Two-year longitudinal trajectory patterns of albuminuria and subsequent rates of end-stage kidney disease and all-cause death: a nationwide cohort study of biopsy-proven diabetic kidney disease

Longitudinal studies: focus on trajectory analysis in kidney diseases

Longitudinal cohort studies are pivotal in medical research for understanding disease progression over time. These studies track a group of individuals across multiple time points, enabling the identification of risk factors and the evaluation of interventions. Traditional methods like linear mixed models, generalized estimating equations, and survival analysis often fall short in capturing the complex, non-linear patterns of disease progression. Trajectory analysis, a statistical technique that identifies distinct paths within longitudinal data, offers a more nuanced approach. This review delves into the methodological foundations of trajectory analysis, including data preparation, model selection, parameter estimation, model evaluation, and interpretation. It highlights the advantages of trajectory analysis, such as its ability to capture heterogeneity, handle various data types, and enhance predictive power. The application of trajectory analysis in nephrology, particularly in chronic kidney disease and diabetic nephropathy, demonstrates its utility in identifying distinct subgroups with different disease trajectories. Studies have shown that trajectory analysis can uncover patterns of renal function decline and proteinuria progression, providing insights that inform personalized treatment strategies. Despite its strengths, trajectory analysis requires advanced statistical knowledge, computational resources, and large sample sizes, which can be barriers for some researchers. Nevertheless, its ability to reveal complex disease patterns and improve predictive accuracy makes it a valuable tool in longitudinal studies. This review underscores the potential of trajectory analysis to enhance our understanding of disease progression and improve patient outcomes in nephrology and beyond.

Renalase protects against podocyte injury by inhibiting oxidative stress and apoptosis in diabetic nephropathy

Diabetic nephropathy (DN) presents a significant public health challenge due to its high rate of incidence and severe health consequences. Renalase has been identified as having renal-protective properties. A key contributor to albuminuria in DN patients is podocyte loss. The function of Renalase in DN in relation to podocyte activity needs to be explored further. In this study, we assessed the therapeutic efficacy of Renalase by monitoring changes in urine protein levels and podocyte health in db/db mice. We also induced hyperglycemia (HG) to stimulate podocyte clone 5 (MPC5) cells to create a model of podocyte loss in DN. Through co-culturing these cells with Renalase or H2O2, we investigated the process by which Renalase prevents podocyte loss in vitro. In db/db mice, Renalase expression was significantly reduced, and adenoviral-mediated Renalase expression markedly alleviated DN symptoms and proteinuria. Furthermore, podocytopathy in db/db mice was significantly mitigated. In vitro, Renalase improved the expression of podocyte marker proteins, podocin, and nephrin, which are reduced by HG, as well as decreased oxidative stress and restrained apoptosis. Our findings suggest that Renalase can mitigate DN by reducing proteinuria through podocyte protection, potentially by inhibiting oxidative stress and apoptosis. These data suggest that Renalase may serve as a novel therapeutic agent in suppressing DN.

Association of the longitudinal trajectory of urinary albumin/creatinine ratio in diabetic patients with adverse cardiac event risk: a retrospective cohort study

Objective

The baseline urinary albumin/creatinine ratio (uACR) has been proven to be significantly associated with the risk of major adverse cardiac events (MACE). However, data on the association between the longitudinal trajectory patterns of uACR, changes in glycated hemoglobin A1c (HbA1c), and the subsequent risk of MACE in patients with diabetes are sparse.

Methods

This is a retrospective cohort study including 601 patients with type 2 diabetes mellitus (T2DM; uACR < 300 mg/g) admitted to The First Hospital of Shanxi Medical University and The Second Hospital of Shanxi Medical University from January 2015 to December 2018. The uACR index was calculated as urinary albumin (in milligrams)/creatinine (in grams), and latent mixed modeling was used to identify the longitudinal trajectory of uACR during the exposure period (2016-2020). The deadline for follow-up was December 31, 2021. The primary outcome was the MACE [a composite outcome of cardiogenic death, hospitalization related to heart failure (HHF), non-fatal acute myocardial infarction, non-fatal stroke, and acute renal injury/dialysis indications]. The Kaplan-Meier survival analysis curve was used to compare the risk of MACE among four groups, while univariate and multivariate Cox proportional hazards models were employed to calculate the hazard ratio (HR) and 95% confidence interval (CI) for MACE risk among different uACR or HbA1c trajectory groups. The predictive performance of the model, both before and after the inclusion of changes in the uACR and HbA1c, was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC).

Results

Four distinct uACR trajectories were identified, namely, the low-stable group (uACR = 5.2-38.3 mg/g, n = 112), the moderate-stable group (uACR = 40.4-78.6 mg/g, n = 229), the high-stable group (uACR = 86.1-153.7 mg/g, n = 178), and the elevated-increasing group (uACR = 54.8-289.4 mg/g, n = 82). In addition, five distinct HbA1c trajectories were also identified: the low-stable group (HbA1c = 5.5%-6.8%, n = 113), the moderate-stable group (HbA1c = 6.0%-7.9%, n = 169), the moderate-decreasing group (HbA1c = 7.4%-6.1%, n = 67), the high-stable group (HbA1c = 7.7%-8.9%, n = 158), and the elevated-increasing group (HbA1c = 8.4%-10.3%, n = 94). Compared with the low-stable uACR group, patients in the high-stable and elevated-increasing uACR groups were more likely to be older, current smokers, and have a longer DM course, higher levels of 2-h plasma glucose (PG), HbA1c, N-terminal pro-B-type natriuretic peptide (NT-proBNP), uACR, and left ventricular mass index (LVMI), while featuring a higher prevalence of hypertension and a lower proportion of β-receptor blocker treatment (p < 0.05). During a median follow-up of 45 months (range, 24-57 months), 118 cases (19.6%) of MACE were identified, including 10 cases (1.7%) of cardiogenic death, 31 cases (5.2%) of HHF, 35 cases (5.8%) of non-fatal acute myocardial infarction (AMI), 18 cases (3.0%) of non-fatal stroke, and 24 cases (4.0%) of acute renal failure/dialysis. The Kaplan-Meier survival curve showed that, compared with that in the low-stable uACR group, the incidence of MACE in the high-stable (HR = 1.337, 95% CI = 1.083-1.652, p = 0.007) and elevated-increasing (HR = 1.648, 95% CI = 1.139-2.387, p = 0.009) uACR groups significantly increased. Similar results were observed for HHF, non-fatal AMI, and acute renal injury/dialysis indications (p < 0.05). The multivariate Cox proportional hazards models indicated that, after adjusting for potential confounders, the HRs for the risk of MACE were 1.145 (p = 0.132), 1.337 (p = 0.007), and 1.648 (p = 0.009) in the moderate-stable, high-stable, and elevated-increasing uACR groups, respectively. In addition, the HRs for the risk of MACE were 1.203 (p = 0.028), 0.872 (p = 0.024), 1.562 (p = 0.033), and 2.218 (p = 0.002) in the moderate-stable, moderate-decreasing, high-stable, and elevated-increasing groups, respectively. The ROC curve showed that, after adding uACR, HbA1c, or both, the AUCs were 0.773, 0.792, and 0.826, which all signified statistically significant improvements (p = 0.021, 0.035, and 0.019, respectively).

Conclusion

A long-term elevated uACR is associated with a significantly increased risk of MACE in patients with diabetes. This study implies that regular monitoring of uACR could be helpful in identifying diabetic patients with a higher risk of MACE.

Lower urinary albumin-to-creatinine ratio predicted all-cause and cardiovascular mortality in Chinese population with diabetes and prediabetes-The Shanghai Changfeng cohort study

INTRODUCTION

Elevated urinary albumin-to-creatinine ratio (UACR) was associated with increased mortality in general population and diabetic patients. However, whether the association remains similar in the subjects with different status of glucose metabolism was unclear. The optimal level of UACR in predicting mortality also remained unknown. This study aims to investigate the relationship between UACR with all-cause and cardiovascular mortality in population with different status of glucose metabolism and explore the predictive cutoff point of UACR.

METHODS

Six thousand three hundred and eighty-six community-dwelling individuals aged ≥45 years were enrolled and followed for an average of 5.3 years. Cox proportional hazards model was performed to analysis the association of baseline UACR and all-cause as well as cardiovascular mortality according to the status of glucose metabolism. Receiver operating characteristic curve was plotted to explore the optimal predictive cutoff point of UACR.

RESULTS

With UACR increasing, both the prevalence of all-cause and cardiovascular death increased. Cox analyses showed baseline UACR independently predicted the risk of all-cause and cardiovascular mortality in the patients with prediabetes mellitus (pre-DM) and diabetes mellitus (DM) but not in subjects with normal glucose tolerance (NGT). When divided by quartiles of UACR, the cumulative survival rate decreased acrossing the quartiles. Compared to the subjects with lowest quartile of UACR, participants with UACR ≥7.40 mg/gCr had a higher risk of all-cause mortality, and participants with UACR ≥16.60 mg/gCr had an increased risk of cardiovascular mortality in all hyperglycemia subjects. The optimal predictive cutoff point of UACR was about 17 mg/gCr.

CONCLUSION

UACR was an independent predictor of all-cause and cardiovascular mortality in population with pre-DM and DM but not in the subjects with NGT. The optimal predictive cutoff point of UACR is about 17 mg/gCr, which was far below the diagnostic cutoff point of microalbuminuria. Earlier interventions of albuminuria should be initiated from very early stage of hyperglycemia to reduce the burden of death in all patients whose glucose metabolism are impaired.

Risk Factors and Comorbidities Associated with Diabetic Kidney Disease

Introduction/objectives:

Diabetic Kidney Disease (DKD) is the leading cause of end-stage kidney disease. Despite optimal glycemic control and blood pressure management, progression to DKD cannot be halted in some patients. We aimed to find the association of modifiable and non-modifiable risk factors and comorbid conditions in patients with DKD.

Methods:

Retrospective medical record review of adult patients with diabetes mellitus (DM) was performed who visited our internal medicine office between January 1, 2020 and December 31, 2020.

Results:

Among 728 patients with DM, 471 (64.7%) patients had DKD, and 257 (35.3%) patients were without DKD. Among the group of patients with DKD, the majority were in CKD stage G1A2 (34.6%), followed equally by G2A2 and G3aA1 (16.8% each). Mean age of the patients with DKD was significantly greater than the patients without DKD (69.4 years vs 62.2 years; P < .001). For each unit increase in age, there was a 7.8% increase in the odds of DKD (95% CI 5.3-10.4; P < .001). Women had 2.32 times greater odds of DKD (95% CI, 1.41-3.81; P = .001). We found decreased odds of DKD for those who consumed alcohol moderately (OR 0.612, 95% CI 0.377-0.994; P < .05). Significantly higher frequencies of associations of several comorbid medical conditions were seen in patients with DKD compared to the patients without DKD, such as hypertension (91.9% vs 75.6%), hyperlipidemia (86.6% vs 78.2%), coronary artery disease (39.3% vs 16.8%), cerebrovascular accidents (13.4% vs 7.4%), congestive heart failure (12.9% vs 4.1%), carotid artery stenosis (11.3% vs 2.6%), aortic aneurysm (5.4% vs 2.0%), peripheral artery disease (10.8% vs 3.5%), gout (12.4% vs 5.5%), and osteoarthritis (41.4% vs 31.2%).

Conclusions:

In patients with diabetes, increasing age, female sex, and lack of moderate alcohol consumption were associated with increased odds of DKD. Higher frequencies of association of hypertension, hyperlipidemia, coronary artery disease, cerebrovascular accidents, congestive heart failure, carotid artery stenosis, aortic aneurysm, peripheral artery disease, gout, and osteoarthritis were also seen in patients with DKD.