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Predicting heart failure mortality using the Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI)
Usama Sikandar1,2,3, Kasper Bonnesen1,2, Uffe Heide-Jørgensen1,2
1Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus N, Denmark.
Insights
The Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI) effectively predicts all-cause mortality in heart failure (HF) patients. While it improves risk prediction for all-cause mortality, it does not significantly enhance prediction for cardiovascular mortality in HF.
Area of Science:
- Cardiology
- Public Health
- Biostatistics
Background:
- Comorbidities significantly increase mortality risk in patients with congestive heart failure (HF).
- Comorbidity indices are crucial for standardizing the assessment of comorbidity burden and predicting patient prognosis.
- The Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI) is a validated index, but its utility in HF populations requires investigation.
Purpose of the Study:
- To evaluate the discriminatory ability of the Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI) in predicting mortality among patients diagnosed with heart failure (HF).
- To compare the performance of DANCAMI against established comorbidity indices, namely the Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Index (ECI), in the HF cohort.
Main Methods:
- A population-based cohort study including 311,628 adult Danish patients diagnosed with first-time HF between 1995 and 2020.
- Logistic regression analysis was employed to calculate the area under the receiver operating characteristic curve (AUC) for 30-day, 1-year, and 10-year all-cause and cardiovascular mortality.
- AUCs were compared for models with baseline demographics (age, sex) alone, and with the addition of DANCAMI, CCI, or ECI.
Main Results:
- DANCAMI demonstrated higher AUCs than the baseline model for all-cause mortality at 30 days (0.688 vs. 0.662), 1 year (0.715 vs. 0.680), and 10 years (0.840 vs. 0.810).
- For cardiovascular mortality, AUCs were comparable between DANCAMI and the baseline model across all time points.
- AUCs for CCI and ECI were similar to DANCAMI for both all-cause and cardiovascular mortality at all evaluated time intervals.
Conclusions:
- Incorporating DANCAMI into risk prediction models significantly improves the discrimination of short-term and long-term all-cause mortality in heart failure patients.
- DANCAMI did not provide additional discriminatory value for cardiovascular mortality beyond baseline demographic information.
- The study suggests DANCAMI is a valuable tool for assessing all-cause mortality risk in HF, with performance comparable to CCI and ECI.
Background:
Patients with congestive heart failure (HF) are often burdened with comorbidities that increase mortality. Comorbidity indices provide a standardised method to measure comorbidity burden and predict prognosis. We aimed to investigate whether the Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI) can discriminate mortality in patients with HF.
Methods:
We conducted a population-based cohort study of all adult Danish patients with first-time HF during 1995-2020 (N = 311,628). We used logistic regression to calculate the area under the receiver operating characteristic curve (AUC) for cardiovascular and all-cause mortality within 30 days, 1 year, and 10 years of diagnosis. The AUCs were computed for a model including age and sex (baseline) and models also including the DANCAMI, the Charlson Comorbidity Index (CCI), or the Elixhauser Comorbidity Index (ECI).
Results:
For all-cause mortality, the AUCs were higher for the DANCAMI than for the baseline model (30-day: 0.688 vs. 0.662; 1-year: 0.715 vs. 0.680; 10-year: 0.840 vs. 0.810). For cardiovascular mortality, the AUCs were comparable between the DANCAMI and the baseline model (30-day: 0.683 vs. 0.676; 1-year: 0.690 vs. 0.684; 10-year: 0.659 vs. 0.658). For both 30-day, 1-year, and 10-year all-cause and cardiovascular mortality, the AUCs for the CCI and the ECI were comparable to those for the DANCAMI.
Conclusions:
Adding the DANCAMI to a model including patient age and sex improved discrimination of short and long-term all-cause mortality but not of cardiovascular mortality.
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