scholarly journals 498 Oxidative stress and left ventricular performance in patients according to different glycometabolic phenotypes

2021 ◽  
Vol 23 (Supplement_G) ◽  
Author(s):  
Sofia Miceli ◽  
Velia Cassano ◽  
Elvira Clausi ◽  
Vittoria Monaco ◽  
Giuseppe Armentaro ◽  
...  

Abstract Recent studies demonstrated that in normoglucose-tolerant subjects (NGT), 1-h post load plasma glucose value ≥155 mg/dL, during OGTT, identifies a worse cardio-metabolic risk profile with increased risk for Type 2 Diabetes Mellitus (T2DM). T2DM patients present increased oxidative stress, due to high blood glucose levels, which plays a central role in the development of CV events. The aim of our study was to evaluate the correlation between oxidative stress and subclinical myocardial damage, assessed with speckle tracking echocardiography, in NGT patients with 1-h post load ≥155 mg/dL vs. NGT < 155 subjects, impaired glucose tolerance (IGT) and T2DM patients. We enrolled 100 Caucasian patients (61 M, 39 W, mean age 61.4 ± 10.7) afferent to CATAMERI study. Main exclusion criteria were CV complications, history of malignant or chronic respiratory disease, alcohol, drug influencing glucose metabolism or smoking abuse. All subjects underwent clinical and laboratory evaluation, OGTT and HOMA-IR. The serum values of the markers of oxidative stress (8-isoprostane and NOX-2) were assessed with ELISA sandwich. Statistical analysis was performed with ANOVA test, linear correlation analysis and stepwise multivariate linear regression model. According to OGTT results, subjects were divided into 4 groups: NGT < 155 (n = 30), NGT ≥ 155 (n = 24), IGT (n = 28), T2DM (n = 18). Serum levels of 8-isoprostane and NOX-2 were significantly increased (P < 0.0001) in NGT  ≥ 155 compared to NGT < 155 group, but similar with IGT, indicating an increase in oxidative stress with the worsening of the metabolic status. The left global systolic function, evaluated as myocardial deformation and global longitudinal strain (GLS), appeared progressively lower proceeding from the NGT < 155 group to the T2DM group (P < 0.0001). Moreover, for similar values of ejection fraction (EF), NGT ≥ 155 subjects presented reduced GLS compared to NGT < 155 (P = 0.001), but similar to IGT patients. The linear correlation analysis showed that endo/epi ratio was significantly and inversely correlated with 1 h post load glycaemia (r = −0.632, P < 0.0001), NOX-2 (r = −0.638, P < 0.0001), 8-isoprostane (r = −0.508, P < 0.0001); GLS was inversely correlated with 1 h post load glycaemia (r = −0.734, P < 0.0001) and directly and significantly correlated with 8-isoprostane (r = 0.564, P < 0.0001), NOX-2 (r = 0.625, P < 0.0001). From stepwise multivariate linear regression model, NOX-2 resulted the major predictor of endo/epi ratio, justifying 40.7% of its variation. 1-h post load glycaemia was the second predictor of endo/epi ratio justifying another 9.2% of its variation. Similarly 1-h post load glycaemia was the strongest predictor of the GLS, explaining 53.9% of its variation. Our study demonstrated that NGT ≥ 155 subjects present functional alterations of myocardial contractile fibres, compared to NGT < 155 subjects, but similar to IGT, and these alterations are correlated with oxidative stress. Moreover, GLS is able to identify early alterations in the contractility of subendocardial longitudinal fibres long before the alteration of EF. This data have a central role in ongoing research on the association between hyperglycaemia at 1-h post load and CV risk.

PLoS ONE ◽  
2018 ◽  
Vol 13 (7) ◽  
pp. e0201011 ◽  
Author(s):  
Rui Zhao ◽  
Xinxin Gu ◽  
Bing Xue ◽  
Jianqiang Zhang ◽  
Wanxia Ren

2020 ◽  
Author(s):  
Haoua Tall ◽  
Issaka Yaméogo ◽  
Ryan Novak ◽  
Lionel L Ouedraogo ◽  
Ousmane Ouedraogo ◽  
...  

Abstract Background: Meningitis is a major cause of morbidity in the world. Previous studies showed that climate factors influence the occurrence of meningitis. A multiple linear regression model was developed to forecast meningitis cases in Burkina Faso using climate factors. However, the multivariate linear regression model based on times series data may produce fallacious results given the autocorrelation of errors. Aims: The aim of the study is to develop a model to quantify the effect of climate factors on meningitis cases, and then predict the expected weekly incidences of meningitis for each district. Data and methods: The weekly cases of meningitis come from the Ministry of Health and covers the period 2005-2017. Climate data were collected daily in 10 meteorological stations from 2005 to 2017 and were provided by the national meteorological Agency of Burkina Faso. An ARIMAX and a multivariate linear regression model were estimated separately for each district. Results: The multivariate linear model is inappropriate to model the number of meningitis cases due to autocorrelation of errors. With the ARIMAX Model, Temperature is significantly associated with an increase of meningitis cases in 3 of 10 districts, while relative humidity is significantly associated with a decrease of meningitis cases in 3 of the 10 districts. The effect of wind speed and precipitation is not significant at the 5% level in all 10 districts. The prediction of meningitis cases with 8 test observations provides an average absolute error ranging from 0.99 in Boromo and Bogandé to 7.22 in the district of Ouagadougou. Conclusion: The ARIMAX model is more appropriate than the multivariate linear model to analyze the dynamics of meningitis cases. Climatic factors such as temperature and relative humidity have a significant influence on the occurrence of meningitis in Burkina Faso; the temperature influences it positively and the relative humidity influences it negatively.


2020 ◽  
Author(s):  
Haoua Tall ◽  
Issaka Yaméogo ◽  
Ryan Novak ◽  
Lionel L Ouedraogo ◽  
Ousmane Ouedraogo ◽  
...  

Abstract Background Meningitis is a major cause of morbidity in the world. Previous studies showed that climate factors influence the occurrence of meningitis. A multiple linear regression model was developed to forecast meningitis cases in Burkina Faso using climate factors. However, the multivariate linear regression model based on times series data may produce fallacious results given the autocorrelation of errors.Aims The aim of the study is to develop a model to quantify the effect of climate factors on meningitis cases, and then predict the expected weekly incidences of meningitis for each district.Data and methods The weekly cases of meningitis come from the Ministry of Health and covers the period 2005-2017. Climate data were collected daily in 10 meteorological stations from 2005 to 2017 and were provided by the national meteorological Agency of Burkina Faso. An ARIMAX and a multivariate linear regression model were estimated separately for each district.Results The multivariate linear model is inappropriate to model the number of meningitis cases due to autocorrelation of errors. With the ARIMAX Model, Temperature is significantly associated with an increase of meningitis cases in 3 of 10 districts, while relative humidity is significantly associated with a decrease of meningitis cases in 3 of the 10 districts. The effect of wind speed and precipitation is not significant at the 5% level in all 10 districts. The prediction of meningitis cases with 8 test observations provides an average absolute error ranging from 0.99 in Boromo and Bogandé to 7.22 in the district of Ouagadougou.Conclusion The ARIMAX model is more appropriate than the multivariate linear model to analyze the dynamics of meningitis cases. Climatic factors such as temperature and relative humidity have a significant influence on the occurrence of meningitis in Burkina Faso; the temperature influences it positively and the relative humidity influences it negatively.


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