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A web-based novel prediction model for predicting depression in elderly patients with coronary heart disease: A
Juntao Tan1, Zhengguo Xu2, Yuxin He3
1Operation Management Office, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China.
Insights
Depression in elderly patients with coronary heart disease (CHD) is linked to higher mortality. Lower lymphocyte percentage, blood urea nitrogen, and low-density lipoprotein cholesterol predict depression, aiding early risk assessment in this population.
Area of Science:
- Geriatric Medicine
- Cardiology
- Psychiatry
- Biostatistics
Background:
- Depression is a significant risk factor for mortality in patients with coronary heart disease (CHD).
- Identifying depression early in elderly CHD patients is crucial for intervention and improved outcomes.
- Existing research often overlooks the specific predictors of depression in this vulnerable demographic.
Purpose of the Study:
- To investigate the key factors associated with depression in elderly patients diagnosed with CHD.
- To develop and validate a predictive model for the early detection of depression in this patient group.
- To provide clinicians with a practical tool for assessing depression risk in elderly CHD patients.
Main Methods:
- A cohort of 1,065 elderly (≥65 years) CHD patients was identified using propensity-score matching.
- Patients were divided into training (n=880) and external validation (n=185) sets.
- Logistic regression and least absolute shrinkage and selection operator (LASSO) regression identified predictive factors; a nomogram was constructed and validated.
Main Results:
- Key predictors of depression included reduced lymphocyte percentage, blood urea nitrogen, and low-density lipoprotein cholesterol levels.
- The developed nomogram demonstrated good discrimination, with Area Under the Curve (AUC) values of 0.762 (training) and 0.679 (validation).
- Calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC) confirmed the nomogram's clinical utility and reliability.
Conclusions:
- Decreased lymphocyte percentage, blood urea nitrogen, and low-density lipoprotein cholesterol are significant predictors of depression in elderly CHD patients.
- The validated nomogram serves as an effective clinical tool for assessing depression risk in this population.
- A web-based calculator tool was developed to facilitate the nomogram's practical application in clinical settings.
Background:
Depression is associated with an increased risk of death in patients with coronary heart disease (CHD). This study aimed to explore the factors influencing depression in elderly patients with CHD and to construct a prediction model for early identification of depression in this patient population.
Materials And Methods:
We used propensity-score matching to identify 1,065 CHD patients aged ≥65 years from four hospitals in Chongqing between January 2015 and December 2021. The patients were divided into a training set (n = 880) and an external validation set (n = 185). Univariate logistic regression, multivariate logistic regression, and least absolute shrinkage and selection operator regression were used to determine the factors influencing depression. A nomogram based on the multivariate logistic regression model was constructed using the selected influencing factors. The discrimination, calibration, and clinical utility of the nomogram were assessed by the area under the curve (AUC) of the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) and clinical impact curve (CIC), respectively.
Results:
The predictive factors in the multivariate model included the lymphocyte percentage and the blood urea nitrogen and low-density lipoprotein cholesterol levels. The AUC values of the nomogram in the training and external validation sets were 0.762 (95% CI = 0.722-0.803) and 0.679 (95% CI = 0.572-0.786), respectively. The calibration curves indicated that the nomogram had strong calibration. DCA and CIC indicated that the nomogram can be used as an effective tool in clinical practice. For the convenience of clinicians, we used the nomogram to develop a web-based calculator tool (https://cytjt007.shinyapps.io/dynnomapp_depression/).
Conclusion:
Reductions in the lymphocyte percentage and blood urea nitrogen and low-density lipoprotein cholesterol levels were reliable predictors of depression in elderly patients with CHD. The nomogram that we developed can help clinicians assess the risk of depression in elderly patients with CHD.
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