Medical experts utilize big data in fight against kidney disease
Big data is being used to assist kidney disease treatment and prevention in China.
A big data-based kidney disease research network has collected the medical data of more than 12.5 million patients from 34 leading hospitals in the nation.
The data, which have been processed for privacy protection, is being used to indicate the level, prevalence and regularity of chronic kidney disease in China, experts told the annual conference of the China Medical Education Association's clinical kidney disease commission.
It will also act as a model for diagnostic development as well as for forcasting disease risk.
"Based on this data, we have created new diagnostic standards for children and newborn babies with acute kidney injury," said Dr Hou Fanfan from Nanfang Hospital and an academician of the Chinese Academy of Sciences.
"We are also able to perfect strategies on kidney disease prevention and control, forecast the tendency of disease development and forecast patients' response to the therapies."
Chronic kidney disease is a common disease seriously impacting domestic people's health. Its incidence is more than 8 percent in China, and there are over one million patients receiving dialysis due to terminal kidney failure.
Moreover, chronic kidney disease is also an important risk factor for hypertension and will increase the risk of heart failure and cardiovascular diseases.
"It is a disease with low awareness, many complications and high medical costs," said Dr Chen Nan from Shanghai's Ruijin Hospital.
"So how to better chronic kidney disease prevention and control, and reduce the incidence rate of terminal kidney failure and patients' mortality, is a big task in the medical field.
"It is crucial to develop and introduce more innovative tools as well as medical therapies and medicines for chronic kidney disease management and treatment. Big data, AI, new materials and biomedicines are all promising methods, while public education is also extremely important."
