主管:国家卫生健康委员会
主办:国家卫生计生委医院管理研究所
中国科学引文数据库(CSCD)来源期刊
中国科技论文统计源期刊 中国科技核心期刊
《中文核心期刊要目总览》入选期刊

Chinese Nursing Management ›› 2023, Vol. 23 ›› Issue (4): 528-534.doi: 10.3969/j.issn.1672-1756.2023.04.010

• Research Papers • Previous Articles     Next Articles

Development and validation of a risk prediction model for Fear of Progression in patients with Chronic Heart Failure

XIONG Juanjuan, QIN Jingwen, GONG Kaizheng   

  1. Department of Cardiology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu province, 225009, China
  • Online:2023-04-15 Published:2023-04-15
  • Contact: E-mail:yungkzh@163.com

Abstract: Objective: To investigate the current status and influencing factors of Fear of Progression (FoP) in patients with Chronic Heart Failure (CHF), to construct a risk prediction model and to verify the prediction effect of the model. Methods: A total of 188 patients with CHF who hospitalized in the department of cardiology of 2 tertiary hospitals from November 2021 to March 2022 were selected as the subjects by convenience sampling. The risk factors between dysfunctional FoP group (n=64) and non-dysfunctional FoP group (n=124) were compared. The risk prediction model was constructed with Logistic regression analysis using the self-regulation common sense model as the theoretical framework. Hosmer-Lemeshow test was used to test the goodness of fit and the area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the efficacy of the model. Eighty CHF patients were selected to verify the prediction effect of the model. Results: The incidence of dysfunctional FoP in patients with CHF was 34.04%. Age (OR=0.909), left atrial diameter (OR=1.074), New York Heart Association function classification (OR=9.156), number of non-cardiovascular comorbidities (OR=4.222), Heart Failure Somatic Perception Scale score (OR=1.153), Connor-Davidson Resilience Scale-10 item (OR=0.749), and Self-care of Heart Failure Index (OR=0.926) were independent influencing factors of dysfunctional FoP in patients with CHF (P<0.05). The AUC of the model was 0.926, the sensitivity was 81.5%, the specificity was 89.1%, and the Youden index was 0.706. The prediction accuracy was 88.75%. Conclusion: The risk prediction model for FoP in patients with CHF constructed in this study has good predictive effects, which is suitable for clinical screening. It might provide a scientific reference for nursing staff to identify high-risk populations and to take targeted positive psychological interventions.

Key words: Chronic Heart failure; Fear of Progression; psychological resilience; risk factor; prediction model; nursing care

CLC Number: R47;R197;R541