Mi Wei-Feng, Chen Xiao-Min, Fan Teng-Teng, Tabarak Serik, Xiao Jing-Bo, Cao Yong-Zhi, Li Xiao-Yu, Bao Yan-Ping, Han Ying, Li Ling-Zhi, Shi Ying, Guo Li-Hua, Wang Xiao-Zhi, Liu Yong-Qiao, Wang Zhan-Min, Chen Jing-Xu, Wu Feng-Chun, Ma Wen-Bin, Li Hua-Fang, Xiao Wei-Dong, Liu Fei-Hu, Xie Wen, Zhang Hong-Yan, Lu Lin
Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, Anhui Mental Health Center, Hefei Fourth People's Hospital, Hefei, China.
Front Psychiatry. 2020 Sep 11;11:574763. doi: 10.3389/fpsyt.2020.574763. eCollection 2020.
Preventing relapse of schizophrenic patients is really a challenge. The present study sought to provide more explicit evidence and factors of different grades and weights by a series of step-by-step analysis through test, logistic regression analysis and decision-tree model. The results of this study may contribute to controlling relapse of schizophrenic patients.
A total of 1,487 schizophrenia patients were included who were 18-65 years of age and discharged from 10 hospitals in China from January 2009 to August 2009 and from September 2011 to February 2012 with improvements or recovery of treatment effect. We used a questionnaire to collect information about relapse and correlative factors during one year after discharge by medical record collection and telephone interview. The test and logistic regression analysis were used to identify risk factors and high-risk factors firstly, and then a decision-tree model was used to find predictive factors.
The test found nine risk factors which were associated with relapse. Logistic regression analysis also showed four high-risk factors further (medication adherence, occupational status, ability of daily living, payment method of medical costs). At last, a decision-tree model revealed four predictors of relapse; it showed that medication adherence was the first grade and the most powerful predictor of relapse (relapse rate for adherence nonadherence: 22.9 55.7%, = 116.36, p < 0.001). The second grade factor was occupational status (employment unemployment: 19.7 42.7%, = 17.72, p < 0.001); the third grade factors were ability of daily living (normal difficult: 28.4 54.3%, = 8.61, p = 0.010) and household income (household income ≥ 3000 RMB <3000 RMB: 28.6 42.4%, = 6.30, p = 0.036). The overall positive predictive value (PPV) of the logistic regression was 0.740, and the decision-tree model was 0.726. Both models were reliable.
For schizophrenic patients discharged from hospital, who had good medication adherence, more higher household income, be employed and normal ability of daily living, would be less likely to relapse. Decision tree provides a new path for doctors to find the schizophrenic inpatient's relapse risk and give them reasonable treatment suggestions after discharge.
预防精神分裂症患者复发是一项挑战。本研究旨在通过一系列逐步分析，包括检验、逻辑回归分析和决策树模型，提供更明确的不同等级和权重的证据及因素。本研究结果可能有助于控制精神分裂症患者的复发。
纳入2009年1月至2009年8月以及2011年9月至2012年2月期间从中国10家医院出院且治疗效果改善或恢复的1487例18 - 65岁精神分裂症患者。通过病历收集和电话访谈，使用问卷收集出院后一年内复发及相关因素的信息。首先采用检验和逻辑回归分析确定危险因素和高危因素，然后使用决策树模型寻找预测因素。
检验发现9个与复发相关的危险因素。逻辑回归分析进一步显示4个高危因素（服药依从性、职业状况、日常生活能力、医疗费用支付方式）。最后，决策树模型揭示了4个复发预测因素；结果显示服药依从性是复发的一级且最有力的预测因素（依从性与不依从性的复发率：22.9% 对55.7%，χ² = 116.36，p < 0.001）。二级因素是职业状况（就业与失业：19.7% 对42.7%，χ² = 17.72，p < 0.001）；三级因素是日常生活能力（正常与困难：28.4% 对54.3%，χ² = 8.61，p = 0.010）和家庭收入（家庭收入≥3000元与<3000元：28.6% 对42.4%，χ² = 6.30，p = 0.036）。逻辑回归的总体阳性预测值（PPV）为0.740，决策树模型为0.726。两个模型均可靠。
对于出院的精神分裂症患者，服药依从性好、家庭收入较高、就业且日常生活能力正常者复发可能性较小。决策树为医生发现精神分裂症住院患者的复发风险并在出院后给予合理治疗建议提供了一条新途径。
