Glycemic status, adiposity indices and cardiovascular risk in chronic kidney disease: Core findings from a nationwide cohort study

Table 1 Summary of limitations and optimization suggestions

Core dimensions	Key points
Study subjects	Korean National Health Insurance Database, 1714859 patients with CKD
Study purpose	To analyze the combined effects of glycemic status (Normal, IFG, DM) and adiposity indices (BMI, WC) on CVD and all-cause mortality in patients with CKD
Core findings	Normal: Low body weight (HR = 1.12) and central obesity (men with WC ≥ 100 cm/women with ≥ 95 cm, HR = 1.16) both increase the risk. IFG: Low body weight is a stable risk factor (HR = 1.25). WC is linearly correlated with the risk of CVD, but not with mortality. DM: Those with low body weight (BMI < 18.5 kg/m2) and low WC (men < 80 cm/women < 75 cm) have the highest risk of CVD (HR = 2.12/1.72)
Core conclusions	It is necessary to combine glycemic status and obesity phenotype to conduct individualized cardiovascular risk stratification and intervention for patients with CKD
Study limitations	Lack of dynamic data on body composition, failure to consider gender differences, and it was an observational study that could not draw causal relationships

CKD: Chronic kidney disease; IFG: Impaired fasting glucose; DM: Diabetes mellitus; BMI: Body mass index; WC: Waist circumference; CVD: Cardiovascular disease; HR: Hazard ratio.

Table 2 Summary of limitations and optimization suggestions

Limitations	Core issues	Optimization suggestions
Obesity assessment index is too single	Unable to distinguish between body fat rate and muscle mass, ignoring the impact of muscle loss in patients with CKD	DXA or BIA could be used to evaluate body composition, including body fat rate and muscle mass index. Indicators such as BRI and VAI can enhance the accuracy of CVD assessment
Not stratified by eGFR	There are differences in metabolic status in different stages of CKD, and their risk models may also vary accordingly	When analyzing the risk association between blood glucose and obesity, CKD should be classified by stages according to eGFR
Lack of long-term glycemic control assessment	The regulatory effect of long-term blood glucose control on obesity-related CVD risk is not clear	TIR derived from CGM and HbA1c index (for long-term monitoring) could be included to analyze the correlation between the quality of blood glucose control and risk
Not studied targeted intervention	Clinical intervention programs corresponding to different risk stratification have not been studied	Intervention research should be carried out to verify the effectiveness of personalized nutrition, exercise, and drug intervention
Inadequate ethnic representation	The study was based on the data of the Korean population only, so universality was limited	A multi-ethnic, multi-center cohort study should be conducted to verify the cross-ethnic applicability of the risk model

CKD: Chronic kidney disease; DXA: Dual-energy X-ray absorptiometry; BIA: Bioelectrical impedance analysis; BRI: Body roundness index; VAI: Visceral adiposity index; CVD: Cardiovascular disease; TIR: Time-in-range; CGM: Continuous glucose monitoring; HbA1c: Hemoglobin A1c.