Analysis of Influencing Factors of Rehabilitation Training Effect and Construction of Nomogram Prediction Model in Elderly Post-Stroke Hemiplegia Patients
FENG Bing, YANG Peiquan, ZHOU Hui
Guiping People's Hospital, Guangxi Guiping 537200, China
Abstract：Objective: To analyze the influencing factors of rehabilitation training effect in elderly post-stroke hemiplegia patients, and to construct a nomogram model to predict the effect of rehabilitation training. Methods: The clinical data of 286 elderly patients with hemiplegia after acute stroke who received rehabilitation training in Guiping People's Hospital from July 2017 to June 2021 were retrospectively collected and randomly divided into modeling group (n=200) and validation group (n=86) with the ratio of 7∶3. The data of the modeling group were used to construct a risk prediction nomogram model, and the data of the validation group were used to evaluate the performance of the model. The two groups were divided into a good effect group and a poor effect group according to the effect of rehabilitation training. Univariate and multivariate Logistic regression analyses were used to identify the risk factors for poor rehabilitation training effect, R3.6.3 software was applied to build a nomogram model for predicting poor rehabilitation effect, and the effect of the nomogram model in predicting poor rehabilitation effect was verified. Results: Among the 286 hemiplegic patients, 42.66% (122/286) had poor rehabilitation effect. The age, male proportion, alcohol consumption proportion, hypertension proportion, rehabilitation training start time >2 weeks, and rural living environment proportion of patients in the poor effect group were significantly higher than those in the good effect group, with significant differences (P<0.05). Through multivariate Logistic regression model, it was found that living environment, age, hypertension, rehabilitation training start time >2 weeks, and alcohol consumption were the risk factors for poor rehabilitation effect of hemiplegic patients (P<0.05). The area under the ROC of the modeling group was 0.801, and the area under the curve of the validation group was 0.851; the slopes of the calibration curves of both the modeling group and the validation group were close to 1. Conclusion: Based on age, drinking, high blood pressure, rehabilitation training start time, and living environment, the nomogram model for predicting poor rehabilitation training effect in elderly post-stroke hemiplegia patients can better predict poor rehabilitation training effect individually, and it has certain guiding significance for early intervention in rehabilitation training.
冯兵, 杨培全, 周辉. 老年脑卒中后偏瘫患者康复训练效果影响因素分析及列线图预测模型构建[J]. 河北医学, 2023, 29(9): 1532-1537.
FENG Bing, YANG Peiquan, ZHOU Hui. Analysis of Influencing Factors of Rehabilitation Training Effect and Construction of Nomogram Prediction Model in Elderly Post-Stroke Hemiplegia Patients. HeBei Med, 2023, 29(9): 1532-1537.
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2023, Vol. 29 
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