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Published on: February 16, 2016
A prediction model for 5-year cardiac mortality in patients with chronic heart failure using
Kenichi Nakajima1, Tomoaki Nakata, Takahisa Yamada
1Department of Nuclear Medicine, Kanazawa University Hospital, 13-1 Takara-machi, Kanazawa, 920-8641, Japan, nakajima@med.kanazawa-u.ac.jp.
Insights
This study developed a new model to predict 5-year cardiac death risk in chronic heart failure patients. Including cardiac sympathetic innervation assessment significantly improved mortality risk prediction for better patient management.
Area of Science:
- Cardiology
- Nuclear Medicine
- Medical Imaging
Background:
- Accurate prediction of mortality risk is crucial for managing patients with chronic heart failure (CHF).
- Cardiac sympathetic nerve function is an important prognostic indicator in CHF.
- Previous models often lack comprehensive assessment of cardiac innervation.
Purpose of the Study:
- To develop a prediction model for 5-year cardiac death in CHF patients.
- To evaluate the added value of cardiac sympathetic innervation assessment using iodine-123 metaiodobenzylguanidine (MIBG) imaging.
- To create a risk stratification tool for CHF management.
Main Methods:
- Utilized a multicenter cohort of 933 CHF patients from Japan with known 5-year outcomes.
- Assessed cardiac sympathetic innervation via late MIBG heart-to-mediastinum ratio (HMR).
- Employed Cox proportional hazard and logistic regression analyses to identify predictive variables for 5-year cardiac mortality.
Main Results:
- During 5-year follow-up, 22% of patients died from cardiac events.
- A five-parameter model including HMR demonstrated superior predictive accuracy compared to a four-parameter model without HMR.
- Inclusion of HMR significantly improved risk reclassification, particularly for low-risk patients (13.8% net reclassification improvement).
Conclusions:
- Cardiac MIBG imaging provides significant additive value in predicting cardiac mortality in CHF.
- The developed prediction formula and nomograms can effectively stratify risk in CHF patients.
- This tool aids in personalized risk assessment and management strategies for chronic heart failure.
Purpose:
Prediction of mortality risk is important in the management of chronic heart failure (CHF). The aim of this study was to create a prediction model for 5-year cardiac death including assessment of cardiac sympathetic innervation using data from a multicenter cohort study in Japan.
Methods:
The original pooled database consisted of cohort studies from six sites in Japan. A total of 933 CHF patients who underwent (123)I-metaiodobenzylguanidine (MIBG) imaging and whose 5-year outcomes were known were selected from this database. The late MIBG heart-to-mediastinum ratio (HMR) was used for quantification of cardiac uptake. Cox proportional hazard and logistic regression analyses were used to select appropriate variables for predicting 5-year cardiac mortality. The formula for predicting 5-year mortality was created using a logistic regression model.
Results:
During the 5-year follow-up, 205 patients (22 %) died of a cardiac event including heart failure death, sudden cardiac death and fatal acute myocardial infarction (64 %, 30 % and 6 %, respectively). Multivariate logistic analysis selected four parameters, including New York Heart Association (NYHA) functional class, age, gender and left ventricular ejection fraction, without HMR (model 1) and five parameters with the addition of HMR (model 2). The net reclassification improvement analysis for all subjects was 13.8 % (p < 0.0001) by including HMR and its inclusion was most effective in the downward reclassification of low-risk patients. Nomograms for predicting 5-year cardiac mortality were created from the five-parameter regression model.
Conclusion:
Cardiac MIBG imaging had a significant additive value for predicting cardiac mortality. The prediction formula and nomograms can be used for risk stratifying in patients with CHF.
