分析中青年脑卒中患者重返工作的影响因素并构建预测模型。

选取2018年5月至2020年4月海南省肿瘤医院收治的323例中青年脑卒中患者为研究对象，调查工具采用一般情况调查表、重返工作准备度量表（RRTW）及自我效能感量表（GSES）。采用问卷调查法对323例中青年脑卒中患者重返工作准备情况进行调查，分别采用Lasso和Logistic回归分析中青年脑卒中的影响因素并构建列线图预测模型，验证该模型的预测性及准确性。

RRTW量表前意向维度评分为（2.68±0.83）分，意向维度评分为（3.07±0.92）分，行动准备-自我评估维度评分为（2.62±0.78）分，行动准备-行为评分为（2.57±0.72）分；GSES量表评分为（13.25±3.54）分。57例中青年脑卒中患者重返工作准备度高，266例中青年脑卒中患者重返工作准备度低；文化程度、不良情绪、功能障碍、家庭人均月收入、家庭支持、社会支持、专业康复指导训练是中青年脑卒中患者重返工作的影响因素（P＜0.05）；中青年脑卒中患者重返工作的列线图模型的一致性指数（C-index）为0.837（95%CI：0.810~0.865），预测值与实测值基本一致，内部验证ROC曲线显示AUC为0.808，决策曲线显示阈值概率在1%~88%时，具有较高的净获益值。

中青年脑卒中患者重返工作准备度低，文化程度、不良情绪、功能障碍、家庭人均月收入、家庭支持、社会支持、专业康复指导训练是影响中青年脑卒中患者重返工作的影响因素，根据影响因素建立列线图模型对患者重返工作意向具有较好的预测作用。

To analyze the factors influencing middle-aged and young stroke patients' return to work and build a prediction model.

A total of 323 middle-aged and young stroke patients admitted to Hainan Cancer Hospital from May 2018 to April 2020 were included. The survey tools were the general questionnaire, the readiness for return-to-work scale (RRTW), and the general self-efficacy scale (GSES). A questionnaire survey was used to investigate the readiness of 323 middle-aged and young stroke patients, return to work. Lasso and Logistic regression were used to analyze the influencing factors of stroke in middle-aged and young patients, and a nomograph prediction model was constructed to verify its predictability and accuracy.

The average score of the intention dimension before the RRTW scale was (2.68±0.83) points; the average score of the intention dimension was (3.07±0.92) points; the average score of the action preparation self-assessment dimension was (2.62±0.78) points; and the action preparation behavior dimension was (2.57±0.72) points; the average score of the GSES scale was (13.25±3.54) points. Fifty-seven middle-aged and young stroke patients had high readiness to return to work, while 266 middle-aged and young stroke patients had low readiness to return to work; education level, adverse emotions, dysfunction, family monthly income per capita, family support, social support, and professional rehabilitation guidance training were the influencing factors for middle-aged and young stroke patients to return to work (P＜0.05); the C-index of the nomograph model for middle-aged and young stroke patients returning to work was 0.837 (95% CI: 0.810-0.865), and the predicted value was consistent with the measured value. The internal validation ROC curve showed an AUC of 0.808, and the decision curve showed a high net benefit value when the threshold probability was within the range of 1% to 88%.

Middle-aged and young stroke patients have low readiness to return to work, and education level, adverse emotions, dysfunction, family per capita monthly income, family support, social support, and professional rehabilitation guidance training are the influencing factors that affect the return to work of middle-aged and young stroke patients. Building a line graph model based on the influencing factors has a good predictive effect on patients' return to work intention .