Capacity for the management of kidney failure in the International Society of Nephrology Western Europe region: report from the 2023 ISN Global Kidney Health Atlas (ISN-GKHA)

Dynamic changes in metabolic syndrome components and chronic kidney disease risk: a population-based prospective cohort study

OBJECTIVE

To investigate the relationships between dynamic changes in metabolic syndrome (MetS) components and chronic kidney disease (CKD) risk.

METHODS

Data from the UK Biobank, including baseline assessments from 2006 to 2010, repeat assessments in 2012-2013, and linked national health records, were analyzed. MetS components consisted of abdominal obesity, elevated blood pressure (BP), fasting blood glucose (FBG), serum uric acid (SUA), and lipid abnormalities. The Kaplan-Meier method and log-rank test were used to analyze CKD incidence and group differences. Cox regression models assessed the association between dynamic changes in MetS components and CKD risk.

RESULTS

The study enrolled 455,060 participants (45.7% male, 18.4% aged 65 years or older) with a median follow-up of 12.68 years. Those with MetS had a significantly higher 10-year CKD cumulative incidence probability of CKD than those without MetS (4.14% VS 1.14%). Multivariate analysis showed all baseline metabolic abnormalities were linked to CKD risk with HRs from 1.40(1.35-1.45) to 1.85 (1.78-1.92), and MetS strongly associated with CKD (HR: 2.31). CKD risk rose with more MetS components and progression stages. Notably, with FBG being the exception, the four MetS components that shifted from normal at baseline to abnormal at follow - up were associated with elevated CKD risk, with HRs (95% CI) ranging from 1.21 (1.00-1.48) to 1.73 (1.34-2.24). Participants with high baseline SUA, even if it normalized at follow - up, still faced a 1.30 - fold higher CKD risk (95% CI: 1.25-1.35), distinct from other components. For those developing one and ≥ 2 new MetS components at follow - up, the CKD risk HRs (95% CI) were 1.49 (1.00-2.35) and 2.26 (1.21-4.24) respectively.

CONCLUSION

MetS and its component changes are significantly associated with CKD risk, in a dose - response pattern. Incorporating SUA into MetS assessments enhances risk identification, especially noting females' higher susceptibility to elevated SUA. Dynamic monitoring of MetS components is crucial for assessing and predicting CKD risk.

CLINICAL TRIAL NUMBER

Not applicable.

Evidence Summary of Personalized Management of Peritoneal Dialysis Volume in Adults

Purpose

The overload capacity poses great challenges to the management and prognosis of peritoneal dialysis patients. There have been many studies, but they are relatively fragmented and inconsistent. It is urgent to summarize high-quality evidence. The objective of this study is to thoroughly investigate, extract, assess, and synthesize the most relevant evidence about the individualized management of peritoneal volume in patients undergoing peritoneal dialysis. It can be utilized in clinical practice to improve patient outcomes.

Methods

The study used the "6S" pyramid model to identify all available evidence related to the personalized management of peritoneal volume among patients receiving peritoneal dialysis. This comprehensive search encompassed various types of evidence, including guidelines, recommended practices, systematic reviews, evidence summaries, expert consensus documents, and original research studies. These were sourced from both domestic and international guideline websites, professional association platforms, as well as relevant databases. The time limit was set from the date of database creation until April 2024, with the search commencing in December 2023.

Results

The systematic search yielded 17 pieces of literature that were ultimately included in the analysis. This collection comprised seven guidelines, four best practices, two documents reflecting expert consensus, two systematic reviews, and two randomized controlled trials. The overall quality of the literature analyzed was found to be high. Through this thorough review, a total of 37 pieces of the best evidence were identified and categorized into three critical aspects: risk factors, comprehensive assessment methodologies, and various intervention strategies.

Conclusion

This study serves as a consolidation of the available evidence regarding the personalized management of peritoneal volume for patients undergoing peritoneal dialysis. It underscores the importance of clinical staff's ability to implement tailored volume management programs that address the unique circumstances of each patient.