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Utilizing Percutaneous Ventricular Assist Devices in Acute Myocardial Infarction Complicated by Cardiogenic Shock
Published on: June 12, 2021
Impact of comorbidity burden on outcome in patients with cardiogenic shock: A Cardiogenic Shock Working Group
Jonas Sundermeyer1,2, Song Li3, Van-Khue Ton4
1The Cardiovascular Center, Tufts Medical Center, Boston, MA, USA.
Insights
Comorbidity burden significantly impacts cardiogenic shock (CS) outcomes, especially in heart failure-related CS. Identifying high-risk comorbidity patterns is crucial for improving patient survival and clinical decision-making in CS management.
Area of Science:
- Cardiology
- Clinical Research
- Public Health
Background:
- Comorbidity burden is a key factor influencing patient outcomes.
- The prognostic impact of comorbidities on cardiogenic shock (CS) and its subtypes is not fully understood.
- Characterizing comorbidity patterns in CS is essential for risk stratification.
Purpose of the Study:
- To determine the prevalence and distribution of comorbidities in CS patients.
- To assess the impact of comorbidities on in-hospital mortality across CS subtypes.
- To identify high-risk comorbidity patterns in all-cause, acute myocardial infarction-related CS (AMI-CS), and heart failure-related CS (HF-CS).
Main Methods:
- Analysis of 6815 patients from the Cardiogenic Shock Working Group (CSWG) registry (2020-2024).
- Utilized adjusted logistic regression models to evaluate the impact of comorbidities on in-hospital mortality.
- Developed the Comorbidity Risk Index for Cardiogenic Shock (COMRI-CS) to quantify comorbidity-associated mortality risk.
Main Results:
- High comorbidity prevalence (89.3% with ≥1, 64.4% with ≥3 comorbidities) was observed.
- In-hospital mortality increased with comorbidity burden in both AMI-CS and HF-CS.
- A high comorbidity burden independently increased mortality risk by 51% in AMI-CS and 122% in HF-CS. Each COMRI-CS point correlated with a ~5.5% increase in mortality.
Conclusions:
- Comorbidity burden is highly prevalent in CS, varies by subtype, and is an independent predictor of mortality.
- Integrating comorbidity assessment into early CS risk stratification can improve clinical decision-making.
- Distinct high-risk comorbidity profiles exist across different CS subtypes.
Aims:
Comorbidity burden is a major determinant of outcomes. Its prognostic impact on cardiogenic shock (CS) across CS subtypes remains insufficiently characterized. We aimed to characterize the prevalence and distribution of comorbidities in CS, assess their impacts on outcomes, and identify high-risk comorbidity patterns in all-cause, acute myocardial infarction-related (AMI-CS) and heart failure-related CS (HF-CS).
Methods And Results:
Cardiogenic shock patients from the multicentre Cardiogenic Shock Working Group (CSWG) registry (2020-2024) were analysed. We used adjusted logistic regression models to assess the impact of comorbidities individually, in combination, and as a cumulative burden on in-hospital mortality. We developed the Comorbidity Risk Index for Cardiogenic Shock (COMRI-CS) to capture the association between comorbidities and CS mortality. Among 6815 patients (26.5% AMI-CS, 53.6% HF-CS), 6087 (89.3%) presented with ≥1 comorbidity, and 4390 (64.4%) with ≥3 comorbidities. In-hospital mortality increased with comorbidity burden (AMI-CS: 35.4%, 39.6%, 47.1% with 1-3, 4-6, ≥7 comorbidities, respectively; HF-CS: 19.6%, 24.9%, 27.5%, respectively). A high comorbidity burden was independently associated with a 51% higher relative mortality risk in AMI-CS (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.02-2.23, p = 0.037), and a more pronounced increase of 122% in HF-CS (OR 2.22, 95% CI 1.49-3.37, p < 0.001). Distinct high-risk comorbidities and combinations were identified, varying across CS subtypes. With each COMRI-CS point, in-hospital mortality increased by ~5.5%.
Conclusions:
In this large real-world CS cohort, comorbidity burden was highly prevalent, varied across subtypes, and was independently associated with mortality. Integrating chronic conditions into early CS risk stratification may enhance clinical decision-making in CS management.
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