Chronic kidney disease (CKD) has been highlighted as one of the most important public health problems due to sharply climbing incidence and prevalence. To efficiently attenuate the disease burden and improve the disease management, not only active and effective treatment should be administrated, but also comprehensive follow-up nursing management with innovative and evolving spirits should be implemented. Thus dynamic changes of diseases could be acquired in time and patients are under appropriate medical instruction as soon as possible. This editorial is based on quickly developing medical big data resources and advanced internet techniques, from both aspects of patients and health care providers, briefly talking about integrated management strategy of CKD and its future development in China.
Acute kidney injury (AKI) is a common critical illness in clinical practice, with complex etiologies, acute onset, and rapid progression. It not only significantly increases the mortality rate of patients, but also may progress to chronic kidney disease. Currently, its incidence remains high, and improving early diagnosis rate and treatment efficacy is a major clinical challenge. Artificial intelligence (AI), with its powerful data processing and analysis capabilities, is developing rapidly in medical field, providing new ideas for disease diagnosis and treatment, and showing great potential in revolutionizing the early diagnosis, condition assessment, and treatment decision-making models in the AKI field. This article will review the application progress of AI in AKI prediction, condition assessment, and treatment decision-making, so as to provide references for clinicians and promote the further application and development of AI in the AKI field.
Chronic kidney disease (CKD) has become a global public health problem because of its high prevalence, low awareness, poor prognosis, and high medical costs. Effective follow-up management can facilitate timely adjustment of the treatment of the CKD patients and delay the disease progression. The application of internet of things (IoT) technology in dynamic monitoring and telemedicine is helpful for the self-management of patients with chronic diseases, and can provide convenient, intelligent, and humanized medical and health services. In the future, with the rapid growth of demands of CKD management and innovations in information technology, new medical IoT industry will accelerate the intelligent development of CKD management. Multi-disciplinary and multi-industrial collaboration should be promoted to solve current challenges, such as evaluation of actual effectiveness, the system design and construction, and the accessibility of intelligent healthcare services, to ensure that IoT products can improve clinical outcomes, reduce medical expenditure, and lower disease burden.
Patients undergoing maintenance hemodialysis are characterized with lower cardiorespiratory capacity and muscle atrophy, thus easily leading to a sedentary lifestyle. These patients are usually associated with lower quality of life and worse prognosis. Evidence indicates appropriate exercise rehabilitation plan could help maintenance hemodialysis patients achieve better health outcomes. However, there is still a lack of evidence data to precisely recommend exercise type, intensity, frequency and timing specially designed for maintenance hemodialysis patients. This article aims to summarize the existing expert consensus on exercise rehabilitation for maintenance hemodialysis patients, important considerations in the implementation process, factors that affect exercise rehabilitation, with a view to encouraging maintenance hemodialysis patients to participate in the development of appropriate exercise rehabilitation plan and maximize health benefits.