<0.001), respectively and the inhospital mortality rate was not significantly different. The proportion of hospital costs incurred by intensive care unit care was 7.8% in low, 19.8% in medium and 28.2% in high (P<0.001) admission hospitals. The potential cost savings of altering intensive care unit utilisation practices for patients with heart failure was CAN$234.8m over the study period. CONCLUSIONS: In a national cohort of patients hospitalised with heart failure, we observed that low intensive care unit utilisation centres had lower hospital costs with no differences in mortality rates. The development of standardised admission criteria for high-cost and high acuity intensive care unit beds could reduce costs to the healthcare system.

Severity of illness assessment with application of the APACHE IV predicted mortality and outcome trends analysis in an academic cardiac intensive care unit.

PURPOSE: To assess trends in life support interventions and performance of the automated Acute Physiology and Chronic Health Evaluation (APACHE) IV model at mortality prediction compared with Oxford Acute Severity of Illness Score (OASIS) in a contemporary cardiac intensive care unit (CICU). METHODS AND MATERIALS: Retrospective analysis of adults (age ≥ 18 years) admitted to CICU from January 1, 2007, through December 31, 2015. Temporal trends were assessed with linear regression. Discrimination of each risk score for hospital mortality was assessed with use of area under the receiver operating characteristic curve (AUROC) values. Calibration was assessed with Hosmer-Lemeshow goodness-of-fit test. RESULTS: The study analyzed 10,004 patients. CICU and hospital mortality rates were 5.7% and 9.1%. APACHE IV predicted death had an AUROC of 0.82 (0.81-0.84) for hospital death, compared with 0.79 for OASIS (P < .05). Calibration was better for OASIS than APACHE IV. Increases were observed in CICU and hospital lengths of stay (both P < .001), APACHE IV predicted mortality (P = .007), Charlson Comorbidity Index (P < .001), noninvasive ventilation use (P < .001), and noninvasive ventilation days (P = .02). CONCLUSIONS: Contemporary CICU patients are increasingly ill, observed in upward trends in comorbid conditions and life support interventions. APACHE IV predicted death and OASIS showed good discrimination in predicting death in this population. APACHE IV and OASIS may be useful for benchmarking and quality improvement initiatives in the CICU, the former having better discrimination.

Predictive Value of the Sequential Organ Failure Assessment Score for Mortality in a Contemporary Cardiac Intensive Care Unit Population.

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.