ObjectiveThis study explores the clinical characteristics of patients with diabetes with severe covid-19, and the association of diabetes with survival duration in patients with severe covid-19.Research design and methodsIn this single-center, retrospective, observational study, the clinical and laboratory characteristics of 193 patients with severe covid-19 were collected. 48 patients with severe covid-19 had diabetes, and 145 patients (ie, the controls) did not have diabetes. A severe case was defined as including at least one of the following criteria: (1) Respiratory rate >30/min. (2) Oxygen saturation ≤93%. (3) PaO2/FiO2≤300 mm Hg. (4) Patients, either with shock or respiratory failure, requiring mechanical ventilation, or combined with other organ failure, requiring admission to intensive care unit (ICU).ResultsOf 193 patients with severe covid-19, 48 (24.9%) had diabetes. Compared with patients with severe covid-19 without diabetes, patients with diabetes were older, susceptible to receiving mechanical ventilation and admission to ICU, and had higher mortality. In addition, patients with severe covid-19 with diabetes had higher levels of leukocyte count, neutrophil count, high-sensitivity C reaction protein, procalcitonin, ferritin, interleukin (IL) 2 receptor, IL-6, IL-8, tumor necrosis factor α, D-dimer, fibrinogen, lactic dehydrogenase and N-terminal pro-brain natriuretic peptide. Among patients with severe covid-19 with diabetes, more non-survivors were men (30 (76.9%) vs 9 (23.1%)). Non-survivors had severe inflammatory response, and cardiac, hepatic, renal and coagulation impairment. Finally, the Kaplan-Meier survival curve showed a trend towards poorer survival in patients with severe covid-19 with diabetes than patients without diabetes. The HR was 1.53 (95% CI 1.02 to 2.30; p=0.041) after adjustment for age, sex, hypertension, cardiovascular disease and cerebrovascular disease by Cox regression. The median survival durations from hospital admission in patients with severe covid-19 with and without diabetes were 10 days and 18 days, respectively.ConclusionThe mortality rate in patients with severe covid-19 with diabetes is considerable. Diabetes may lead to an increase in the risk of death.
Non-insulin-dependent (type 2) diabetes mellitus (NIDDM) is a common disorder of middle-aged individuals characterized by high blood glucose levels which, if untreated, can cause serious medical complications and lead to early death. Genetic factors play an important role in determining susceptibility to this disorder. However, the number of genes involved, their chromosomal location and the magnitude of their effect on NIDDM susceptibility are unknown. We have screened the human genome for susceptibility genes for NIDDM using non-and quasi-parametric linkage analysis methods in a group of Mexican American affected sib pairs. One marker, D2S125, showed significant evidence of linkage to NIDDM and appears to be a major factor affecting the development of diabetes mellitus in Mexican Americans. We propose that this locus be designated NIDDM1.
In a rapidly changing climate, alpine plants may persist by adapting to new conditions. However, the rate at which the climate is changing might exceed the rate of adaptation through evolutionary processes in long-lived plants. Persistence may depend on phenotypic plasticity in morphology and physiology. Here we investigated patterns of leaf trait variation including leaf area, leaf thickness, specific leaf area, leaf dry matter content, leaf nutrients (C, N, P) and isotopes (δ13C and δ15N) across an elevation gradient on Gongga Mountain, Sichuan Province, China. We quantified inter- and intra-specific trait variation and the plasticity in leaf traits of selected species to experimental warming and cooling by using a reciprocal transplantation approach. We found substantial phenotypic plasticity in most functional traits where δ15N, leaf area, and leaf P showed greatest plasticity. These traits did not correspond with traits with the largest amount of intraspecific variation. Plasticity in leaf functional traits tended to enable plant populations to shift their trait values toward the mean values of a transplanted plants’ destination community, but only if that population started with very different trait values. These results suggest that leaf trait plasticity is an important mechanism for enabling plants to persist within communities and to better tolerate changing environmental conditions under climate change.
BackgroundThe triglyceride and glucose index (TyG) has been proposed as a marker of insulin resistance. We aimed to investigate the ability of TyG, through comparing with the predictive value of alanine aminotransferase (ALT), to identify individuals at risk for nonalcoholic fatty liver disease (NAFLD).MethodsA cross-sectional study was conducted in a Chinese health examination cohort of 10 761 people aged above 20 years. NAFLD was diagnosed by ultrasonography.ResultsCompared with the participants in the lowest quartile of TyG, the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for NAFLD were 1.8 (1.5–2.1), 3.0 (2.5–3.5), and 6.3 (5.3–7.5) for those in the second, the third, and the fourth quartile of TyG, whereas the corresponding ORs (95% CI) for NAFLD were 1.5 (1.3–1.7), 1.9 (1.6–2.2), and 3.1 (2.6–3.7) for the upper three quartiles of ALT. These results suggested that TyG was superior to ALT in association with NAFLD risk. According to the ROC analysis, the optimal cut-off point of TyG for NAFLD was 8.5 and the area under the ROC curve (AUC) was 0.782 (95% CI 0.773–0.790), with 72.2 and 70.5% sensitivity and specificity, respectively. The AUC of TyG was larger than that of ALT (0.715 (95% CI 0.705–0.725), P for difference <0.0001), whereas the largest AUC was obtained when adding TyG to ALT (0.804 (95% CI 0.795–0.812), P for difference <0.0001).ConclusionsTyG is effective to identify individuals at risk for NAFLD. A TyG threshold of 8.5 was highly sensitive for detecting NAFLD subjects and may be suitable as a diagnostic criterion for NAFLD in Chinese adults.Electronic supplementary materialThe online version of this article (doi:10.1186/s12944-017-0409-6) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.