CKD Progression, and Models

OBJECTIVE: Loss of muscle mass and sarcopenia are common in CKD and ESRD, and sarcopenia can worsen insidiously in patients with advancing CKD. The temporal dynamics of sarcopenia in patients with progressive loss of kidney function, and its association with future outcomes, is unclear. METHODS: In a contemporary national cohort of incident ESRD US veterans, we selected 661 patients who had at least two 24-hour urine creatinine (24hrUC) measurements, a surrogate of muscle mass, performed during the 3-year prelude period prior to ESRD transition...

BACKGROUND: Predicting time to renal replacement therapy (RRT) is important in patients at high risk for end-stage kidney disease. We developed and validated machine learning models for predicting the time to RRT and compared its accuracy with conventional prediction methods that uses the rate of estimated glomerular filtration rate (eGFR) decline. METHODS: Data of adult chronic kidney disease (CKD) patients who underwent hemodialysis at Oita University Hospital from April 2016 to March 2021 were extracted from electronic medical records (N = 135)...

There are cases in which CKD progression is difficult to evaluate, because the changes in estimated glomerular filtration rate (eGFR) and proteinuria sometimes show opposite directions as CKD progresses. Indices and models that enable the easy and accurate risk prediction of end-stage-kidney disease (ESKD) are indispensable to CKD therapy. In this study, we investigated whether a CKD stage coordinate transformed into a vector field (CKD potential model) accurately predicts ESKD risk. Meta-analysis of large-scale cohort studies of CKD patients in PubMed was conducted to develop the model...

BACKGROUND: Chronic kidney disease (CKD) requires accurate prediction of renal replacement therapy (RRT) initiation risk. This study developed deep learning algorithms (DLAs) to predict RRT risk in CKD patients by incorporating medical history and prescriptions in addition to biochemical investigations. METHODS: A multi-centre retrospective cohort study was conducted in three major hospitals in Hong Kong. CKD patients with an eGFR < 30ml/min/1.73m2 were included...

PURPOSE OF REVIEW: Identifying patients with risk of developing progressive chronic kidney disease (CKD) early is an important step in improving kidney care. This review discusses four recently developed models, two which predict risk of new onset disease, and two which predict progression earlier in the course of disease. RECENT FINDINGS: Several models predicting CKD incidence and progression have been recently developed and externally validated. A connecting theme across these models is the use of data beyond estimated glomerular filtration rate, allowing for greater accuracy and personalization...

INTRODUCTION: Chronic kidney disease prevention programs must identify patients at risk of early progression to provide better treatment and prolong kidney replacement therapy-free survival. Risk equations have been developed and validated in cohorts outside of Colombia, so this study aims to evaluate the discrimination and calibration of the four-variable kidney failure risk equation in a Colombian population where it has yet to be validated. METHODS: External validation study of a kidney failure risk equation using a historical cohort of patients with CKD stages 3, 4, and 5, adults without a history of dialysis or kidney transplantation with a two-year follow-up, belonging to the Baxter Renal Care Services Colombia network...

BACKGROUND: The consequences of chronic kidney disease (CKD) can be addressed with a range of pharmacotherapies primarily prescribed by nephrologists. More accurate information regarding future CKD-related pharmacotherapy requirements could guide clinical decisions including follow-up frequency. METHODS: Following assignment to derivation and validation groups (2,1), variables predicting individually future use of vitamin D receptor agonists (VDRA), phosphate binders, erythropoiesis stimulating agents (ESAs) and iron were identified using logistic regression in a prospective cohort study containing demography, comorbidity, hospitalization, laboratory, and mortality data in patients with CKD stage G4/G5 across six European countries...

BACKGROUND: To suppress the incidence of end-stage kidney disease, we need to identify chronic kidney disease (CKD) patients with a high risk of rapid decline in the estimated glomerular filtration rate (eGFR). However, the current status of eGFR slope and its associated factors in the Japanese population have not been fully elucidated. METHODS: Among examinees aged 40-70 years in the 2014 Specific Health Checkup conducted by the National Health Insurance in Kobe, Japan (n = 61,985), we prospectively observed 7291 examinees with CKD stage G3 from 2014 to 2018...

OBJECTIVE: We conducted a community-based cohort study to predict the 3-year occurrence of chronic kidney disease (CKD) among population aged ≥60 years. METHOD: Participants were selected from two communities through randomized cluster sampling in Jiading District of Shanghai, China. The two communities were randomly divided into a development cohort ( n  = 12012) and a validation cohort ( n  = 6248) with a 3-year follow-up...

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INTRODUCTION: End-stage kidney disease (ESKD) is associated with increased morbidity and mortality. Identifying patients with stage 4 CKD (CKD4) at risk of rapid progression to ESKD remains challenging. Accurate prediction of CKD4 progression can improve patient outcomes by improving advanced care planning and optimizing healthcare resource allocation. METHODS: We obtained electronic health record data from patients with CKD4 in a large health system between January 1, 2006, and December 31, 2016...

INTRODUCTION: The kidney failure risk equation (KFRE) estimates a person's risk of kidney failure and has great potential utility in clinical care. METHODS: We used mixed methods to explore implementation of the KFRE in nephrology clinics. RESULTS: KFRE scores were integrated into the electronic health record at Johns Hopkins Medicine and were displayed to nephrology providers. Documentation of KFRE scores increased over time, reaching 25% of eligible outpatient nephrology clinic notes at month 11...

Prognostic models can strongly support individualized care provision and well-informed shared decision making. There has been an upsurge of prognostic research in the field of nephrology, but the uptake of prognostic models in clinical practice remains limited. Therefore, we map out the research field of prognostic models for kidney patients and provide directions on how to proceed from here. We performed a scoping review of studies developing, validating, or updating a prognostic model for patients with CKD...

BACKGROUND: Mortality following hemodialysis initiation may influence the decision to initiate hemodialysis in elderly patients. Our objective is to demonstrate mortality following hemodialysis initiation in elderly (≥70 years) and to derive a prediction risk score based on clinical and laboratory indicators to determine risk of all-cause mortality in patients aged ≥80 years. METHODS: We identified elderly (≥70 years) who initiated maintenance hemodialysis between January 2005 and December 2016 using data from the Thai Renal Replacement Therapy Registry...

Chronic kidney disease (CKD) has become a major global health crisis, causing millions of yearly deaths. Predicting the possibility of a person being affected by the disease will allow timely diagnosis and precautionary measures leading to preventive strategies for health. Machine learning techniques have been popularly applied in various disease diagnoses and predictions. Ensemble learning approaches have become useful for predicting many complex diseases. In this paper, we utilise the boosting method, one of the popular ensemble learnings, to achieve a higher prediction accuracy for CKD...

Chronic kidney disease (CKD) remains one of the most prominent global causes of mortality worldwide, necessitating accurate prediction models for early detection and prevention. In recent years, machine learning (ML) techniques have exhibited promising outcomes across various medical applications. This study introduces a novel ML-driven monogram approach for early identification of individuals at risk for developing CKD stages 3-5. This retrospective study employed a comprehensive dataset comprised of clinical and laboratory variables from a large cohort of diagnosed CKD patients...

Chronic kidney disease (CKD) is a multifactorial, complex condition that requires proper management to slow its progression. In Thailand, 11.6 million people (17.5%) have CKD, with 5.7 million (8.6%) in the advanced stages and >100,000 requiring hemodialysis (2020 report). This study aimed to develop a risk prediction model for CKD in Thailand. Data from 17,100 patients were collected to screen for 14 independent variables selected as risk factors, using the IBK, Random Tree, Decision Table, J48, and Random Forest models to train the predictive models...

BACKGROUND: Multiparametric renal Magnetic Resonance Imaging (MRI) provides a non-invasive method to assess kidney structure and function, but longitudinal studies are limited. METHODS: A total of 22 patients with CKD category G3-4 (estimated glomerular filtration rate (eGFR) 15-59 mL/min/1.73 m2 ) were recruited. Annual 3T multiparametric renal MRI scans were performed, comprising total kidney volume (TKV), longitudinal relaxation time (T1 ), apparent diffusion coefficient (ADC), Arterial Spin Labelling, and Blood Oxygen Level Dependent relaxation time (T2 *), with 15 patients completing a Year 2 scan...

BACKGROUND/PURPOSE: Predictive modeling aids in identifying patients at high risk of adverse events. Using routinely collected data, we report a competing risk prediction model for kidney failure. METHODS: A total of 5138 patients with CKD stages 3b-5 were included and randomized into the development and validation cohorts at a ratio of 7:3. The outcome was end-stage kidney disease, defined as the initiation of dialysis or kidney transplantation. All patients were followed-up until December 31, 2020...

INTRODUCTION: Chronic kidney disease (CKD) rapid progression is associated with higher risk of end-stage kidney disease and higher mortality rate. Monitoring and recognition of CKD rapid progression is still lacking, however interventions have been shown to improve this. Thus, this study aimed to evaluate the acceptability and feasibility of CKD-CHECK toolkit and preliminary measure the outcome of the CKD-CHECK toolkit in assisting primary care doctor to order further tests for CKD rapid progressors and trigger appropriate nephrology referral...