Objective: To investigate the association between computed tomography-measured quality characteristics of skeletal muscle (SM) and early diagnosis of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM).
Methods: This retrospective study included patients diagnosed with T2DM, with and without early DKD, between January 2019 and December 2021. To reduce potential bias, propensity score matching (PSM) was performed. The area and computed tomography attenuation values for SM and different abdominal adipose depots were measured. After PSM, logistic and multiple linear regression analyze were performed to analyse risk factors for early DKD.
Results: A total of 267 patients were enrolled (mean age, 61.67 years ± 10.87; 155 men) and divided into two groups: T2DM with early DKD (n = 133); and T2DM without DKD (n = 134). After PSM, 230 patients were matched (T2DM with early DKD [n = 115]; and T2DM without DKD [n = 115]), with no statistical differences in general characteristics between the two groups (P > .05). In multivariate logistic regression analysis, high-density lipoprotein cholesterol (odds ratio [OR] 0.14; 95% confidence interval [CI] 0.04-0.49; P = .002), uric acid (OR 1.01; 95% CI 1.00-1.01; P = .006), and SM attenuation value (OR 0.94; 95% CI 0.90-0.98; P = .003) were independent risk factors for early DKD. Multiple linear regression analysis revealed significant correlations between SM attenuation value and cystatin C (β = -0.39, P = .004), urine albumin-to-creatinine ratio (β = -0.26, P = .026), and estimated glomerular filtration rate (β = 0.31 P = .009) after adjustment for confounders.
Conclusion: Patients with T2DM and lower SM attenuation values may exhibit a higher risk for early DKD than those with higher values, which provides a potential imaging biomarker for early DKD diagnosis.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1053/j.jrn.2024.04.002 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Diabetic kidney disease (DKD) progression is often marked by early glomerular endothelial cell (GEC) dysfunction, including alterations in the fenestration size and number linked to impaired glomerular filtration. However, the cellular mechanisms regulating GEC fenestrations remain poorly understood due to limitations in existing models, challenges in imaging small fenestrations , and inconsistencies between and findings. This study used a logic-based protein-protein interaction network model with normalized Hill functions for dynamics to explore how glucose-mediated signaling dysregulation impacts fenestration dynamics in GECs.
View Article and Find Full Text PDFUnraveling diabetic kidney disease: insights from single-cell RNA sequencing.
Int Urol Nephrol
January 2025
Department of Nephrology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
The incidence of diabetic kidney disease (DKD) is rising annually. Diabetes leads to structural damage and dysfunction in the kidneys, clinically manifesting as progressive proteinuria and declining renal function, ultimately resulting in end-stage renal disease (ESRD). Recent findings have identified a subset of DKD known as normoalbuminuric diabetic kidney disease (NADKD), characterized by normal urine albumin levels but reduced renal function.
View Article and Find Full Text PDFA nomograph model for predicting the risk of diabetes nephropathy.
Int Urol Nephrol
January 2025
Medical College, Qinghai University, Xining, 810016, People's Republic of China.
Objective: Using machine learning to construct a prediction model for the risk of diabetes kidney disease (DKD) in the American diabetes population and evaluate its effect.
Methods: First, a dataset of five cycles from 2009 to 2018 was obtained from the National Health and Nutrition Examination Survey (NHANES) database, weighted and then standardized (with the study population in the United States), and the data were processed and randomly grouped using R software. Next, variable selection for DKD patients was conducted using Lasso regression, two-way stepwise iterative regression, and random forest methods.
Modified Hu-Lu-Ba-Wan Alleviates Early-Stage Diabetic Kidney Disease via Inhibiting Interleukin-17A in Mice.
Chin J Integr Med
January 2025
Institute of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Objective: To identify the underlying molecular mechanism of Modified Hu-Lu-Ba-Wan (MHW) in alleviating renal lesions in mice with diabetic kidney disease (DKD).
Methods: The db/db mice were divided into model group and MHW group according to a random number table, while db/m mice were settled as the control group (n=8 per group). The control and model groups were gavaged daily with distilled water [10 mL/(kg·d)], and the MHW group was treated with MHW [17.
Could MOTS-C Levels in Children with Type 1 Diabetes Mellitus Be an İndicator for Early Diabetic Kidney Disease?
J Clin Res Pediatr Endocrinol
December 2024
Department of Pediatric Nephrology and Rheumatology, University of Canakkale Onsekiz Mart, Çanakkale, Turkey.
Objective: The aim of our study was to compare serum MOTS-c levels in children with Type 1 diabetes mellitus (T1DM) to those of healthy children. We also aimed to examine whether serum MOTS-c levels could be used as an early indicator of DKD by correlating with changes in GFR and microalbuminuria.
Methods: We recruited 82 patients who were being treated for insulin-dependent diabetes at the outpatient pediatric endocrinology clinic.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!