AI Model Accurately Predicts Continuous Renal Replacement Therapy Survival
By HospiMedica International staff writers Posted on 11 Jul 2024 |

Continuous renal replacement therapy (CRRT) is a type of dialysis used for severely ill patients who are unable to undergo regular hemodialysis. Although CRRT has been in use for many decades, there is still no universally accepted set of clinical guidelines for physicians to determine when to initiate CRRT to ensure a positive outcome. The decision to commence CRRT typically relies on a physician's evaluation of the patient’s medical history, vital signs, lab results, and medications. Given the severe illness of these patients, there is always a degree of uncertainty about their survival during or after the treatment. It is estimated that around 50% of adults who undergo CRRT do not survive, rendering the treatment potentially futile for these patients and their families. Now, a new machine-learning model has been developed that can accurately predict the short-term survival of patients undergoing CRRT.
The machine-learning model developed by researchers at the University of California, Los Angeles (UCLA, Los Angeles, CA, USA) helps doctors decide whether a patient should start CRRT by using data from thousands of patient electronic health records to predict the likelihood of survival following CRRT. Unlike previous models that only predict in-hospital mortality after the initiation of CRRT, this innovative tool provides clinicians with information on whether to start CRRT at all.
The model offers a data-driven tool to aid clinical decision-making. It uses advanced machine-learning techniques to sift through a large and complex array of patient data, a task that has traditionally been challenging for doctors. The study illustrates the potential of integrating machine-learning models into healthcare, enhancing treatment effectiveness, and optimizing the use of medical resources.
“CRRT is often used as a last resort, but many patients do not survive it, leading to wasted resources and false hope for families,” said Dr. Ira Kurtz, chief of the UCLA Division of Nephrology and the study’s senior author. “By making it possible to predict which patients will benefit, the model aims to improve patient outcomes and resource use, by serving as a basis for testing its utility in future clinical trials. Like all machine learning models, it needs to be tested in the real world to determine whether it is equally as accurate in its predictions in patients that it wasn’t trained on.”
Related Links:
UCLA
Latest Critical Care News
- Novel Coating Significantly Extends Longevity of Implantable Biosensors
- Nanogel-Based Drug Delivery Technology to Improve UTI Treatment
- New IV Pole Improves Safety and Ease of Administering IV Medications at Hospital Bedside
- Battery-Powered Wearable Device Monitors Joint Pain
- Wireless Pacifier Monitors Vitals of NICU Babies Without Need for Painful Blood Draws
- Breakthrough Sensor Technology Tracks Stroke After Effects
- New Study Demonstrates AI-Assisted Detection of Reduced Ejection Fraction
- Novel 3D Adipose Tissue Bioprinting Method to Find Applications in Regenerative Medicine
- Miniaturized Pacemaker for Newborns Found Safe and Effective for Up to Two Years
- World’s First 3D Neural Electrode Uses Soft Actuation Technology to Avoid Nerve Damage
- Smartwatch Algorithm Detects Cardiac Arrest
- Blood-Brain Barrier “Organ Chip” Treats Brain Tumors Unreachable by Chemotherapy
- AI Model Could Use ECG Tests to Detect Premature Aging and Cognitive Decline
- World-First Technology Uses Real-Time ECG Signal Analysis for Accurate CVAD Placement
- AI Outperforms Humans at Analyzing Long-Term ECG Recordings
- Smart Sensor Enables Precise, Self-Powered Tracking of Healing Wounds
Channels
Artificial Intelligence
view channel
Innovative Risk Score Predicts Heart Attack or Stroke in Kidney Transplant Candidates
Heart researchers have utilized an innovative risk assessment score to accurately predict whether patients being evaluated for kidney transplants are at risk for future major cardiac events, such as a... Read more
AI Algorithm Detects Early-Stage Metabolic-Associated Steatotic Liver Disease Using EHRs
Liver disease, which is treatable when detected early, often goes unnoticed until it reaches advanced stages. Metabolic-associated steatotic liver disease (MASLD), the most prevalent form of liver disease,... Read moreSurgical Techniques
view channel
Easy-To-Apply Gel Could Prevent Formation of Post-Surgical Abdominal Adhesions
Surgical adhesions are a frequent and often life-threatening complication following open or laparoscopic abdominal surgery. These adhesions develop in the weeks following surgery as the body heals.... Read more
Groundbreaking Leadless Pacemaker to Prevent Invasive Surgeries for Children
Leadless pacemakers marked a significant advancement in cardiac care, primarily because traditional pacemakers are dependent on leads, which are prone to breakage over time. Currently, two FDA-approved... Read morePatient Care
view channel
Portable Biosensor Platform to Reduce Hospital-Acquired Infections
Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more
First-Of-Its-Kind Portable Germicidal Light Technology Disinfects High-Touch Clinical Surfaces in Seconds
Reducing healthcare-acquired infections (HAIs) remains a pressing issue within global healthcare systems. In the United States alone, 1.7 million patients contract HAIs annually, leading to approximately... Read more
Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization
An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more
Game-Changing Innovation in Surgical Instrument Sterilization Significantly Improves OR Throughput
A groundbreaking innovation enables hospitals to significantly improve instrument processing time and throughput in operating rooms (ORs) and sterile processing departments. Turbett Surgical, Inc.... Read moreHealth IT
view channel
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read more
Smartwatches Could Detect Congestive Heart Failure
Diagnosing congestive heart failure (CHF) typically requires expensive and time-consuming imaging techniques like echocardiography, also known as cardiac ultrasound. Previously, detecting CHF by analyzing... Read morePoint of Care
view channel
Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour
Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Smartphone-Enabled, Paper-Based Quantitative Diagnostic Platform Transforms POC Testing
Point-of-care diagnostics are crucial for public health, offering rapid, on-site testing that enables prompt diagnosis and treatment. This is especially valuable in remote or underserved regions where... Read moreBusiness
view channel
Becton Dickinson to Spin Out Biosciences and Diagnostic Solutions Business
Becton, Dickinson and Company (BD, Franklin Lakes, NJ, USA), has announced that its board of directors has unanimously authorized BD management to pursue a plan to separate BD's Biosciences and Diagnostic... Read more