A vivid depiction of an elderly patient receiving kidney treatment in a modern clinical setting. Background includes medical staff analyzing predictive models on digital screens. The patient appears hopeful, engaging with a healthcare provider discussing future health risks. Medical environment looks clean and technologically advanced, emphasizing precision healthcare.
Chronic kidney disease (CKD) impacts up to 10% of adults globally. While many affected individuals live without severe symptoms, those with moderate to severe stages of CKD face an increased risk of kidney failure and death. Current predictive tools only focus on one of these outcomes, often neglecting mortality.
The KDpredict model aims to address this gap. Developed in Canada and tested across Denmark and Scotland, KDpredict provides simultaneous predictions for both kidney failure and death. This dual approach supports more comprehensive patient-centered care.
A Tool for Both Kidney Failure and Mortality Prediction
The KDpredict tool employs a “super learner” strategy, integrating various predictive models to offer the best accuracy. According to Dr. Pietro Ravani from the University of Calgary, the model helps to “shift away from the limitations of existing benchmarks” by accounting for competing risks such as death. KDpredict predicts one to five-year risks for each outcome, providing insights that shape treatment decisions.
One of the key advancements of KDpredict is its flexibility. “The model is designed to be adapted and revised to suit local clinical needs,” explains co-author Dr. Simon Sawhney. This ensures that as healthcare systems evolve, the predictive model remains relevant and accurate.
Improving Accuracy Across Multiple Countries
The study involved a diverse cohort of nearly 93,000 patients from three countries: Canada, Denmark, and Scotland. The patients had moderate to severe CKD, with follow-up periods ranging from five to six years. Dr. Christian Fynbo Christiansen highlighted the model’s ability to predict kidney failure with greater accuracy, especially in patients with CKD stage G3b to G4.
In particular, KDpredict outperformed the widely-used Kidney Failure Risk Equation (KFRE) by providing more accurate and tailored predictions. According to the research, KDpredict’s five-year index of prediction accuracy reached 30.5% in Scotland, compared to only 14.2% with KFRE.
Application and Clinical Use
KDpredict is already available for use in clinical settings through online platforms. Clinicians can use the tool to provide personalized risk assessments for their patients. “We’ve created a tool that not only predicts kidney failure risk but also death, offering a more holistic approach to care,” notes Dr. Ravani.
Patients with CKD are now able to engage in better-informed discussions about their care. The KDpredict model supports shared decision-making between healthcare providers and patients. By considering both kidney failure and mortality risks, clinicians can prioritize treatments that align with individual health goals.
Why KDpredict Matters for CKD Patients
KDpredict fills a critical need in nephrology by offering a balanced view of CKD outcomes. Dr. Sawhney adds, “For the first time, we can talk to patients not just about their risk of kidney failure but also their overall health and longevity.” This represents a significant leap forward in managing chronic kidney disease and its associated risks.
The study concludes that KDpredict is a valuable tool for CKD management. Its ability to predict both kidney failure and death ensures more accurate treatment decisions, making it an indispensable resource for nephrologists and patients alike.
Citation:
Liu P, Sawhney S, Heide-Jørgensen U, et al. Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease: multinational, longitudinal, population based, cohort study. BMJ. 2024;385. doi:10.1136/bmj-2023-078063.
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