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- Title
Construction of Nomogram prediction model for kinesiophobia in patients underwent total knee arthroplasty.
- Authors
LEI Mengdi; ZHANG Zhuoqi; PAN Lanxia; SONG Jing
- Abstract
Objective: To analyze the influencing factors of kinesiophobia in patient,s underwent total knee arthroplasty (TKA), and establish and verify a Nomogram model. Method: A total of 335 patients who underwent total knee arthroplasty in a tertiary grade A hospital in Henan province from January to October 2021 were selected as the research objects. The general information,the occurrence of kinesiophobia, anxiety, depression and social support of the patients were investigated. The influencing factors of kinesiophobia in patients undergoing total knee arthroplasty were analyzed, and the Nomogram model was established and verified. Results: Logistic regression analysis showed that age, VAS score, complications, depression and negative coping were the risk factors of kinetophobia, self-efficacy and social support were the protective factors of kinetophobia. The consistency index of Nomogram model for predicting kinesiophobia after total knee replacement was 0.849, the AUC of nomogram model was 0.741, the sensitivity of prediction model was 78.94%, the specificity was 97.18%. Conclusion: The patient's age, pain level, total knee arthroplasty, complications, depression, negative coping, self-efficacy, social support could affect the occurence of kinesiophobia. The constructed Nomogram prediction model has good specificity and sensitivity, and it is helpful for clinical workers to judge the occurrence of kinesiophobia in patients underwent total knee arthroplasty.
- Subjects
CHINA; EXPERIMENTAL design; PHOBIAS; TOTAL knee replacement; SOCIAL support; RESEARCH methodology; TERTIARY care; REGRESSION analysis; VISUAL analog scale; BODY movement; MENTAL depression; DESCRIPTIVE statistics; STATISTICAL models; ANXIETY; PSYCHOLOGICAL adaptation
- Publication
Chinese Nursing Research, 2023, Vol 37, Issue 4, p40
- ISSN
1009-6493
- Publication type
Article
- DOI
10.12102/j.issn.1009-6493.2023.01.007