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Predicting 15-Year Mortality in Adults With Congenital Heart Disease Using Disease Severity and Functional Indices
Fouke Ombelet1, Eva Goossens2, Silke Apers1
1KU Leuven Department of Public Health and Primary Care, KU Leuven - University of Leuven, Leuven, Belgium.
Insights
The Congenital Heart Disease Functional Index (CHDFI) best predicts 15-year mortality in adults with congenital heart disease (CHD). This index, incorporating both anatomic and physiological factors, offers superior risk stratification compared to other common indices.
Area of Science:
- Cardiology
- Medical Informatics
- Public Health
Background:
- Congenital heart disease (CHD) affects adults, requiring long-term risk stratification.
- Current disease severity and functional indices are used for risk stratification, but their long-term predictive value for mortality is not well-established.
- Assessing long-term mortality risk is crucial for managing adult CHD patients.
Purpose of the Study:
- To determine and compare the predictive value of various disease severity and functional indices for 15-year mortality in adults with CHD.
- To identify the most effective index for risk stratification in this population.
Main Methods:
- A cohort of 629 adult CHD patients (median age 24 years) were assessed using five indices: Task Force 1 criteria, Disease Severity Index, New York Heart Association functional class, Ability Index, and Congenital Heart Disease Functional Index (CHDFI).
- Cox hazard regression analysis and Harrell's concordance statistics index (C-index) were used to evaluate the predictive performance of each index for all-cause and cardiac mortality over 15 years.
Main Results:
- Over 15 years, 40 deaths occurred (4.56 per 1000 person-years).
- The CHDFI demonstrated the highest predictive ability for all-cause mortality (C-index = 0.74) and cardiac mortality (C-index = 0.76).
- The CHDFI showed statistically superior discrimination compared to the Disease Severity Index (P < 0.01).
Conclusions:
- Several indices, including Task Force 1, NYHA class, Ability Index, and CHDFI, can aid in predicting long-term mortality in adults with CHD.
- The CHDFI's superior performance highlights the importance of integrating both anatomic and physiological variables for accurate long-term mortality prediction.
- The CHDFI is a valuable tool for risk stratification in adult CHD patients.
Background:
Disease severity and functional indices are widely used for risk stratification of patients with congenital heart disease (CHD). The predictive value of these classification systems for assessing long-term mortality is unknown. We aimed to determine and compare the predictive value of disease severity and functional indices for 15-year mortality in adults with CHD.
Methods:
Between 2000 and 2002, we categorized 629 patients with CHD (median age, 24 years; 60% were men) on 5 indices: disease complexity scores based on criteria of Task Force 1 of the 32nd Bethesda Conference; Disease Severity Index; New York Heart Association functional class; Ability Index; and Congenital Heart Disease Functional Index (CHDFI). Harrell's concordance statistics index (C-index) was calculated for each classification system through Cox hazard regression analysis to evaluate their performance on predicting all-cause and cardiac mortality over the subsequent 15 years.
Results:
Over the 15-year follow-up period, 40 patients died, resulting in a mortality rate of 4.56 per 1000 person-years. The CHDFI showed the highest discrimination ability for all-cause mortality (C-index = 0.74; P < 0.001) and cardiac mortality (C-index = 0.76; P < 0.001). The C-index for the other classifications ranged from 0.58 to 0.71 for all-cause mortality and 0.55 to 0.67 for cardiac mortality. The CHDFI showed statistical superiority toward the Disease Severity Index (P < 0.01).
Conclusions:
These results suggest that the Task Force 1 of the 32nd Bethesda Conference, New York Heart Association functional class, Ability Index, and CHDFI could aid in predicting long-term mortality. The CHDFI demonstrated the highest discrimination ability and emphasizes the importance to integrate both anatomic and physiological variables to predict long-term mortality.
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