Analysis on predictive modeling constructing of worse compliance in patients with TB / HIV coinfection
YANG Jing1,2 XUE Miao1,2 JI Yulin2 CAO Xinyu1,2 ZHANG Huan1,2 FENG Ping2▲
1.West China School of Nursing, Sichuan University, Sichuan Province, Chengdu 610000, China;
2.Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Sichuan Province, Chengdu 610000, China
Abstract：Objective To explore the influencing factors of treatment compliance in patients with TB/HIV coinfection, and to construct and verify the prediction nomogram of treatment compliance. Methods A total of 168 patients with TB /HIV coinfection admitted to West China Hospital of Sichuan University from May 2017 to May 2020 were selected as the study subjects. Seven patients were lost to follow-up. At the end of follow-up, Morisky medication compliance questionnaire was used to evaluate their compliance. According to their scores, they were divided into good compliance group (≥6 points, 86 cases) and poor compliance group (＜6 points, 75 cases). Clinical data of two groups were collected, univariate analysis and multivariate logistic regression were conducted to analyze the influencing factors of treatment compliance, and a nomogram model was established and verified. Results The rural household registration ratio, Hamilton depression scale (HAMD) score and Hamilton anxiety scale (HAMA) score in the poor compliance group were higher than those in the good compliance group, and the social support rating scale (SSRS) score was lower than that in the good compliance group, with statistical significance (all P ＜ 0.05). There were statistically significant differences in education level and monthly family income between the two groups (all P ＜ 0.05). The results of multivariate logistic regression analysis showed that education level of junior middle school or below, monthly family income ＜5000 yuan, rural household registration, high HAMD score and high HAMA score were independent risk factors for poor treatment compliance of patients with TB / HIV coinfection (all OR ＞ 1, P ＜ 0.05). High SSRS score (OR ＜ 1, P ＜ 0.05) was the protective factor. The consistency index of nomogram for predicting treatment compliance was 0.914 (95%CI: 0.856, 0.930). Conclusion The treatment compliance of patients with TB / HIV coinfection is related to education, family income, social support and other factors, and the nomogram can be a good auxiliary tool for predicting the treatment compliance of patients.
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