Subarachnoid Hemorrhage in Hospitalized Renal Transplant Recipients with Autosomal Dominant Polycystic Kidney Disease: A Nationwide Analysis

Consensus document on autosomal dominant polycystic kindey disease from the Spanish Working Group on Inherited Kindey Diseases. Review 2020

Autosomal dominant polycystic kidney disease (ADPKD) is the most frequent cause of genetic renal disease and accounts for 6-10% of patients on kidney replacement therapy (KRT). Very few prospective, randomized trials or clinical studies address the diagnosis and management of this relatively frequent disorder. No clinical guidelines are available to date. This is a revised consensus statement from the previous 2014 version, presenting the recommendations of the Spanish Working Group on Inherited Kidney Diseases, which were agreed to following a literature search and discussions. Levels of evidence mostly are C and D according to the Centre for Evidence-Based Medicine (University of Oxford). The recommendations relate to, among other topics, the use of imaging and genetic diagnosis, management of hypertension, pain, cyst infections and bleeding, extra-renal involvement including polycystic liver disease and cranial aneurysms, management of chronic kidney disease (CKD) and KRT and management of children with ADPKD. Recommendations on specific ADPKD therapies are provided as well as the recommendation to assess rapid progression.

Recent Advances and Clinical Outcomes of Kidney Transplantation

Recent advances in surgical, immunosuppressive and monitoring protocols have led to the significant improvement of overall one-year kidney allograft outcomes. Nonetheless, there has not been a significant change in long-term kidney allograft outcomes. In fact, chronic and acute antibody-mediated rejection (ABMR) and non-immunological complications following kidney transplantation, including multiple incidences of primary kidney disease, as well as complications such as cardiovascular diseases, infections, and malignancy are the major factors that have contributed to the failure of kidney allografts. The use of molecular techniques to enhance histological diagnostics and noninvasive surveillance are what the latest studies in the field of clinical kidney transplant seem to mainly focus upon. Increasingly innovative approaches are being used to discover immunosuppressive methods to overcome critical sensitization, prevent the development of anti-human leukocyte antigen (HLA) antibodies, treat chronic active ABMR, and reduce non-immunological complications following kidney transplantation, such as the recurrence of primary kidney disease and other complications, such as cardiovascular diseases, infections, and malignancy. In the present era of utilizing electronic health records (EHRs), it is strongly believed that big data and artificial intelligence will reshape the research done on kidney transplantation in the near future. In addition, the utilization of telemedicine is increasing, providing benefits such as reaching out to kidney transplant patients in remote areas and helping to make scarce healthcare resources more accessible for kidney transplantation. In this article, we discuss the recent research developments in kidney transplants that may affect long-term allografts, as well as the survival of the patient. The latest developments in living kidney donation are also explored.

Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

Kidney diseases form part of the major health burdens experienced all over the world. Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great importance of collecting a large quantity of health-related data among human cohorts, what scholars refer to as “big data”, has increasingly been identified, with the establishment of a large group of cohorts and the usage of electronic health records (EHRs) in nephrology and transplantation. These data are valuable, and can potentially be utilized by researchers to advance knowledge in the field. Furthermore, progress in big data is stimulating the flourishing of artificial intelligence (AI), which is an excellent tool for handling, and subsequently processing, a great amount of data and may be applied to highlight more information on the effectiveness of medicine in kidney-related complications for the purpose of more precise phenotype and outcome prediction. In this article, we discuss the advances and challenges in big data, the use of EHRs and AI, with great emphasis on the usage of nephrology and transplantation.