Background As an important treatment for the treatment of kidney disease, peritoneal dialysis has been widely studied and applied due to its low cost and easy operation. Given that chronic kidney disease is growing globally, peritoneal dialysis is receiving increasing attention. With the development and popularization of mobile network technology, mobile telematics began to become a mainstream trend. The emergence of mobile telemedicine system is an important result of applying the universal computing concept to medical purposes. However, as users are not familiar with the medical field, telemedicine technology depends to a large extent on the patient's acceptance of the use of them.
Methods By integrating the experience of clinicians, the remote diagnosis and treatment system of peritoneal dialysis developed by Shenzhen Traditional Chinese Medicine Hospital can monitor the whole course of peritoneal dialysis data of patients. We used statistical methods to empirically analyze the peritoneal dialysis data. By exploring data over a standard duration of time, the filtration rate per minute of the peritoneal dialysis patients using a 1.5% low-calcium peritoneal solution was reduced over time and had a power function relationship which can help to remind incorrect data. The linear equation can be obtained by least square regression of the data after the time of peritoneal effusion and the weight of the effluent deformed.
Results The least squares method was used to regress the patient's peritoneal dialysis data (logarithm of peritoneal dialysis time and filtration rate per minute), and the regression equation R square was equal to 0.95. The regression coefficient passed the T test and the regression equation fits well. According to the result parameters of the regression equation, we calculated the standard range of filtration rate for each peritoneal dialysis. Taking 441 cases of a random patient as an example, 438 cases of diafiltration rate met the standard range. 3 cases were filtered out below the standard.
Conclusions The system can inform the patients of the results according to the confidence interval of the regression prediction, which greatly strengthens the interaction of the system and increases the patients' compliance.