Significance statement: The prognostic significance of variabilities in body mass index (BMI) or metabolic parameters in patients with CKD is uncertain. In this observational cohort study of 84,636 patients with predialysis CKD in South Korea, the authors analyzed the association between variability of BMI or various metabolic parameters and risks of all-cause mortality and incident myocardial infarction, stroke, and requirement for KRT. They found that elevated variability in BMI or certain metabolic parameters was associated with higher risks of adverse outcomes, independent of baseline metabolic status. These findings may encourage clinicians in the nephrology field to carefully assess not only baseline BMI or metabolic status in patients with CKD, but also the fluctuating status of metabolic parameters, due to their potential prognostic significance in such patients. Background: The association between variabilities in body mass index (BMI) or metabolic parameters and prognosis of patients with CKD has rarely been studied. Methods: In this retrospective observational study on the basis of South Korea’s national health screening database, we identified individuals who received ≥3 health screenings, including those with persistent predialysis CKD (eGFR <60 ml/min per 1.73 m² or dipstick albuminuria ≥1). The study exposure was variability in BMI or metabolic parameters until baseline assessment, calculated as the variation independent of the mean and stratified into quartiles (with Q4 the highest quartile and Q1 the lowest). We used Cox regression adjusted for various clinical characteristics to analyze risks of all-cause mortality and incident myocardial infarction, stroke, and KRT. Results: The study included 84,636 patients with predialysis CKD. Comparing Q4 versus Q1, higher BMI variability was significantly associated with higher risks of all-cause mortality (hazard ratio [HR], 1.66; 95% confidence interval [95% CI], 1.53 to 1.81), P [for trend] <0.001), KRT (HR, 1.20; 95% CI, 1.09 to 1.33; P<0.001), myocardial infarction (HR, 1.19; 95% CI, 1.05 to 1.36, P=0.003), and stroke (HR, 1.19; 95% CI, 1.07 to 1.33, P=0.01). The results were similar in the subgroups divided according to positive or negative trends in BMI during the exposure assessment period. Variabilities in certain metabolic syndrome components (e.g., fasting blood glucose) also were significantly associated with prognosis of patients with predialysis CKD. Those with a higher number of metabolic syndrome components with high variability had a worse prognosis. Conclusions: Higher variabilities in BMI and certain metabolic syndrome components are significantly associated with a worse prognosis in patients with predialysis CKD.

Blood homocysteine level and related vitamin levels are associated with various health outcomes. We aimed to assess causal effects of blood homocysteine, folate, and cobalamin on kidney function in the general population by performing Mendelian randomization (MR) analysis. Genetic instruments for blood homocysteine, folate, and cobalamin levels were introduced from a previous genome-wide association (GWAS) meta-analysis of European individuals. Summary-level MR analysis was performed for the estimated glomerular filtration rate (eGFR) from the CKDGen consortium GWAS that included 567,460 European ancestry individuals. For replication, allele-score-based MR was performed with an independent U.K. Biobank cohort of 337,138 individuals of white British ancestry. In summary-level MR for the CKDGen data, high genetically predicted homocysteine levels were significantly associated with low eGFR (per 1 standard deviation, beta for eGFR change −0.95 (−1.21, −0.69) %), supported by pleiotropy-robust MR sensitivity analysis. Genetically predicted high folate levels were significantly associated with high eGFR change (0.86 (0.30, 1.42) %); however, causal estimates from cobalamin were nonsignificant (−0.11 (−0.33, 0.11) %). In the U.K. Biobank data, the results were consistently identified. Therefore, a high blood homocysteine level causally decreases eGFR. Future trials with appropriate homocysteine-lowering interventions may be helpful for the primary prevention of kidney function impairment.

Background: Precise prediction of contrast media–induced acute kidney injury (CIAKI) is an important issue because of its relationship with poor outcomes. Objective: Herein, we examined whether a deep learning algorithm could predict the risk of intravenous CIAKI better than other machine learning and logistic regression models in patients undergoing computed tomography (CT). Methods: A total of 14,185 patients who were administered intravenous contrast media for CT at the preventive and monitoring facility in Seoul National University Hospital were reviewed. CIAKI was defined as an increase in serum creatinine of ≥0.3 mg/dL within 2 days or ≥50% within 7 days. Using both time-varying and time-invariant features, machine learning models, such as the recurrent neural network (RNN), light gradient boosting machine (LGM), extreme gradient boosting machine (XGB), random forest (RF), decision tree (DT), support vector machine (SVM), κ-nearest neighbors, and logistic regression, were developed using a training set, and their performance was compared using the area under the receiver operating characteristic curve (AUROC) in a test set. Results: CIAKI developed in 261 cases (1.8%). The RNN model had the highest AUROC of 0.755 (0.708-0.802) for predicting CIAKI, which was superior to that obtained from other machine learning models. Although CIAKI was defined as an increase in serum creatinine of ≥0.5 mg/dL or ≥25% within 3 days, the highest performance was achieved in the RNN model with an AUROC of 0.716 (95% confidence interval [CI] 0.664-0.768). In feature ranking analysis, the albumin level was the most highly contributing factor to RNN performance, followed by time-varying kidney function. Conclusions: Application of a deep learning algorithm improves the predictability of intravenous CIAKI after CT, representing a basis for future clinical alarming and preventive systems.

Kidney volume is used as a predictive and therapeutic marker for several clinical conditions. However, there is a lack of large-scale studies examining the relationship between kidney volume and various clinicodemographic factors, including kidney function, body composition and physical performance. In this observational study, MRI-derived kidney volume measurements from 38 526 UK Biobank participants were analysed. Major kidney volume–related measures included body surface area (BSA)-adjusted total kidney volume (TKV) and the difference in bilateral kidneys. Multivariable-adjusted linear regression and cubic spline analyses were used to explore the association between kidney volume–related measures and clinicodemographic factors. Cox or logistic regression was used to identify the risks of death, non-kidney cancer, myocardial infarction, ischaemic stroke and chronic kidney disease (CKD). The median of BSA-adjusted TKV and the difference in kidney volume were 141.9 ml/m² [interquartile range (IQR) 128.1–156.9] and 1.08-fold (IQR 1.04–1.15), respectively. Higher BSA-adjusted TKV was significantly associated with higher estimated glomerular filtration rate {eGFR; β = 0.43 [95% confidence interval (CI) 0.42–0.44]; P < .001}, greater muscle volume [β = 0.50 (95% CI 0.48–0.51); P < .001] and greater mean handgrip strength [β = 0.15 (95% CI 0.13–0.16); P < .001] but lower visceral adipose tissue volume [VAT; β = −0.09 (95% CI −0.11 to −0.07); P < .001] in adjusted models. A greater difference in bilateral kidney volumes was associated with lower eGFR, muscle volume and physical performance but with higher proteinuria and VAT. Higher BSA-adjusted TKV was significantly associated with a reduced risk of CKD [odds ratio (OR) 0.7 (95% CI 0.63–0.77); P < .001], while a greater difference in kidney volume was significantly associated with an increased risk of CKD [OR 1.13 (95% CI 1.07–1.20); P < .001]. Higher BSA-adjusted TKV and lower differences in bilateral kidney volumes are associated with higher kidney function, muscle volume and physical performance and a reduced risk of CKD.

Background: The genetically predicted lipid-lowering effect of HMGCR or PCSK9 variant can be used to assess drug proxy effects on kidney function.Methods: Mendelian randomization (MR) analysis-identified HMGCR and PCSK9 genetic variants were used to predict the low-density lipoprotein (LDL) cholesterol-lowering effects of medications targeting related molecules. Primary summary-level outcome data for log-estimated glomerular filtration rate (eGFR; creatinine) were provided by the CKDGen Consortium (n = 1,004,040 European) from a meta-analysis of CKDGen and UK Biobank data. We also conducted a separate investigation of summary-level data from CKDGen (n = 567,460, log-eGFR [creatinine]) and UK Biobank (n = 436,581, log-eGFR [cystatin C]) samples. Summary-level MRs using an inverse variance weighted method and pleiotropy-robust methods were performed.Results: Summary-level MR analysis indicated that the LDL-lowering effect predicted genetically by HMGCR variants (50-mg/dL decrease) was significantly associated with a decrease in eGFR (–1.67%; 95% confidence interval [CI], –2.20% to –1.13%). Similar significance was found in results from the pleiotropy-robust MR methods when the CKDGen and UK Biobank data were analyzed separately. However, the LDL-lowering effect predicted genetically by PCSK9 variants was significantly associated with an increase in eGFR (+1.17%; 95% CI, 0.10%–2.25%). The results were similarly supported by the weighted median method and in each CKDGen and UK Biobank dataset, but the significance obtained by MR-Egger regression was attenuated.Conclusion: Genetically predicted HMG-CoA reductase inhibition was associated with low eGFR, while genetically predicted PCSK9 inhibition was associated with high eGFR. Clinicians should consider that the direct effect of different types of lipid-lowering medication on kidney function can vary.

The association between visit-to-visit blood pressure (BP) variability and dementia risk in chronic kidney disease (CKD) patients has rarely been studied. In this retrospective observational study, individuals who received three or more general health screenings were identified in the nationwide database of Korea. Those with persistent non-dialysis-dependent CKD [estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m² or dipstick albuminuria ≥1+] were included. The study exposure was systolic or diastolic BP variability, calculated as the variation independent of the mean and categorized into quartiles (Q4: the highest quartile; Q1: the lowest quartile). The risks of all-cause dementia, including Alzheimer's disease and vascular dementia, were analyzed by Cox regression adjusted for various clinical characteristics, including baseline BP and eGFR values. We included 103 139 CKD patients and identified 7574 (7%) dementia events, including 5911 (6%) Alzheimer's disease cases, 886 (1%) vascular dementia events and 777 (1%) cases categorized as other types of dementia. Higher systolic BP variability was significantly associated with higher risks of all-cause dementia {[Q4 versus Q1], hazard ratio [HR] 1.173 [95% confidence interval (CI) 1.102–1.249], P for trend < .001}. The results were also significant for the risk of Alzheimer's disease [HR 1.162 (95% CI 1.083–1.248), P < .001] and vascular dementia [HR 1.282 (95% CI 1.064–1.545), P = .039]. The results were similar when diastolic BP variability was the exposure, as high diastolic BP variability was significantly associated with higher risks of all-cause dementia [HR 1.191 (95% CI 1.117,1.270), P < .001]. Higher visit-to-visit BP variability is significantly associated with a higher risk of dementia in CKD patients.