Wenzhe Sun, Guo Li, Xin Zhao, Junhua Mei, Jinfeng Miao, Zhou Zhu, Yan Lan, Guohua Chen, Ping Jing, Suiqiang Zhu, and Xiuli Qiu
Guo Li,1 Ping Jing,2 Guohua Chen,3 Junhua Mei,3 Jinfeng Miao,1 Wenzhe Sun,1 Yan Lan,1 Xin Zhao,1 Xiuli Qiu,1 Zhou Zhu,1,* Suiqiang Zhu1,* 1Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, Peopleâs Republic of China; 2Department of Neurology, Wuhan Central Hospital, Wuhan, Hubei, 430014, Peopleâs Republic of China; 3Department of Neurology, Wuhan First Hospital, Wuhan, Hubei, 430022, Peopleâs Republic of China*These authors contributed equally to this workCorrespondence: Zhou Zhu Tel +86-18171081029Email zhouzhu@hust.edu.cnSuiqiang Zhu Tel +86-13035101141Email zhusuiqiang@163.comPurpose: The early detection of major post-stroke depression (PSD) is essential to optimize patient care. A major PSD prediction tool needs to be developed and validated for early screening of major PSD patients.Patients and Methods: A total of 639 acute ischemic stroke (AIS) patients from three hospitals were consecutively recruited and completed a 3-month follow-up. Sociodemographic, clinical and laboratory test data were collected on admission. With major depression criteria being met in the DSM-V, 17-item Hamilton Rating Scale For Depression (HRSD) score ⥠17 at 3 months after stroke onset was regarded as the primary endpoint. Multiple imputation was used to substitute the missing values and multivariable logistic regression model was fitted to determine associated factors with a bootstrap backward selection process. The nomogram was constructed based on the regression coefficients of the associated factors. Performance of the nomogram was assessed by discrimination (C-statistics) and calibration curve.Results: A total of 7.04% (45/639) of patients were diagnosed with major PSD at 3 months. The final logistic regression model included age, baseline NIHSS and mRS scores, educational level, calciumâphosphorus product, history of hypertension and atrial fibrillation. The model had acceptable discrimination, based on a C-statistic of 0.81 (95% CI, 0.791â 0.829), with 71.1% sensitivity and 78.6% specificity. We also transformed the model to a nomogram, an easy-to-use clinical tool which could be used to facilitate the early screening of major PSD patients at 3 months.Conclusion: We identified several associated factors of major PSD at 3 months and constructed a convenient nomogram to guide follow-up and aid accurate prognostic assessment.Keywords: major post-stroke depression, nomogram, calciumâphosphorus product, C-statistic