ABSTRACT
Objective To analyze the influencing factors for catheter-associated infection(CAI)in chemotherapy treated patients after indwelling peripherally inserted central catheter(PICC)based on a random forest model.Methods 400 tumor patients who received chemotherapy and PICC were selected and divided into the training set(n=300)and the test set(n=100)in a 3∶1 ratio through computer-generated random number.Patients in the training set were subdivided into the non-infection group and the infection group based on the occurrence of infec-tion.Clinical data from two groups of patients were compared.Influencing factors for the occurrence of CAI after PICC were analyzed with multivariate logistic regression model and the integrated classification algorithm of random forest model,and the predictive performance of the two methods was compared.Results Among 300 chemotherapy treated patients in the training set,32 cases(10.67％)experienced CAI.Compared with the non-infection group,patients in the infection group had more single punctures for catheterization,longer PICC retention time,larger pro-portion of catheter movement,larger proportion of complication with diabetes,higher frequency of dressing chan-ges,lower white blood cell count and immune function(all P＜0.05).PICC retention time,catheter movement,complication with diabetes,dressing change frequency,white blood cell(WBC)and immune function were inde-pendent influencing factors for CAI after PICC(all P＜0.05).The random forest model showed that ranking by the importance of different influencing factors was as following:PICC retention time,catheter movement,complication with diabetes,WBC,dressing change frequency and immune function.The integrated classification algorithm of random forest model for predicting the occurrence of CAI in chemotherapy treated patients showed that the area un-der the receiver operating characteristic(ROC)curve(AUC)was 0.872,which had better prediction performance compared with the logistic regression model(AUC=0.791).Conclusion PICC retention time,catheter movement,complicated with diabetes,dressing change frequency,WBC level and immune function are independent influencing factors for CAI in chemotherapy treated patients.The integrated classification algorithm of random forest model can be used to predict CAI in chemotherapy treated patients,and its prediction performance is better than that of the logistic regression model.
ABSTRACT
Computational medicine is an emerging discipline that uses computer models and complex software to simulate the development and treatment of diseases. Advances in computer hardware and software technology, especially the development of algorithms and graphics processing units (GPUs), have led to the broader application of computers in the medical field. Computer vision based on mathematical biological modelling will revolutionize clinical research and diagnosis, and promote the innovative development of Chinese medicine, some biological models have begun to play a practical role in various types of research. This paper introduces the concepts and characteristics of computational medicine and then reviews the developmental history of the field, including Digital Human in Chinese medicine. Additionally, this study introduces research progress in computational medicine around the world, lists some specific clinical applications of computational medicine, discusses the key problems and limitations of the research and the development and application of computational medicine, and ultimately looks forward to the developmental prospects, especially in the field of computational Chinese medicine.
Subject(s)
Humans , Algorithms , Computer SimulationABSTRACT
Rich experience of clinical diagnosis and treatment has been accumulated in the developmental history of Chinese medicine, and the efficacy has been increasingly accepted by the public. However, the evaluation of clinical efficacy is currently based more on scientific evidence instead of merely the changes of patient symptoms. In Chinese medicine, the changes of major disease indicators, patient symptoms, and pathogenesis are the major criteria for the evaluation of clinical efficacy. The lack of well-accepted and uniform criteria and the uncertainty of subjective evaluation limit the development of clinical Chinese medicine. Evidence-based medicine combines clinical skills with the current best evidence. Narrative medicine, utilizing people's narratives in clinical practice, emphasizes patient feelings, willingness, and value orientation. The introduction of both evidence-based medicine and narrative medicine into the evaluation of clinical efficacy refers to the construction of the clinical efficacy evaluation system in a paradigm of participatory diagnosis and treatment. It can fully reflect the characteristics of Chinese medicine, respect the values of patients, and achieve universal clinical evidence. Therefore, it helps to improve the diagnosis and treatment, the relationship between doctors and patients, patients' life quality and decision-making awareness, and finally the new evaluation model of clinical efficacy of Chinese medicine.