New model predicts which patients with kidney disease may develop heartbeat irregularities

October 24, 2020

Highlights Washington, DC (October 24, 2020) -- A new model that uses machine learning, which is a type of artificial intelligence, may help predict which patients with kidney disease are at especially high risk of developing heart beat irregularities. The findings come from a study that will be presented online during ASN Kidney Week 2020 Reimagined October 19-October 25.

Atrial fibrillation (AF)--an irregular, often rapid heart rate--is common in patients with chronic kidney disease (CKD) and is associated with poor kidney and cardiovascular outcomes. Researchers conducted a study to see if a new prediction model could be used to identify patients with CKD at highest risk of experiencing AF. The team compared a previously published AF prediction model with a model developed using machine learning (a type of artificial intelligence) based on clinical variables and cardiac markers.

In an analysis of information on 2,766 participants in the Chronic Renal Insufficiency Cohort (CRIC), the model based on machine learning was superior to the previously published model for predicting AF.

"The application of such a model could be used to identify patients with CKD who may benefit from enhanced cardiovascular care and also to identify selection of patients for clinical trials of AF therapies," said lead author Leila Zelnick, PhD (University of Washington, in Seattle)
-end-
Study: "Prediction of Atrial Fibrillation Using Clinical and Cardiac Biomarker Data: The CRIC Study"

ASN Kidney Week 2020 Reimagined, the largest nephrology meeting of its kind, will provide a forum for more than 13,000 professionals to discuss the latest findings in kidney health research and engage in educational sessions related to advances in the care of patients with kidney and related disorders. Kidney Week 2020 Reimagined will take place October 19-October 25.

Since 1966, ASN has been leading the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients. ASN has more than 21,000 members representing 131 countries. For more information, visit http://www.asn-online.org.

American Society of Nephrology

Related Kidney Disease Articles from Brightsurf:

Waistline matters in kidney disease
Does fat matter in kidney disease? The investigators found that all measures of higher abdominal fat content (including visceral fat, liver fat, or subcutaneous fat) and slower walk times were associated with increased levels of cardiometabolic risk factors in adults with non-dialysis dependent kidney disease.

Reducing urinary protein for patients with rare kidney disease slows kidney decline
New findings show that reducing the amount of protein in the urine of patients with focal segmental glomerulosclerosis can significantly slow declines in kidney function and extend time before patients' kidneys fail.

Antioxidant agent may prevent chronic kidney disease and Parkinson's disease
Researchers from Osaka University developed a novel dietary silicon-based antioxidant agent with renoprotective and neuroprotective effects.

Acute kidney injury and end stage kidney disease in severe COVID-19
Many COVID-19 patients experience hematuria, proteinuria and elevated serum creatinine concentration early in the course of the disease.

Genes tell a story about diabetic kidney disease
Studying Finnish genes leads to unique revelations about the development of a serious complication of diabetes, and informs an ongoing genomic study of a Singaporean cohort as part of Singapore's Diabetes Study in Nephropathy and other Microvascular Complications (DYNAMO).

New study provides insight into chronic kidney disease
Researchers have further analyzed a known signaling pathway they believe brings them one step closer to understanding the complex physiology of patients with chronic kidney disease (CKD), which might provide a path to new treatment options.

Predicting risk of chronic kidney disease
Data from about 5 million people (with and without diabetes) in 28 countries were used to develop equations to help identify people at increased five-year risk of chronic kidney disease, defined as reduced estimated glomerular filtration rate (eGFR).

A healthy diet may help prevent kidney disease
In an analysis of published studies, a healthy dietary pattern was associated with a 30% lower incidence of chronic kidney disease.

Is kidney failure a man's disease?
A new analysis of the ERA-EDTA Registry [1] reveals a striking gender difference in the incidence and prevalence of end-stage renal disease.

Chronic kidney disease: Everyone's concern
850 million people worldwide are affected by kidney disease. This worrying figure was published last June.

Read More: Kidney Disease News and Kidney Disease Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.