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Abstract Background Nonalcoholic fatty liver disease (NAFLD) and liver cirrhosis are significant clinical concerns, especially among individuals with type 2 diabetes mellitus (T2DM). However, in China, there is a paucity of reliable evidence detailing the characteristics of NAFLD and liver cirrhosis in T2DM. Furthermore, the relationship between blood glucose levels and NAFLD prevalence remains unclear. Methods Data from the Shanghai Suburban Adult Cohort and Biobank were analyzed, including 6621 participants with T2DM. NAFLD was diagnosed by ultrasonography and liver cirrhosis was performed according to the health information systems. Logistic regression and restricted cubic spline analysis were used to explore the potential risk factors for NAFLD and liver cirrhosis. Results The prevalence of NAFLD was 59.36%, and liver cirrhosis was 1.43% among T2DM patients. In these patients, factors like age, being female, marital status, and obesity significantly increased the risk of NAFLD. Specifically, obesity had a strong positive association with NAFLD (odds ratio [OR] = 4.70, 95% confidence interval [CI]: 4.13–5.34). The higher glycated hemoglobin (HbA1c) quartile was associated with a heightened NAFLD risk compared to the lowest quartile (all p 8.00% (OR = 1.03, 95% CI: 0.92–1.15). Conclusion Systematic screening for NAFLD is essential in T2DM patients, especially with poor glucose control and obesity in female.

Abstract Objective Early identification of diabetic retinopathy (DR) is key to prioritizing therapy and preventing permanent blindness. This study aims to propose a machine learning model for DR early diagnosis using metabolomics and clinical indicators. Methods From 2017 to 2018, 950 participants were enrolled from two affiliated hospitals of Wenzhou Medical University and Anhui Medical University. A total of 69 matched blocks including healthy volunteers, type 2 diabetes, and DR patients were obtained from a propensity score matching-based metabolomics study. UPLC-ESI-MS/MS system was utilized for serum metabolic fingerprint data. CART decision trees (DT) were used to identify the potential biomarkers. Finally, the nomogram model was developed using the multivariable conditional logistic regression models. The calibration curve, Hosmer–Lemeshow test, receiver operating characteristic curve, and decision curve analysis were applied to evaluate the performance of this predictive model. Results The mean age of enrolled subjects was 56.7 years with a standard deviation of 9.2, and 61.4% were males. Based on the DT model, 2-pyrrolidone completely separated healthy controls from diabetic patients, and thiamine triphosphate (ThTP) might be a principal metabolite for DR detection. The developed nomogram model (including diabetes duration, systolic blood pressure and ThTP) shows an excellent quality of classification, with AUCs (95% CI) of 0.99 (0.97–1.00) and 0.99 (0.95–1.00) in training and testing sets, respectively. Furthermore, the predictive model also has a reasonable degree of calibration. Conclusions The nomogram presents an accurate and favorable prediction for DR detection. Further research with larger study populations is needed to confirm our findings.

Although previous studies demonstrate that trehalose can help maintain glucose homeostasis in healthy humans, its role and joint effect with gl utamate on diabetic retinopathy (DR) remain unclear. We aimed to comprehensively quantify the associations of trehalose and glutamate with DR. This study included 69 pair s of DR and matched type 2 diabetic (T2D) patients. Serum trehalose and glutamate were d etermined via ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry system. Covariates were collected by a standardized questionnai re, clinical examinations and laboratory assessments. Individual and joint association of trehalose and glutamate with DR were quantified by multiple conditional logistic regress ion models. The adjusted odds of DR averagely decreased by 86% (odds ratio (OR): 0.14; 9 5% CI: 0.06, 0.33) with per interquartile range increase of trehalose. Comparing with the l owest quartile, adjusted OR (95% CI) were 0.20 (0.05, 0.83), 0.14 (0.03, 0.63) and 0.01 (

Background: The sixty-day effects of initial composite interventions for the treatment of severely and critically ill patients with COVID-19 are not fully assessed. Methods: Using a Bayesian piecewise exponential model, we analyzed the 60-day mortality, health-related quality of life (HRQoL), and disability in 1082 severely and critically ill patients with COVID-19 between 8 December 2022 and 9 February 2023 in Shanghai, China. The final 60-day follow-up was completed on 10 April 2023. Results: Among 1082 patients (mean age, 78.0 years, 421 [38.9%] women), 139 patients (12.9%) died within 60 days. Azvudine had a 99.8% probability of improving 2-month survival (adjusted HR, 0.44 [95% credible interval, 0.24–0.79]), and Paxlovid had a 91.9% probability of improving 2-month survival (adjusted HR, 0.71 [95% credible interval, 0.44–1.14]) compared with the control. IL-6 receptor antagonist, baricitinib and a-thymosin each had a high probability of benefit (99.5%, 99.4%, and 97.5%, respectively) compared to their controls, while the probability of trail-defined statistical futility (HR > 0.83) was high for therapeutic anticoagulation (99.8%; HR, 1.64 [95% CrI, 1.06–2.50]) and glucocorticoid (91.4%; HR, 1.20 [95% CrI, 0.71–2.16]). Paxlovid, Azvudine, and therapeutic anticoagulation showed a significant reduction in disability (p < 0.05) Conclusions: Among severely and critically ill patients with COVID-19 who received 1 or more therapeutic interventions, treatment with Azvudine had a high probability of improved 60-day mortality compared with the control, indicating its potential in a resource-limited scenario. Treatment with an IL-6 receptor antagonist, baricitinib, and a-thymosin also had high probabilities of benefit in improving 2-month survival, among which a-thymosin could improve HRQoL. Treatment with Paxlovid, Azvudine, and therapeutic anticoagulation could significantly reduce disability at day 60.

Abstract Background Recent studies indicate that ultrasound can detect changes in tracheal diameter during endotracheal tube (ETT) cuff inflation. We sought to assess the accuracy of ultrasound measurement of tracheal diameter, and to determine the relationship between tracheal wall pressure (TWP), cuff inflation volume (CIV), and the degree of tracheal deformation. Methods Our study comprised two parts: the first included 45 porcine tracheas, the second 41 porcine tracheas. Each trachea was intubated with a cuffed ETT, which was connected to an injector and the manometer via a three-way tap. The cuff was inflated and the cuff pressure recorded before and after intubation. The tracheal diameter was measured using ultrasound. This included three separate measurements: outer transverse diameter (OTD), internal transverse diameter (ITD), and anterior tracheal wall thicknesses (ATWT). A precision electronic Vernier caliper was also used to measure tracheal diameter. We calculated TWP and the percentage change of tracheal diameter. The Bland–Altman method, linear regression, and locally weighted regression (LOESS) were used to analyze the data. Results There were strong correlation and agreement for OTD (r = 0.97, P

Background: Diabetic retinopathy (DR) is a major diabetes-related disease linked to metabolism. However, the cognition of metabolic pathway alterations in DR remains scarce. We aimed to corroborate alterations of metabolic pathways identified in prior studies and investigate novel metabolic dysregulations that may lead to new prevention and treatment strategies for DR.Methods: In this case-control study, we tested 613 serum metabolites in 69 pairs of type 2 diabetic patients (T2DM) with DR and propensity score-matched T2DM without DR via ultra-performance liquid chromatography-tandem mass spectrometry system. Metabolic pathway dysregulation in DR was thoroughly investigated by metabolic pathway analysis, chemical similarity enrichment analysis (ChemRICH), and integrated pathway analysis. The associations of ChemRICH-screened key metabolites with DR were further estimated with restricted cubic spline analyses.Results: A total of 89 differentially expressed metabolites were identified by paired univariate analysis and partial least squares discriminant analysis. We corroborated biosynthesis of unsaturated fatty acids, glycine, serine and threonine metabolism, glutamate and cysteine-related pathways, and nucleotide-related pathways were significantly perturbed in DR, which were identified in prior studies. We also found some novel metabolic alterations associated with DR, including the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives in DR.Conclusions: The results suggest that the metabolism disorder in DR can be better understood through integrating multiple biological knowledge databases. The progression of DR is associated with the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives.

Background: Optimal ω-6/ω-3 polyunsaturated fatty acids ratio (PUFAR) is reported to exert protective effects against chronic diseases. However, data on PUFAR and diabetic retinopathy (DR) remains scarce. We aimed to thoroughly quantify whether and how PUFAR was related to DR as well as its role in DR detection. Methods: This two-centre case-control study was conducted from August 2017 to June 2018 in China, participants were matched using a propensity score matching algorithm. We adopted multivariable logistic regression models and restricted cubic spline analyses to estimate the independent association of PUFAR with DR, adjusting for confounders identified using a directed acyclic graph. The value of PUFAR as a biomarker for DR identification was further evaluated by receiver operating characteristic analyses and Hosmer-Lemeshow tests. Findings: An apparent negative relationship between PUFAR and DR was observed. Adjusted odds of DR decreased by 79% (OR: 0·21, 95% CI: 0·10–0·40) with an interquartile range increase in PUFAR. Similar results were also obtained in tertile analysis. As compared to those in the 1st tertile of PUFAR, the adjusted odds of DR decreased by 76% (OR: 0·24, 95% CI: 0·08–0·66) and 93% (OR: 0·07, 95% CI: 0·03–0·22) for subjects in the 2nd and 3rd tertiles, respectively. Good calibration and discrimination of the PUFAR associated predictive model were detected and PUFAR = 35 would be an ideal cut-off value for DR identification. Interpretation: Our results suggest that serum PUAFR is inversely associated with DR. Although PUFAR-alteration is not observed amongst different stages of DR, it can serve as an ideal biomarker in distinguishing patients with DR from those without DR. Funding: This study was funded by Natural Science Foundation of Zhejiang Province, Zhejiang Basic Public Welfare Research Project, the Major Project of the Eye Hospital of Wenzhou Medical University, and the Academician's Science and Technology Innovation Program in Zhejiang province. Part of this work was also funded by the National Nature Science Foundation of China, and Research Project for College Students in Wenzhou Medical University.

Background: Accurate 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). Methods: All 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. Findings: Independent 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. Interpretation: The nomogram presents accurate and favourable prognostic prediction for PLHIV who underwent ART. Funding: This work was supported by Zhejiang Basic Public Welfare Research Project (LGF19H260011), Wenzhou Basic Public Welfare Research Project (Y20180201), the Initial Scientific Research Fund (KYQD170301), the Major Project of the Eye Hospital Wenzhou the Major Project of the Eye Hospital Wenzhou Medical University (YNZD201602). Part of this work was also funded by National Natural Science Foundation of China (81670777) and Science and Technology Innovation Activity Plan and New Talents Plan for College Students in Zhejiang Province (2019R413073). The funders had no roles in study design, data collection, data analysis, interpretation and writing of the report. Keywords: PLHIV, Nomogram, Prognosis, HIV/AIDS-related mortality, DCA

Introduction Despite 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 methods In 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.Results We 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.Conclusions This 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.

Background Considering its emergence as a public health concern worldwide, with potential spatial-temporal heterogeneities, we aimed to determine the global burden of early-onset liver cancer attributable to aetiologies and concomitant risk factors. Methods We used data from the Global Burden of Diseases Study 2019 to determine age-standardised disability-adjusted life-year (DALY) rates for early-onset liver cancer by aetiologies and the population DALYs attributable to concomitant risk factors between 2010 and 2019. We also calculated estimated annual percentage changes (EAPCs) to measure temporal trends. Results There were 2.9 million DALYs related to early-onset liver cancer globally in 2019. East Asia contributed over half of DALYs, which increased annually by 1.23% (95% confidence interval (CI) = 0.71, 1.76) between 2010 and 2019. Non-alcoholic steatohepatitis was the only growing aetiology. The proportion of DALYs attributed to metabolic risks increased by 22.50% (95% CI = 14.33, 38.13), while behavioral risks remained stable. Obesity surpassed smoking as the most prevalent nondeterministic aetiological risk factor from 2010 to 2019, while the population DALY attributable to hepatitis B combined with obesity increased by 29.93% (95% CI = 8.49, 60.77) in the same period, making it the principal joint contributor. Conclusions Early-onset liver cancer poses considerable disability and continues to increase in many regions, especially in East Asia. Metabolic risk factors, particularly when hepatitis B and obesity coexist, are the fastest-growing contributors to this type of cancer. More targeted interventions are imperative to curb the growing burden of early-onset liver cancer due to metabolic risks. [ABSTRACT FROM AUTHOR]

Objective: To comprehensively assess the association between operative positioning with intraoperative-acquired pressure injury (IAPI) development., Methods: This retrospective cohort study included 455 patients who underwent surgery between October 2020 and January 2021. The authors grouped patients by operative positioning into the prone position and nonprone position groups. They used propensity-score matching at a 1:2 ratio to control for preoperative confounders, applied multiple logistic regression models to analyze the effects between positioning and IAPI, and assessed interactions of positioning and intraoperative factors on IAPI., Results: The final enrollment was 92 cases in the prone position group and 181 in the nonprone position group. Multivariable logistic analysis suggested that the prone position had a 2.92 times higher risk of IAPI than the nonprone position (odds ratio, 2.92; 95% CI, 1.13-7.57; P = .026). Subgroup analysis showed a significant multiplicative interaction between positioning and foam dressing on IAPI (P < .05), which was not observed in other intraoperative factors (P > .05)., Conclusions: This study provides evidence that prone operative positioning can increase IAPI risk. Patients in the prone position may particularly benefit from using dressings in Chinese populations. Further large-sample longitudinal studies are required to confirm these findings., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)