IntroductionDespite advances in diabetic retinopathy (DR) medications, early identification is vitally important for DR administration and remains a major challenge. This study aims to develop a novel system of multidimensional network biomarkers (MDNBs) based on a widely targeted metabolomics approach to detect DR among patients with type 2 diabetes mellitus (T2DM) efficiently.Research design and methodsIn this propensity score matching-based case-control study, we used ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry system for serum metabolites assessment of 69 pairs of patients with T2DM with DR (cases) and without DR (controls). Comprehensive analysis, including principal component analysis, orthogonal partial least squares discriminant analysis, generalized linear regression models and a 1000-times permutation test on metabolomics characteristics were conducted to detect candidate MDNBs depending on the discovery set. Receiver operating characteristic analysis was applied for the validation of capability and feasibility of MDNBs based on a separate validation set.ResultsWe detected 613 features (318 in positive and 295 in negative ESI modes) in which 63 metabolites were highly relevant to the presence of DR. A panel of MDNBs containing linoleic acid, nicotinuric acid, ornithine and phenylacetylglutamine was determined based on the discovery set. Depending on the separate validation set, the area under the curve (95% CI), sensitivity and specificity of this MDNBs system were 0.92 (0.84 to 1.0), 96% and 78%, respectively.ConclusionsThis study demonstrates that metabolomics-based MDNBs are associated with the presence of DR and capable of distinguishing DR from T2DM efficiently. Our data also provide new insights into the mechanisms of DR and the potential value for new treatment targets development. Additional studies are needed to confirm our findings.

BackgroundAccurate forecast of the death risk is crucial to the administration of people living with HIV/AIDS (PLHIV). We aimed to establish and validate an effective prognosis nomogram in PLHIV receiving antiretroviral therapy (ART).MethodsAll the data were obtained from 2006 to 2018 in the Wenzhou area from China AIDS prevention and control information system. Factors included in the nomogram were determined by univariate and multiple Cox proportional hazard analysis based on the training set. The receiver operating characteristic (ROC) and calibration curves were used to assess its predictive accuracy and discriminative ability. Its clinical utility was also evaluated using decision curve analysis (DCA), X-tile analysis and Kaplan-Meier curve, respectively in an independent validation set.FindingsIndependent prognostic factors including haemoglobin, viral load and CD4+ T-cell count were determined and contained in the nomogram. Good agreement between the prediction by nomogram and actual observation could be detected in the calibration curve for mortality, especially in the first year. In the training cohort, AUC (95% CI) and C-index (95% CI) were 0.93 (0.90, 0.96) and 0.90 (0.85, 0.96), respectively. In the validation set, the nomogram still revealed excellent discriminations [AUC (95% CI): 0.95 (0.91, 1.00)] and good calibration [C-index (95% CI): 0.92 (0.82–1.00)]. Moreover, DCA also demonstrated that the nomogram was clinical beneficial. Additionally, participants could be classified into three distinct (low, middle and high) risk groups by the nomogram.InterpretationThe nomogram presents accurate and favourable prognostic prediction for PLHIV who underwent ART.FundingThis work was supported by (LGF19H260011), (Y20180201), the (KYQD170301), the Major Project of the Eye Hospital Wenzhou the Major Project of the (YNZD201602). Part of this work was also funded by (81670777) and and (2019R413073). The funders had no roles in study design, data collection, data analysis, interpretation and writing of the report.

Background: The aim of this study is to evaluate the performance of three existing prediction scores which are applicable to adults for identifying nonalcoholic fatty liver disease (NAFLD) in Chinese children. Methods: We used data from routine check-up based medical records of 1845 children to validate the performance of three existing scoring systems including the hepatic steatosis index (HSI), Zhejiang University index (ZJU index), and triglyceride-glucose index (TyG index) in detection of NAFLD in children.Propensity score matching was applied to adjust for potential confounding effects in both training and validation cohorts. The area under the curve (AUC) of the receiver operating characteristic curve analysis was utilized to assess the performance of the three scoring systems.Results: Children with NAFLD had higher scores of HSI, ZJU index, and TyG index when compared with the control group (children without NAFLD). Elevated HSI, ZJU index, and TyG index scores were significantly associated with the presence of pediatric NAFLD since adjusted odds ratio and 95% CI with per interquartile range elevation of the HSI, ZJU index, and TyG index were

Rapid aging in China is increasing the number of older people who tend to require health services for their poor perceived health. Drawing on the China Health and Retirement Longitudinal Study (CHARLS) 2018 data, we used two-part model and binary logistic regression to compare various types of health insurance in the healthcare utilization, costs and catastrophic health expenditures (CHE) among the middle-aged and older adults in China. Compared with uninsured, all types of health insurance promoted hospital utilization rate (ranged from 8.6% to 12.2%) and reduced out-of-pocket (OOP) costs (ranged from 64.9% to 123.6%), but had no significant association with total costs. In contrast, the association of health insurance and outpatient care was less significant. When Urban Employee Medical Insurance (UEMI) as reference, other types of insurance did not show a significant difference. Health insurance could not reduce the risk of CHE. The equity in healthcare utilization improved and healthcare costs had been effectively controlled among the elderly, but health insurance did not protect against CHE risks. Policy efforts should further focus on optimizing healthcare resource allocation and inclining toward the lower socio-economic and poor-health groups.

Diabetic retinopathy (DR), the most common microvascular complication of diabetes and leading cause of visual impairment in adults worldwide, is suggested to be linked to abnormal lipid metabolism. The present study aims to comprehensively investigate the relationship between n-6 polyunsaturated fatty acids (PUFAs) and DR. This was a propensity score matching based case-control study, including 69 pairs of DR patients and type 2 diabetic patients without DR with mean age of 56.7 ± 9.2 years. Five n-6 PUFAs were determined by UPLC-ESI-MS / MS system. Principle component regression (PCR) and multiple conditional logistic regression models were used to investigate the association of DR risk with n-6 PUFAs depending on independent training and testing sets, respectively. According to locally weighted regression model, we observed obvious negative correlation between levels of five n-6 PUFAs (linoleic acid, γ-linolenic acid, eicosadienoic acid, dihomo-γ-linolenic acid and arachidonic acid) and DR. Based on multiple PCR model, we also observed significant negative association between the five n-6 PUFAs and DR with adjusted OR (95% CI) as 0.62 (0.43,0.87). When being evaluated depending on the testing set, the association was still existed, and PCR model had excellent classification performance, in which area under the curve (AUC) was 0.88 (95%CI: 0.78, 0.99). In addition, the model also had valid calibration with a non-significant Hosmer-Lemeshow Chi-square of 9.44 (P = 0.307) in the testing set. n-6 PUFAs were inversely associated with the presence of DR, and the principle component could be potential indicator in distinguishing DR from other T2D patients.