Study of the Significance of Thromboelastography Changes in Patients with Dyslipidemia

Comparative studies between humans and golden Syrian hamsters via thromboelastography

BACKGROUND

Thromboelastography (TEG) is a widely utilized clinical testing method for real-time monitoring of platelet function and the thrombosis process. Lipid metabolism disorders are crucial risk factors for thrombosis. The lipid metabolism characteristics of hamsters resemble those of humans more closely than mice and rats, and their relatively large blood volume makes them suitable for studying the mechanisms of thrombosis related to plasma lipid mechanisms. Whole blood samples from golden Syrian hamsters and healthy humans were obtained following standard clinical procedures. TEG was employed to evaluate coagulation factor function, fibrinogen (Fib) function, platelet function, and the fibrinolytic system.

METHODS

The whole blood from hamster or healthy human was isolated following the clinical procedure, and TEG was employed to evaluate the coagulation factor function, Fib function, platelet function, and fibrinolytic system. Coagulation analysis used ACLTOP750 automatic coagulation analysis pipeline. Blood routine testing used XN-2000 automatic blood analyzer.

RESULTS

TEG parameters revealed that hamsters exhibited stronger coagulation factor function than humans (reaction time [R], p = 0.0117), with stronger Fib function (alpha angle, p < 0.0001; K-time [K], p < 0.0001). Platelet function did not differ significantly (maximum amplitude [MA], p = 0.077). Hamsters displayed higher coagulation status than humans (coagulation index [CI], p = 0.0023), and the rate of blood clot dissolution in hamsters differed from that in humans (percentage lysis 30 min after MA, p = 0.02). Coagulation analysis parameters indicated that prothrombin time (PT) and activated partial thromboplastin time (APTT) were faster in hamsters than in humans (PT, p = 0.0014; APTT, p = 0.03), whereas the Fib content was significantly lower in hamsters than in humans (p < 0.0001). No significant difference was observed in thrombin time (p = 0.1949).

CONCLUSIONS

In summary, TEG could be used to evaluate thrombosis and bleeding parameters in whole blood samples from hamsters. The platelet function of hamsters closely resembled that of humans, whereas their coagulation function was significantly stronger.

Retracted: Study of the Significance of Thromboelastography Changes in Patients with Dyslipidemia

[This retracts the article DOI: 10.1155/2022/1927881.].

Cardiometabolic Risk Factors Associated With Type 2 Diabetes Mellitus: A Mechanistic Insight

A complex metabolic condition referred to as Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance (IR) and decreased insulin production. Obesity, dyslipidemia, hypertension, and chronic inflammation are just a few of the cardiometabolic illnesses that people with T2DM are more likely to acquire and results in cardiovascular issues. It is essential to comprehend the mechanistic insights into these risk variables in order to prevent and manage cardiovascular problems in T2DM effectively. Impaired glycemic control leads to upregulation of De novo lipogenesis (DNL), promote hepatic triglyceride (TG) synthesis, worsening dyslipidemia that is accompanied by low levels of high density lipoprotein cholesterol (HDL-C) and high amounts of small, dense low-density lipoprotein cholesterol (LDL-C) further developing atherosclerosis. By causing endothelial dysfunction, oxidative stress, and chronic inflammation, chronic hyperglycemia worsens already existing cardiometabolic risk factors. Vasoconstriction, inflammation, and platelet aggregation are caused by endothelial dysfunction, which is characterized by decreased nitric oxide production, increased release of vasoconstrictors, proinflammatory cytokines, and adhesion molecules. The loop of IR and endothelial dysfunction is sustained by chronic inflammation fueled by inflammatory mediators produced in adipose tissue. Infiltrating inflammatory cells exacerbate inflammation and the development of plaque in the artery wall. In addition, the combination of chronic inflammation, dyslipidemia, and IR contributes to the emergence of hypertension, a prevalent comorbidity in T2DM. The ability to target therapies and management techniques is made possible by improvements in our knowledge of these mechanistic insights. Aim of present review is to enhance our current understanding of the mechanistic insights into the cardiometabolic risk factors related to T2DM provides important details into the interaction of pathophysiological processes resulting in cardiovascular problems. Understanding these pathways will enable us to create efficient plans for the prevention, detection, and treatment of cardiovascular problems in T2DM patients, ultimately leading to better overall health outcomes.

A Predictive Model to Evaluate the HbeAg Positivity of Chronic Hepatitis B Virus Patients in Clinics: A Cross-Sectional Study

Background and Objective: The study aims to investigate the correlation between Hepatitis B ‘e’ antigen (HBeAg) and HBV DNA levels, and to find a convenient tool to estimate the HBV DNA level for clinicians. Materials and Methods: We enrolled 1020 patients in this cross-sectional study and divided them into four groups: an HbeAg-positive and -negative group, and high and low HBV DNA levels groups. Results: Alanine aminotransferase (ALT), Albumin (ALB) and HBeAg are independent risk factors for CHB patients. When the level of HBeAg is higher than 16.15 S/CO, it is four times more likely that the patients will have high levels of HBV DNA than those who do not. The ALT and TB are independent risk factors in HBeAg-negative patients with a high HBV DNA level. We have drawn three predictive models to estimate the HBV DNA levels for those with the chronic hepatitis B virus (CHB), and those that are HBeAg-positive and HBeAg-negative (Y1 = 0.004 × ALT(IU/L) + 1.412 × HBeAg (S/CO) − 0.029 × ALB (g/L) + 0.779, the AUC is 0.672, and the cutoff value is −0.072, there the sensitivity is 0.615, the specificity is 0.648, PPV is 65.182% and NPV is 60.837%; Y2 = 0.007 × HBeAg (S/CO) − 0.016 × HGB (g/L) + 3.070, the AUC is 0.724, and the cutoff value is 1.216, where the sensitivity is 0.626, the specificity is 0.897, PPV is 94.118% and NPV is 34.437%; Y3 = −0.005 × ALT(IU/L) + 0.006 × TB (umol/L) + 0.385, the AUC is 0.661, and the cutoff value is 0.263, where the sensitivity is 0.677, the specificity is 0.587, PPV is 66.820% and NPV is 40.774%, respectively). We propose that HBeAg is the most important risk factor for the patient with a high HBV DNA level, however, it is not as important in the HBeAg-positive group. Conclusions: HBeAg is an independent risk factor that reflects the level of HBV DNA with a strong correlation. Patient with HBeAg (−) should combine TB and ALT to estimate the level of HBV DNA.