ArticleScientific reports2025
Construction and validation of a risk predictive model for fear of disease progression in patients after percutaneous coronary intervention.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study aimed to construct and validate a predictive model for fear of disease progression in patients after percutaneous coronary intervention(PCI). From March to October 2024, 455 post-PCI patients in the Department of Cardiovascular Medicine of a tertiary general hospital in Sichuan Province, China, were randomly divided into a training set and a validation set in a ratio of 7:3 as study subjects. LASSO regression and multifactorial logistic regression were used to analyze the factors influencing fear of disease progression in post-PCI patients, and a column chart was constructed. The predictive performance of the model was evaluated using the area under the ROC curve, Hosmer-Lemeshow test, and calibration curve. Clinical effectiveness was evaluated using clinical decision curve analysis. Among 455 post-PCI patients, 295 had a fear of disease progression, with an incidence of 64.8%. Seven influencing factors, including average monthly family income, number of chronic diseases, disease duration, number of interventional treatments, number of stent implants, psychological resilience, and perceived social support, were screened to construct the prediction model. The area under the ROC curve of the prediction model in the training set and the validation set were 0.941 (95% CI: 0.915-0.967) and 0.947 (95% CI: 0.911-0.984), respectively; the results of the Hosmer-Lemeshow goodness-of-fit test were χ2 = 12.564 (P = 0.128) and χ2 = 3.758 (P = 0.878); calibration curves showed significant agreement between predicted and actual values. The clinical decision curve analysis demonstrates that this model exhibits favorable net benefit and clinical effectiveness.The fear of disease progression prediction model constructed in this study has good predictive ability, which can provide a reference basis for effectively identifying high-risk groups and formulating targeted interventions to reduce the fear of disease progression in post-PCI patients.
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