Identifying predictors of relapse in Schizophrenia (SZ) has been a hot issue since relapse is associated with worse clinical outcome. In this study, relapse rates of SZ patients after hospital discharge and their possible factors were investigated annually over 3 years to differentiate short-term and long-term predictors for relapse in SZ in China. According to the sequence of discharge date, 420 SZ patients were recruited. The severity of disease, compliance with medication use, social functions, and relapse rate were assessed at the time points of 1-, 2- and 3-year after hospital discharge. After each assessment, only the not-relapsed participants remained in the study for the next assessment. The factors influencing relapse in SZ were analysed by a logistic regression. Our results indicated that the relapse rate at 1-, 2- and 3-year after hospital discharge was 33.0%, 29.8%, and 16.4%, respectively. Compliance with medication use, communication skills, and work/study functioning were associated with relapse in SZ, with differential long-term and short-term effects. Especially, the compliance with medication use in the relapsed participants were significantly worse than that in the not-relapsed participants in three assessments over 3 years (P<0.001). Logistic regression analyses also revealed that SZ patients with worse compliance with medication use, communication skills, and work/study functioning showed higher risk of relapse. Importantly, worse compliance with medication use was associated with a 6.369-, 13.889-, and 8.850- fold increase in relapse at 1-, 2- and 3-year after hospital discharge, respectively (P<0.001). To our knowledge, this is the first longitudinal study to investigate factors influencing relapse in SZ in China. Our results demonstrated that good compliance with medication use, communication skills, and work/study functioning may reduce the risk of relapse in SZ. The findings of this study suggested that good compliance with medication use is critical to prevention of SZ relapse.
Author(s): Fengchun Wu, Yuanyuan Huang, Yanling Zhou, Hehua Li, Bin Sun, Xiaomei Zhong, Xinni Luo, Yingjun Zheng, Hongbo He, Yuping Ning
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