Prediction of short-term outcome after subacute ischemic stroke using multiple layer perceptron neural network / 中国康复理论与实践

@#Objective To establish a predictive model using multiple layer perceptron (MLP) for short-term outcome after subacute ischemic stroke.Methods From January, 2019 to September, 2021, 60 readmission-inpatients in Department of Rehabilitation, Ruijin Hospital, Shanghai Jiaotong University School of Medicine were collected the clinical features of first admission (less than 30 days after attack), and the outcomes were assessed with modified Rankin Scale (MRS) three months after the first admission. The risk factors were screened with single factor analysis, and the short-term outcome predictive models were established with multi-factor Logistic regression and MLP. The predictive accuracy of both models was calculated, and the predictive effects were compared with Receiver Operating Characteristic (ROC) curve.Results For multi-factor Logistic regression, the predictive accuracy was 73.3%, and the area under ROC curve was 0.851. For MLP, the predictive accuracy was 88.9%, and the area under the ROC curve was 0.930.Conclusion The prediction of short-term outcome after subacute ischemic stroke can be done with MLP model.

Advance in Hoffa's Disease and Substance P Positive Nerve Fibers (review) / 中国康复理论与实践

Hoffa's disease is the clinical condition characterized by anterior knee joint pain secondary to inflammation and/or impinge-ment of the infrapatellar fat pad. The substance P positive nerve fibers rich in the infrapatellar fat pad were stimulated by the noxious stimu-li, which may associated with the pain of Hoffa's disease. The relationship between Hoffa's disease and substance P positive nerve fibers in the infrapatellar fat pad was reviewed in this paper.