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Published on: June 10, 2025
A novel nomogram to predict all-cause readmission or death risk in Chinese elderly patients with heart failure
Mengxi Yang1, Liyuan Tao2, Hui An3
1Department of Cardiology, China-Japan Friendship Hospital, Beijing, China.
Insights
This study developed accurate nomograms to predict heart failure readmission or death in elderly Chinese patients. These tools can help reduce readmission and mortality rates in this vulnerable population.
Area of Science:
- Cardiology
- Geriatrics
- Medical Informatics
Background:
- Elderly patients with heart failure (HF) experience high rates of all-cause readmission and mortality.
- Accurate prediction models are needed to identify high-risk individuals for targeted interventions.
Purpose of the Study:
- To develop and validate an accurate and user-friendly model for predicting all-cause readmission or death risk in Chinese elderly patients with HF.
- To identify key clinical factors associated with short-term (30-day) and long-term (1-year) adverse outcomes.
Main Methods:
- A prospective cohort study involving 854 elderly patients (≥65 years) with HF.
- Data collection included demographics, comorbidities, laboratory values, and medications.
- Cox regression analysis and nomogram development with bootstrap validation were employed to identify predictors and build the model.
Main Results:
- The 30-day and 1-year cumulative all-cause readmission rates were 10.5% and 34.9%, respectively.
- The 30-day and 1-year cumulative mortality rates were 11.6% and 19.7%, respectively.
- Key predictors for both 30-day and 1-year outcomes included older age, stroke, low diastolic blood pressure, low BMI, reduced estimated glomerular filtration rate, and high BNP levels. Specific factors also predicted individual time points.
Conclusions:
- Accurate and easy-to-use nomograms were developed to predict all-cause readmission or death in Chinese elderly HF patients.
- These predictive tools can aid clinicians in risk stratification and potentially reduce adverse outcomes.
- The study highlights the importance of comprehensive assessment in managing elderly HF patients.
Aims:
Elderly patients with heart failure (HF) are associated with frequent all-cause readmission or death. The present study sought to develop an accurate and easy-to-use model to predict all-cause readmission or death risk in Chinese elderly patients with HF.
Methods And Results:
This was a prospective cohort study in patients with HF aged 65 or older. Demographic, co-morbidity, laboratory, and medication data were collected. A Cox regression model was used to identify factors for the prediction of readmission or death at 30 days and 1 year. A nomogram was developed with bootstrap validation. Of the included 854 patients, the cumulative all-cause readmission and mortality rates were 10.5% and 11.6% at 30 days and 34.9% and 19.7% at 1 year, respectively. The independent risk factors associated with both 30 day and 1 year readmission or death were older age, stroke, diastolic blood pressure < 60 mmHg, body mass index ≤ 18.5 kg/m2 , lower estimated glomerular filtration rate, and BNP > 400 pg/mL (all P < 0.05). Anaemia, abnormal neutrophils, and admission without angiotensin-converting enzyme inhibitors/angiotensin receptor blockers were the specific independent risk factors of 30 day all-cause readmission or death (all P < 0.05), whereas serum sodium ≤ 140 mmol/L and admission without beta-blockers were the specific independent risk factors of 1 year all-cause readmission or death (all P < 0.05). The C-index of the 30 day and 1 year diagnosis prediction model was 0.778 [95% confidence interval (CI) 0.693-0.862] and 0.738 (95% CI 0.640-0.836), respectively.
Conclusions:
We developed accurate and easy-to-use nomograms to predict all-cause readmission or death in Chinese elderly patients with HF. The nomograms will assist in reducing the all-cause readmission and mortality rates.
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