Addition of nonalbumin proteinuria to albuminuria improves prediction of type 2 diabetic nephropathy progression

Urinary non-albumin protein-creatinine ratio is an independent predictor of mortality in patients with type 2 diabetes: a retrospective cohort study

Albuminuria is a well-known predictor of chronic kidney disease in patients with type 2 diabetes mellitus (DM). However, proteinuria is associated with chronic complications in patients without albuminuria. In this retrospective cohort study, we explored whether non-albumin proteinuria is associated with all-cause mortality and compared the effects of non-albumin proteinuria on all-cause mortality between patients with and without albuminuria. We retrospectively collected data from patients with type 2 DM for whom we had obtained measurements of both urinary albumin-to-creatinine ratio (UACR) and urinary protein-to-creatinine ratio (UPCR) from the same spot urine specimen. Urinary non-albumin protein-creatinine ratio (UNAPCR) was defined as UPCR-UACR. Of the 1809 enrolled subjects, 695 (38.4%) patients died over a median follow-up of 6.4 years. The cohort was separated into four subgroups according to UACR (30 mg/g) and UNAPCR (120 mg/g) to examine whether these indices are associated with all-cause mortality. Compared with the low UACR and low UNAPCR subgroup as the reference group, multivariable Cox regression analyses indicated no significant difference in mortality in the high UACR and low UNAPCR subgroup (hazard ratio [HR] 1.189, 95% confidence interval [CI] 0.889-1.589, P = 0.243), but mortality risks were significantly higher in the low UACR and high UNAPCR subgroup (HR 2.204, 95% CI 1.448-3.356, P < 0.001) and in the high UACR with high UNAPCR subgroup (HR 1.796, 95% CI 1.451-2.221, P < 0.001). In the multivariable Cox regression model with inclusion of both UACR and UNAPCR, UNAPCR ≥ 120 mg/g was significantly associated with an increased mortality risk (HR 1.655, 95% CI 1.324-2.070, P < 0.001), but UACR ≥ 30 mg/g was not significantly associated with mortality risk (HR 1.046, 95% CI 0.820-1.334, P = 0.717). In conclusion, UNAPCR is an independent predictor of all-cause mortality in patients with type 2 DM.

Machine Learning Models for Prediction of Diabetic Microvascular Complications

IMPORTANCE AND AIMS

Diabetic microvascular complications significantly impact morbidity and mortality. This review focuses on machine learning/artificial intelligence (ML/AI) in predicting diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN).

METHODS

A comprehensive PubMed search from 1990 to 2023 identified studies on ML/AI models for diabetic microvascular complications. The review analyzed study design, cohorts, predictors, ML techniques, prediction horizon, and performance metrics.

RESULTS

Among the 74 identified studies, 256 featured internally validated ML models and 124 had externally validated models, with about half being retrospective. Since 2010, there has been a rise in the use of ML for predicting microvascular complications, mainly driven by DKD research across 27 countries. A more modest increase in ML research on DR and DN was observed, with publications from fewer countries. For all microvascular complications, predictive models achieved a mean (standard deviation) c-statistic of 0.79 (0.09) on internal validation and 0.72 (0.12) on external validation. Diabetic kidney disease models had the highest discrimination, with c-statistics of 0.81 (0.09) on internal validation and 0.74 (0.13) on external validation, respectively. Few studies externally validated prediction of DN. The prediction horizon, outcome definitions, number and type of predictors, and ML technique significantly influenced model performance.

CONCLUSIONS AND RELEVANCE

There is growing global interest in using ML for predicting diabetic microvascular complications. Research on DKD is the most advanced in terms of publication volume and overall prediction performance. Both DR and DN require more research. External validation and adherence to recommended guidelines are crucial.

Non-albumin proteinuria marks tubular involvement and is associated with arterial stiffness in subjects affected by severe obesity

INTRODUCTION

Obesity is a well-established risk factor for kidney disease, and tubular damage can play a pivotal role in the development of obesity-related kidney damage. This study aimed to investigate the pathophysiological pathways involved in the development of non-albumin proteinuria (NAP), a marker of tubular involvement, in a cohort of subjects with severe obesity and preserved kidney function.

METHODS

A total of 106 subjects with BMI ≥ 35 kg/m2 in waiting list for bariatric surgery underwent blood chemistry analysis including metabolic and lipid profile, vascular tests for cardiovascular risk stratification and a comprehensive assessment of kidney function, including renal resistive index (RRI) and NAP measurement.

RESULTS

Nineteen patients with ACR ≥ 30 mg/g regardless of NAP values (ALB+), nineteen with NAP≥ 150 mg/g and albuminuria < 30 mg/g (iNAP) and sixty-eight without proteinuria (No-P) were found. Both ALB+ and iNAP groups exhibited a higher prevalence of hypertension and anti-hypertensive treatment compared to No-P, while the prevalence of diabetes was similar between groups. Concerning lipid profile, no differences in total, HDL and LDL cholesterol were found, while ALB+ patients had higher serum triglyceride levels than the other two groups. RRI and carotid-femoral pulse wave velocity (cf-PWV) was significantly higher in ALB+ and iNAP groups compared to No-P. Remarkably, cf-PWV remained still significant after adjustment for age, sex and MBP (p = 0.0004). In overall population, a multiple regression analysis showed that cf-PWV was an independent determinant of NAP in a model including age, sex, glycated hemoglobin, systolic and mean blood pressure (R2 =0.17, p = 0.031).

CONCLUSION

iNAP subjects showed increased arterial stiffness comparable to that observed in ALB+ group, suggesting that they may represent a subgroup at higher cardiovascular risk, often unrecognized in clinical practice.

Prognostic models of diabetic microvascular complications: a systematic review and meta-analysis

BACKGROUND

Many prognostic models of diabetic microvascular complications have been developed, but their performances still varies. Therefore, we conducted a systematic review and meta-analysis to summarise the performances of the existing models.

METHODS

Prognostic models of diabetic microvascular complications were retrieved from PubMed and Scopus up to 31 December 2020. Studies were selected, if they developed or internally/externally validated models of any microvascular complication in type 2 diabetes (T2D).

RESULTS

In total, 71 studies were eligible, of which 32, 30 and 18 studies initially developed prognostic model for diabetic retinopathy (DR), chronic kidney disease (CKD) and end stage renal disease (ESRD) with the number of derived equations of 84, 96 and 51, respectively. Most models were derived-phases, some were internal and external validations. Common predictors were age, sex, HbA1c, diabetic duration, SBP and BMI. Traditional statistical models (i.e. Cox and logit regression) were mostly applied, otherwise machine learning. In cohorts, the discriminative performance in derived-logit was pooled with C statistics of 0.82 (0.73‑0.92) for DR and 0.78 (0.74‑0.83) for CKD. Pooled Cox regression yielded 0.75 (0.74‑0.77), 0.78 (0.74‑0.82) and 0.87 (0.84‑0.89) for DR, CKD and ESRD, respectively. External validation performances were sufficiently pooled with 0.81 (0.78‑0.83), 0.75 (0.67‑0.84) and 0.87 (0.85‑0.88) for DR, CKD and ESRD, respectively.

CONCLUSIONS

Several prognostic models were developed, but less were externally validated. A few studies derived the models by using appropriate methods and were satisfactory reported. More external validations and impact analyses are required before applying these models in clinical practice.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42018105287.

Proteinuria as a significant predictive factor for the progression of carotid artery atherosclerosis in non-albuminuric type 2 diabetes

AIMS

This study aimed to evaluate the clinical significance of urine protein to creatinine ratio (uPCR) in relation to the cardiovascular risk associated with carotid artery intima-media thickness (cIMT) progression in subjects with type 2 diabetes (T2D) and normoalbuminuria.

METHODS

In this retrospective longitudinal study on T2D, we recruited 927 participants with normoalbuminuria (urine albumin to creatinine ratio [uACR] < 30 mg/g) whose cIMT was measured at baseline and after at least 1 year, and whose initial uPCR and uACR data were available.

RESULTS

Higher initial uPCR was positively correlated with a greater increment in maximal cIMT (β = 0.074, p = 0.028), and this correlation was significant even after adjusting for multiple confounding factors (β = 0.074, p = 0.046). High baseline uPCR was an independent predictive factor for the increased risk of maximal cIMT progression in a simple logistic regression model (OR, 1.41; 95% CI, [1.08-1.86]; p = 0.013). Even after adjusting for several confounding variables, higher uPCR was significantly associated with a higher risk of cIMT progression (OR, 1.48; 95% CI, [1.08-2.03]; p = 0.014).

CONCLUSIONS

These results suggest that high uPCR may be a useful predictive marker for the progression of carotid artery atherosclerosis, even in subjects with T2D and without albuminuria.

Efficacy of combined angiotensin II receptor blocker with tripterygium glycosides on diabetic nephropathy: A protocol for meta-analysis

BACKGROUND

Several studies have reported good results for angiotensin II receptor blockers (ARB) combined with tripterygium glycosides (TGs) in the treatment of diabetic nephropathy (DN). However, because a small number of cases were included in each study, the statistical power was limited. Therefore, we performed a protocol for meta-analysis to further evaluate the clinical efficacy and safety of combined ARB and TGs in treatment of DN.

METHODS

The protocol was written following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement guidelines. We searched PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, Science Direct up to April 2021. Outcome measures were 24-h urinary total protein, urinary albumin excretion rate, serum creatinine, blood urea nitrogen, albumin, hemoglobin A1c, β2-microglobulin and serum glutamic pyruvic transaminase. The risk of bias assessment of the included studies was performed by two authors independently using the tool recommended in the Cochrane Handbook for Systematic Reviews of Interventions (version 5.1.0). We performed meta-analysis using STATA 11.0.

RESULTS

The review will add to the existing literature by showing compelling evidence and improved guidance in clinic settings.

CONCLUSION

The findings will provide helpful evidence for the application of combined ARB and TGs in the treatment of DN.

OSF REGISTRATION NUMBER

10.17605/OSF.IO/ARGE3.

Non-Albumin Proteinuria (NAP) as a Complementary Marker for Diabetic Kidney Disease (DKD)

Diabetic kidney disease (DKD) is one of the most common forms of chronic kidney disease. Its pathogenic mechanism is complex, and it can affect entire structures of the kidney. However, conventional approaches to early stage DKD have focused on changes to the glomerulus. Current standard screening tools for DKD, albuminuria, and estimated glomerular filtration rate are insufficient to reflect early tubular injury. Therefore, many tubular biomarkers have been suggested. Non-albumin proteinuria (NAP) contains a wide range of tubular biomarkers and is convenient to measure. We reviewed the clinical meanings of NAP and its significance as a marker for early stage DKD.

Association of urinary non-albumin protein with the different urinary marker for glomerular and tubular damage in patients with type 2 diabetes

BACKGROUND/AIM

In recent years, the diagnostic utility of urinary protein levels has been demonstrated for the early detection and progression of kidney disease. This study aimed to evaluate the associations of the non-albumin protein (NAP) with different urinary marker for tubular and glomerular damage in patients with type 2 diabetes (T2D).

METHODS

In this observational cross-sectional study, 424 patients with T2D duration > 10 years were classified into two groups according to estimated glomerular filtration rate (eGFR). The ratios of different urinary markers (albumin, NAP, total protein, transferrin, retinol-binding protein (RBP), and neutrophil gelatinase-associated lipocalin (NGAL) to creatinine were analyzed.

RESULTS

The levels of urinary biomarkers increased significantly with decrease in eGFR levels. In the group with moderately decreased eGFR, the albumin to-creatinine ratio (ACR), non-albumin protein-to-creatinine ratio (NAPCR), and total protein-to-creatinine ratio (PCR) were independently associated with all urinary markers after being adjusted for risk factors. The area under the receiver operating characteristics (ROC) curve for ACR and PCR had a better diagnostic value than other urinary biomarkers. Comparing ROC curve of NAPCR with other urinary biomarkers, it was significantly better than NGAL/Cr (p = 0.033).

CONCLUSIONS

The findings of the present study confirm that ACR and PCR are diagnostic biomarkers in T2D patients with decreased eGFR. NAPCR in these patients diagnostically only outperformed NGAL/Cr.

Association between nonalbumin proteinuria and renal tubular damage of N-acetyl-β-d-glucosaminidase and its clinical relevance in patients with type 2 diabetes without albuminuria

AIM

Although albuminuria and urinary N-acetyl-β-d-glucosaminidase (uNAG) are known as progression markers of diabetic kidney disease, there is limited information regarding the association between urinary nonalbumin proteinuria (NAP) and uNAG and the clinical relevance thereof in patients without albuminuria.

METHODS

This cross-sectional study included samples from 244 consecutive patients with type 2 diabetes mellitus (T2D) without albuminuria. Proteinuria and albuminuria were defined according to protein-to-creatinine ratio (uPCR) and albumin-to-creatinine ratio (uACR), respectively. NAP was indirectly calculated by the difference between uPCR and uACR.

RESULTS

NAP and uNAG excretion were significantly correlated (r = 0.525, P < 0.001). Individuals whose NAP levels were in the highest tertile had a longer duration of diabetes, uncontrolled hyperglycemia, and impaired insulin stimulation (all P < 0.05), although more patients in the highest NAP tertile were prescribed insulin and sulfonylurea. Multiple linear regression analyses revealed associations among uNAG, diabetes duration, and waist circumference.

CONCLUSIONS

T2D patients without albuminuria excrete proteinuria and that presence of the protein in urine is associated with uNAG. NAP was positively correlated with T2D duration and waist circumference, but negatively correlated with body mass index. Lean, but centrally obese, T2D patients in late diabetes experience more tubular damage, regardless of the presence of albuminuria.