Dataset Information

Age and shock severity predict mortality in cardiac intensive care unit patients with and without heart failure.

ABSTRACT:

Aims

Age is an important risk factor for mortality among patients with cardiogenic shock and heart failure (HF). We sought to assess the extent to which age modified the performance of the Society for Cardiovascular Angiography and Interventions (SCAI) shock stage for in-hospital and 1 year mortality in cardiac intensive care unit (CICU) patients with and without HF.

Methods and results

We retrospectively reviewed unique admissions to the Mayo Clinic CICU during 2007-2015 and stratified patients by age and SCAI shock stage. The association between age and in-hospital mortality was analysed using multivariable logistic regression, and 1 year mortality was analysed using Cox proportional hazards analysis, both in the entire cohort and among patients with an admission diagnosis of HF or acute coronary syndrome (ACS). The final study population included 10 004 unique patients with a mean age of 67 ± 15 years, including 46.1% with HF and 43.1% with ACS. Older patients more frequently had HF and had more extensive co-morbidities, higher illness severity, more organ failure, and differential use of critical care therapies. The percentage of patients with SCAI shock stages A, B, C, D, and E were 46%, 30%, 16%, 7%, and 1%, respectively. Patients with HF were older, had greater severity of illness and higher SCAI shock stage, and had higher rates of death at all time points. In-hospital mortality occurred in 908 (9%) patients, including 549 (12%) patients with HF (61% of all hospital deaths). Age was independently associated with hospital mortality (adjusted odds ratio per 10 years 1.3, 95% confidence interval 1.2-1.4, P < 0.001) and 1 year mortality (adjusted hazard ratio per 10 years 1.2, 95% confidence interval 1.2-1.3, P < 0.001) in the overall cohort. The associations of age with both hospital mortality (adjusted odds ratio 1.6 vs. 1.3 per 10 years older) and 1 year mortality (adjusted hazard ratio 1.5 vs. 1.3 per 10 years older) were higher for patients with ACS compared with patients with HF. Older age was associated with higher adjusted hospital mortality and 1 year mortality in each SCAI shock stage (all P < 0.05). Additive increases in both hospital mortality and 1 year mortality were observed with increasing age and SCAI shock stage.

Conclusions

Age is an independent risk factor for mortality that modifies the relationship between the SCAI shock stage and mortality risk in CICU patients, providing robust risk stratification for in-hospital and 1 year mortality. Although patients with HF had a higher risk of dying, age was more strongly associated with mortality among patients with ACS.

SUBMITTER: Padkins M

PROVIDER: S-EPMC7754759 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Age and shock severity predict mortality in cardiac intensive care unit patients with and without heart failure.

Padkins Mitchell M Breen Thomas T Anavekar Nandan N van Diepen Sean S Henry Timothy D TD Baran David A DA Barsness Gregory W GW Kashani Kianoush K Holmes David R DR Jentzer Jacob C JC

ESC heart failure 20200910 6

<h4>Aims</h4>Age is an important risk factor for mortality among patients with cardiogenic shock and heart failure (HF). We sought to assess the extent to which age modified the performance of the Society for Cardiovascular Angiography and Interventions (SCAI) shock stage for in-hospital and 1 year mortality in cardiac intensive care unit (CICU) patients with and without HF.<h4>Methods and results</h4>We retrospectively reviewed unique admissions to the Mayo Clinic CICU during 2007-2015 and stra ...[more]

PMID: 32909377

Similar Datasets

Project description:BackgroundThe study set out to develop an accurate and clinically valuable prognostic nomogram to assess the risk of in-hospital death in patients with acute decompensated chronic heart failure (ADCHF) and diabetes.MethodsWe extracted clinical data of patients diagnosed with ADCHF and diabetes from the Medical Information Mart for Intensive Care III database. Risk variables were selected utilizing least absolute shrinkage and selection operator regression analysis, and were included in multivariate logistic regression and presented in nomogram. bootstrap was used for internal validation. The discriminative power and predictive accuracy of the nomogram were estimated using the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis (DCA).ResultsAmong 867 patients with ADCHF and diabetes, In-hospital death occurred in 81 (9.3%) patients. Age, heart rate, systolic blood pressure, red blood cell distribution width, shock, β-blockers, angiotensin converting enzyme inhibitors or angiotensin receptor blockers, assisted ventilation, and blood urea nitrogen were brought into the nomogram model. The calibration curves suggested that the nomogram was well calibrated. The AUC of the nomogram was 0.873 (95% CI: 0.834-0.911), which was higher that of the Simplified Acute Physiology Score II [0.761 (95% CI: 0.711-0.810)] and sequential organ failure assessment score [0.699 (95% CI: 0.642-0.756)], and Guidelines-Heart Failure score [0.782 (95% CI: 0.731-0.835)], indicating that the nomogram had better ability to predict in-hospital mortality. In addition, the internally validated C-index was 0.857 (95% CI: 0.825-0.891), which again verified the validity of this model.ConclusionsThis study constructed a simple and accurate nomogram for predicting in-hospital mortality in patients with ADCHF and diabetes, especially in those who admitted to the intensive care unit for more than 48 hours, which contributed clinicians to assess the risk and individualize the treatment of patients, thereby reducing in-hospital mortality.

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.

Dataset Information

Age and shock severity predict mortality in cardiac intensive care unit patients with and without heart failure.

Aims

Methods and results

Conclusions

Publications

Age and shock severity predict mortality in cardiac intensive care unit patients with and without heart failure.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets