Association between the Triglyceride Glucose Index and All-Cause Mortality in Critically Ill Patients with Acute Kidney Injury.

Introduction: The triglyceride glucose (TyG) index is a reliable alternative biomarker of insulin resistance, but the association between the TyG index and acute kidney injury (AKI) in critically ill patients remains unclear. Methods: The data for the study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Cox regression and restricted cubic spline (RCS) analysis were performed to analyze the association between the TyG index and all-cause mortality. Besides, Cox regression was carried out in subgroups of age, gender, BMI, diabetes history, and dialysis status. Results: A total of 7,508 critically ill participants with AKI from the MIMIC-IV database were included in this study, with 3,688 (49.12%) participants failed to survive. In Cox regression, after confounder adjustment, patients with a higher TyG index had a higher risk of all-cause mortality (HR = 1.845, 95% CI = 1.49-2.285, p < 0.001). In RCS, after confounder adjustment, the risk of death was positively correlated with the increased value of the TyG index when TyG index surpassed 10.014. This relationship was validated in age, gender, BMI, diabetes subgroups but not in the dialysis subgroup. Interestingly, RCS analysis demonstrated that, in patients undertaking dialysis, there is a "U"-shaped curve for the value of TyG index and risk of all-cause mortality. When TyG index is less than 10.460, the risk of all-cause mortality would decrease with the increased value of TyG index, while when TyG index is higher than 11.180, the risk of all-cause mortality would increase firmly with the increased value of TyG index. Conclusion: Overall, a higher TyG index is associated with a higher risk of all-cause mortality in critically ill AKI. Interestingly, the relationship in the dialysis subgroup follows a "U"-shaped curve, indicating the importance of proper clinical blood glucose and lipid management in this particular population.

Secondhand smoke, genetic susceptibility, and incident chronic kidney disease in never smokers: A prospective study of a selected population from the UK Biobank.

INTRODUCTION: A large number of people around the world are exposed to the risks of passive smoking. This prospective study aimed to examine the association between secondhand smoke exposure, exposure time, and the incidence of chronic kidney disease (CKD) and determine whether this association was influenced by genetic susceptibility. METHODS: The study included 214244 participants of the UK Biobank who were initially free of CKD. Cox proportional hazards model was used to estimate the associations between secondhand smoke exposure time and the risks of CKD in people who have never smoked. The genetic risk score for CKD was calculated by a weighted method. The likelihood ratio test comparing models was used to examine the cross-product term between secondhand smoke exposure and genetic susceptibility to CKD outcomes. RESULTS: During a median of 11.9 years of follow-up, 6583 incidents of CKD were documented. Secondhand smoke exposure increased the risk of CKD (HR=1.09; 95% CI: 1.03-1.16, p<0.01), and a dose-response relationship between CKD prevalence and secondhand smoke exposure time was found (p for trend<0.01). Secondhand smoke exposure increases the risk of CKD even in people who never smoke and have a low genetic risk (HR=1.13; 95% CI: 1.02-1.26, p=0.02). There was no statistically significant interaction between secondhand smoke exposure and genetic susceptibility to CKD (p for interaction=0.80). CONCLUSIONS: Secondhand smoke exposure is associated with higher risk of CKD, even in people with low genetic risk, and the relationship is dose dependent. These findings change the belief that people with low genetic susceptibility and without direct participation in smoking activities are not prone to CKD, emphasizing the need to avoid the harm of secondhand smoke in public places.

Serum metabolite differences detected by HILIC UHPLC-Q-TOF MS in systemic sclerosis.

BACKGROUND: Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by extensive fibrosis and vascular damage. Vasculopathy, activation of the immune system, and diffuse fibrosis are all involved in the fatal pathogenesis of SSc. However, little metabolomic research has been conducted in SSc. METHODS: This study included 30 SSc patients and 30 healthy individuals. The metabolite differences in serum samples were analyzed using ultra-high-pressure liquid chromatography and quadrupole-time-of-flight mass spectrometry. Meanwhile, serum metabolites were analyzed in patients with systemic involvement (lung or skin fibrosis). RESULTS: A total of 2360 ion peaks were detected, all of which were attributable to 38 metabolites. These metabolites primarily consisted of fatty acids, amino acids, and glycerophospholipids, which were the major metabolic pathways altered in SSc patients. Glutamine metabolism was the main pathway altered in SSc patients with lung involvement, whereas amino acid metabolism and steroid hormone biosynthesis were the main pathways altered in SSc patients with skin involvement. CONCLUSION: These findings suggested that metabolic profiles and pathways differed between SSc patients and healthy people, potentially providing new targets for SSc-directed therapeutics and diagnostics. Key Points • Metabolic profiles and pathways differed between SSc patients and healthy people. • The levels of trans-dehydroandrosterone are substantially lower in lcSSc than in dcSSc, potentially providing new targets for SSc patients with skin involvement. • L-glutamine could be used as a serum metabolic marker and a therapeutic target for SSc patients with lung involvement.

Effect of Glomerular Filtration Rate by Different Equations on Prediction Models for End-Stage Renal Disease in Diabetes.

Background and Objectives: The study aimed to evaluate the performance of a predictive model using the kidney failure risk equation (KFRE) for end-stage renal disease (ESRD) in diabetes and to investigate the impact of glomerular filtration rate (GFR) as estimated by different equations on the performance of the KFRE model in diabetes. Design Setting Participants and Measurements: A total of 18,928 individuals with diabetes without ESRD history from the UK Biobank, a prospective cohort study initiated in 2006-2010, were included in this study. Modification of diet in renal disease (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI) or revised Lund-Malmö (r-LM) were used to estimate GFR in the KFRE model. Cox proportional risk regression was used to determine the correlation coefficients between each variable and ESRD risk in each model. Harrell's C-index and net reclassification improvement (NRI) index were used to evaluate the differentiation of the models. Analysis was repeated in subgroups based on albuminuria and hemoglobin A1C (HbA1c) levels. Results: Overall, 132 of the 18,928 patients developed ESRD after a median follow-up of 12 years. The Harrell's C-index based on GFR estimated by CKD-EPI, MDRD, and r-LM was 0.914 (95% CI = 0.8812-0.9459), 0.908 (95% CI = 0.8727-0.9423), and 0.917 (95% CI = 0.8837-0.9496), respectively. Subgroup analysis revealed that in diabetic patients with macroalbuminuria, the KFRE model based on GFR estimated by r-LM (KFRE-eGFRr-LM) had better differentiation compared to the KFRE model based on GFR estimated by CKD-EPI (KFRE-eGFRCKD-EPI) with a KFRE-eGFRr-LM C-index of 0.846 (95% CI = 0.797-0.894, p = 0.025), while the KFRE model based on GFR estimated by MDRD (KFRE-eGFRMDRD) showed no significant difference compared to the KFRE-eGFRCKD-EPI (KFRE-eGFRMDRD C-index of 0.837, 95% CI = 0.785-0.889, p = 0.765). Subgroup analysis of poor glycemic control (HbA1c >8.5%) demonstrated the same trend. Compared to KFRE-eGFRCKD-EPI (C-index = 0.925, 95% CI = 0.874-0.976), KFRE-eGFRr-LM had a C-index of 0.935 (95% CI = 0.888-0.982, p = 0.071), and KFRE-eGFRMDRD had a C-index of 0.925 (95% CI = 0.874-0.976, p = 0.498). Conclusions: In adults with diabetes, the r-LM equation performs better than the CKD-EPI and MDRD equations in the KFRE model for predicting ESRD, especially for those with macroalbuminuria and poor glycemic control (HbA1c >8.5%).

Relationship Between the TyG Index and Diabetic Kidney Disease in Patients with Type-2 Diabetes Mellitus.

BACKGROUND: Diabetic kidney disease (DKD) lacks a simple and relatively accurate predictor. The Triglyceride-Glucose (TyG) Index is a proxy of insulin resistance, but the association between the TyG Index and DKD is less certain. We investigated if the TyG Index can predict DKD onset effectively. MATERIALS AND METHODS: Cross-sectional and longitudinal analyses were undertaken. In total, 1432 type-2 diabetes mellitus (T2DM) patients were included in the cross-sectional analysis. The TyG Index (calculated by ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]) was split into three tertiles. Associations of the TyG Index with microalbuminuria and estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 were calculated. Longitudinally, 424 patients without DKD at baseline were followed up for 21 (range, 12-24) months. The main outcome was DKD prevalence as defined with eGFR <60 mL/min/1.73 m2 or continuously increased urinary microalbuminuria: creatinine ratio (>30 mg/mL) over 3 months. Cox regression was used to analyze the association between the TyG Index at baseline and DKD. Receiver operating characteristics curve (ROC) analysis was used to assess the sensitivity and specificity of the TyG Index in predicting DKD. RESULTS: In cross-sectional analysis, patients with a higher TyG Index had a higher risk of microalbuminuria (OR = 2.342, 95% CI = 1.744-3.144, p < 0.001), and eGFR <60 mL/min/1.73 m2 (1.696, 95% CI =1.096-2.625, p = 0.018). Longitudinally, 94 of 424 participants developed DKD. After confounder adjustment, patients in the high tertile of the TyG Index at baseline had a greater risk to developing DKD than those in the low tertile (HR = 1.727, 95% CI = 1.042-2.863, p = 0.034). The area under the ROC curve was 0.69 (0.63-0.76). CONCLUSION: The TyG Index is a potential predictor for DKD in T2DM patients. CLINICAL TRIAL: Clinical Trials identification number = NCT03692884.

Epidemiology of Takayasu arteritis in Shanghai: A hospital-based study and systematic review.

BACKGROUND: Takayasu arteritis (TAK) is a rare large vessel vasculitis, and epidemiological data on TAK are lacking in China. Thus, we designed this study to estimate the TAK prevalence and incidence in residential Shanghai, China. METHODS: Data on diagnosed TAK cases aged over 16 years were retrieved from 22 tertiary hospitals in Shanghai through hospital electronic medical record systems between January 1, 2015 and December 31, 2017 to estimate the prevalence and incidence. A systematic literature review based on searches in PubMed, Ovid-Medline, Excerpta Medica Database (EMBASE), Web of Science, and China National Knowledge Infrastructure (CNKI) was performed to summarize TAK distribution across the world. RESULTS: In total 102 TAK patients, with 64% female, were identified. The point prevalence (2015-2017) was 7.01 (95% CI 5.65-8.37) cases per million, and the mean annual incidence was 2.33 (1.97-3.21) cases per million. The average age of TAK patients was 44 ± 16 years, with the highest prevalence (11.59 [9.23-19.50] cases per million) and incidence (3.55 [0.72 3.74] cases per million) in the 16 to 34 years population. Seventeen reports were included in the system review, showing that the epidemiology of TAK varied greatly across the world. The incidence and prevalence were both relatively higher in Asian countries, with the prevalence ranging 3.3-40 cases per million and annual incidence ranging 0.34-2.4 cases per million. CONCLUSIONS: The prevalence and incidence of TAK in Shanghai was at moderate to high levels among the previous reports. The disease burden varied globally among racial populations.