Are lipid ratios and triglyceride-glucose index associated with critical care outcomes in COVID-19 patients?

Triglyceride glucose (TyG) index: A promising biomarker for diagnosis and treatment of different diseases

The Triglyceride-glucose index (TyG index) is a comprehensive statistical measure that incorporates fasting triglyceride and fasting glucose levels. Research has demonstrated that it can serve as an effective alternative biomarker for insulin resistance (IR) due to its high sensitivity and specificity. The TyG index is straightforward to compute and imposes fewer time and cost constraints, rendering it suitable for large populations and advantageous for use in various applications, clinical settings, and epidemiological investigations. Numerous high-quality clinical studies have underscored the significance of the TyG index in diverse medical conditions. This review provides a synthesis of the association between the TyG index and diseases such as diabetes, cardiovascular diseases, cerebrovascular diseases, fatty liver, kidney diseases, and reproductive system diseases. Furthermore, the TyG index has exhibited predictive capabilities for identifying IR in children and adolescents. Through a systematic review of pertinent clinical trials, this paper elucidates the correlation between the TyG index and various diseases. The findings presented herein suggest that the TyG index holds promise as a valuable and practical indicator for different medical conditions, prompting a reevaluation of conventional disease risk assessment paradigms and highlighting the intricate interplay of metabolic parameters with diverse diseases. By leveraging insights from the TyG index, tailored disease risk management strategies can be developed to offer a fresh perspective and guidance for clinical interventions.

Type 2 diabetes and susceptibility to COVID-19: a machine learning analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) was one of the most prevalent comorbidities among patients with coronavirus disease 2019 (COVID-19). Interactions between different metabolic parameters contribute to the susceptibility to the virus; thereby, this study aimed to rank the importance of clinical and laboratory variables as risk factors for COVID-19 or as protective factors against it by applying machine learning methods.

METHOD

This study is a retrospective cohort conducted at a single center, focusing on a population with T2DM. The patients attended the Yazd Diabetes Research Center in Yazd, Iran, from February 20, 2020, to October 21, 2020. Clinical and laboratory data were collected within three months before the onset of the COVID-19 pandemic in Iran. 59 patients were infected with COVID-19, while 59 were not. The dataset was split into 70% training and 30% test sets. Principal Component Analysis (PCA) was applied to the data. The most important components were selected using a 'sequential feature selector' and scored by a Linear Discriminant Analysis model. PCA loadings were then multiplied by the PCs' scores to determine the importance of the original variables in contracting COVID-19.

RESULTS

HDL-C, followed by eGFR, showed a strong negative correlation with the risk of contracting the virus. Higher levels of HDL-C and eGFR offer protection against COVID-19 in the T2DM population. But, the ratio of BUN to creatinine did not show any correlation. Conversely, the AIP, TyG index and TG showed the most positive correlation with susceptibility to COVID-19 in such a way that higher levels of these factors increase the risk of contracting the virus. The positive correlation of diastolic BP, TyG-BMI index, MAP, BMI, weight, TC, FPG, HbA1C, Cr, systolic BP, BUN, and LDL-C with the risk of COVID-19 decreased, respectively.

CONCLUSION

The atherogenic index of plasma, triglyceride glucose index, and triglyceride levels are the most significant risk factors for COVID-19 contracting in individuals with T2DM. Meanwhile, high-density lipoprotein cholesterol is the most protective factor.

The predictive significance of uric acid to high density lipoprotein- cholesterol ratio and uric acid for the severity and mortality of coronavirus disease-19

OBJECTIVE

The non-invasive and inexpensive predictive indicators seem to be essential for the evaluation of coronavirus disease-19 (COVID-19) prognosis. Uric acid to high-density lipoprotein-cholesterol ratio (UHR) have been known as inflammatory and metabolic biomarker in some disorders. This study aimed to evaluate the usefulness of serum uric acid (UA) and UHR values on admission as prognostic indicators for the severity and mortality of COVID-19. Regression models were accomplished to assess the association between UA and UHR with the severity and mortality of COVID-19.

RESULTS

This study was performed with 424 confirmed COVID-19 patients. The mean UA and UHR values of the severe group and deceased group were statistically higher than those mild group and survivor group, respectively (P < 0.05). Compared to the survivor cases, deceased subjects had lower serum concentrations of HDL-c (p < 0.05). Multivariate logistic regression analysis showed that UHR and UA values statistically are correlated with the severity (OR = 1.20 CI:1.07-1.35, OR = 1.19 CI:1.023-1.381 respectively) and mortality (OR = 10.04 CI:1.50-67.30, OR = 10.73 CI:1.47-87.11, respectively) of COVID-19. Compared with a reference range, serum UA levels ≥ 7.3 mg/dl and a UHR value greater than 0.185 increase the risk of critical care of COVID-19 almost 2.5 and 3.5 times, respectively. In summary, our results revealed that UHR index value and serum UA levels are useful biochemical indicators for predicting the severity and mortality of COVID-19.

The prognostic significance of insulin resistance in COVID-19: a review

Objectives

Emerging publications indicate that diabetes predisposes patients with COVID-19 to more severe complications, which is partly attributed to inflammatory condition. In the current review, we reviewed recent published literature to provide evidence on the role of insulin resistance (IR) in diabetes, the association between diabetes and COVID-19 severity and mortality, the impact of COVID-19 infection on incident new-onset diabetes, mechanisms responsible for IR in COVID-19 patients, and the predictive value of different surrogates of IR in COVID-19.

Method

The literature search performs to find out studies that have assessed the association between IR surrogates and morbidity and mortality in patients with COVID-19.

Results

We showed that there is a bulk of evidence in support of the fact that diabetes is a potent risk factor for enhanced morbidity and mortality in COVID-19 patients. COVID-19 patients with diabetes are more prone to remarkable dysglycemia compared to those without diabetes, which is associated with an unfavourable prognosis. Furthermore, SARS-COV2 can make patients predispose to IR and diabetes via activating ISR, affecting RAAS signaling pathway, provoking inflammation, and changing the expression of PPARɣ and SREBP-1. Additionally, higher IR is associated with increased morbidity and mortality in COVID-19 patients and different surrogates of IR can be utilized as a prognostic biomarker for COVID-19 patients.

Conclusion

Different surrogates of IR can be utilized as predictors of COVID-19 complications and death.

Association between lipid profile and clinical outcomes in COVID-19 patients

High-density lipoprotein cholesterol (HDL-c) removes cholesterol, an essential component in lipid rafts, and this cholesterol removal can regulate protein attachment to lipid rafts, modulating their functionality in the immune cell response. Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can alter the lipid profile, there is little information on the role of HDL-c and other lipids in prognostic of the coronavirus disease 2019 (COVID-19) in Mexican population. This study aims to evaluate the predictive value of HDL-c and lipid profile on severity and survival of 102 patients infected with SARS-CoV-2 during the COVID-19 first wave. Our findings, derived from univariate and multivariate Cox proportional hazards regression models, highlighted age and hypertension as significant predictors of survival (HR = 1.04, p = 0.012; HR = 2.78, p = 0.027), while gender, diabetes, and obesity showed no significant impact. Triglycerides and HDL-c levels notably influenced mortality, with elevated triglycerides and lower HDL-c associated with higher mortality risk (p = 0.032). This study underscores the importance of lipid profiles alongside traditional risk factors in assessing COVID-19 risk and outcomes. It contributes to the understanding of COVID-19 patient management and emphasizes the need for further investigation into the role of dyslipidemia in influencing COVID-19 prognosis, potentially aiding in refined risk stratification and therapeutic strategies.

Correlation between epicardial adipose tissue and myocardial injury in patients with COVID-19

Background: Many people infected with COVID-19 develop myocardial injury. Epicardial adipose tissue (EAT) is among the various risk factors contributing to coronary artery disease. However, its correlation with myocardial injury in patients diagnosed with COVID-19 remains uncertain. Methods: We examined myocardial biomarkers in population affected by COVID-19 during the period from December 2022 to January 2023. The patients without myocardial injury were referred to as group A (n = 152) and those with myocardial injury were referred to as group B (n = 212). Results: 1) The A group and the B group exhibitedstatistically significant differences in terms of age, TC, CRP, Cr, BUN, LDL-C, IL-6, BNP, LVEF and EAT (p < 0.05). 2) EAT volumehad a close relationship with IL-6, LDL-C, cTnI, and CRP (p < 0.05); the corresponding correlation coefficient values were 0.24, 0.21, 0.24, and 0.16. In contrast to those with lower EAT volume, more subjects with a higher volume of EAT had myocardial injury (p < 0.05). Regression analysis showed that EAT, LDL-C, Age and Cr were established as independent risk variables for myocardial injury in subjects affected by COVID-19. 3) In COVID-19 patients, the likelihood of myocardial injury rised notably as EAT levels increase (p < 0.001). Addition of EAT to the basic risk model for myocardial injury resulted in improved reclassification. (Net reclassification index: 58.17%, 95% CI: 38.35%, 77.99%, p < 0.001). Conclusion: Patients suffering from COVID-19 with higher volume EAT was prone to follow myocardial injury and EAT was an independent predictor of heart damage in these individuals.

Association of triglyceride-glucose index with vascular risk factors and clinical outcomes among COVID-19 patients: a retrospective cross-sectional study in Mengo Hospital, Kampala, Uganda

Introduction

triglyceride-glucose (TyG) index is a reliable surrogate marker of insulin resistance. We assessed the association between triglyceride-glucose (TyG) index and vascular risk factors and clinical outcomes of critically ill adult COVID-19 patients.

Methods

data from the charts of all patients with a confirmed diagnosis of COVID-19 who were hospitalized at Mengo Hospital Uganda from December 2020 to August 2021 was used for this study. Data on demographics, past medical history, clinical presentation, laboratory findings and clinical outcomes within the first 10 days of admission was extracted. TyG index was calculated as Inverse (triglyceride (mg/dl) x fasting glucose level (mg/dl)/2 and defined vascular risk factors using standard methods. Bivariate and multivariate logistic regression was conducted to establish a significant association. Statistical significance was set at p< 0.05.

Results

out of 314 patients, 176 (56%) were females. The mean age ± SD was 58.2 years ± 16.82. The median TyG index was 9.76 (9.29-10.33). A high TyG index was found among 85.4% (n= 268, 95% CI: 0.809-0.889) of patients. Elevated total cholesterol was in 55.4% (n=174), triglycerides 70.7% (n=222), LDL 64.7% (n=203), blood glucose 80.6% (n=253), systolic blood pressure 43% (n=135) and 24.8% (n=78) diastolic blood pressure. The majority 49.7% ( n=156) were discharged, 22.0% (n=69) needed admission to the intensive care unit (ICU), 15.3% (n=48) died in the unit and 13.0% (n=41) had a composite outcome. The TyG index was significantly associated with glycated hemoglobin (AOR=1.029, 95%CI 0.561-1.496, p<0.001), low-density lipoprotein cholesterol (AOR=0.121,95%CI 0.023-0.219, p=0.016), high-density cholesterol (AOR=1.956, 95%CI 1.299-2.945, p=0.001), total cholesterol (AOR=2.177, 95%CI 1.5222-3.144, p<0.001, hospital death (AOR=0.778, 95%CI 0.623-0.972, p=0.028) and composite outcome (AOR=1.823, 95% CI 1.221-2.559, p=0.023). There was no association between hypertension and TyG index.

Conclusion

a high TyG index was associated with vascular risk factors and clinical outcomes.

Biomarkers of glucose homeostasis as mediators of the relationship of body mass index and waist circumference with COVID-19 outcomes among postmenopausal women: The Women's Health Initiative

BACKGROUND & AIMS

Systematic reviews, meta-analyses and Mendelian randomization studies suggest that cardiometabolic diseases may be associated with COVID-19 risk and prognosis, with evidence implicating insulin resistance (IR) as a common biological mechanism. As driving factors for IR, we examined body mass index (BMI) and waist circumference (WC) among postmenopausal women in association with COVID-19 outcomes (positivity and hospitalization), and the role of glucose homeostasis as a mediator of this relationship.

METHODS

Associations of BMI and WC at baseline (1993-1998) with COVID-19 outcomes collected at Survey 1 (June-December, 2020) and/or Survey 2 (September-December, 2021) were evaluated among 42,770 Women's Health Initiative (WHI) participants (baseline age: 59.36 years) of whom 16,526 self-reported having taken ≥1 COVID-19 test, with 1242 reporting ≥1 positive COVID-19 test and 362 reporting ≥1 COVID-19 hospitalization. We applied logistic regression and causal mediation analyses to sub-samples with available fasting biomarkers of glucose homeostasis (glucose, insulin, Homeostatic Model Assessment for Insulin Resistance, Homeostasis Model Assessment for β-cell function, Quantitative Insulin-sensitivity Check Index, Triglyceride-Glucose index (TyG)) at baseline, whereby 57 of 759 reported COVID-19 test positivity and 23 of 1896 reported COVID-19 hospitalization.

RESULTS

In fully adjusted models, higher BMI, WC and TyG were associated with COVID-19 test positivity and hospitalization. Glucose concentrations mediated associations of BMI and WC with COVID-19 positivity, whereas TyG mediated BMI and WC's associations with COVID-19 hospitalization.

CONCLUSIONS

Obesity and central obesity markers collected an average of 24 years prior were associated with COVID-19 outcomes among postmenopausal women. Glucose concentration and TyG partly mediated these associations.

Glycemic Dysregulation, Inflammation and Disease Outcomes in Patients Hospitalized with COVID-19: Beyond Diabetes and Obesity

INTRODUCTION

During the COVID-19 pandemic, diabetes mellitus (DM) and obesity were associated with high rates of morbidity and mortality. The aim of this study was to investigate the relationship between markers of inflammation, disease severity, insulin resistance, hyperglycemia, and outcomes in COVID-19 patients with and without diabetes and obesity.

MATERIALS AND METHODS

Epidemiological, clinical, and laboratory data were collected from the University Hospital of Ioannina COVID-19 Registry and included hospitalized patients from March 2020 to December 2022. The study cohort was divided into three subgroups based on the presence of DM, obesity, or the absence of both.

RESULTS

In diabetic patients, elevated CRP, IL-6, TRG/HDL-C ratio, and TyG index, severe pneumonia, and hyperglycemia were associated with extended hospitalization. Increased IL-6, NLR, and decreased PFR were associated with a higher risk of death. In the obese subgroup, lower levels of PFR were associated with longer hospitalization and a higher risk of death, while severe lung disease and hyperglycemia were associated with extended hospitalization. In patients without DM or obesity severe pneumonia, NLR, CRP, IL-6, insulin resistance indices, and hyperglycemia during hospitalization were associated with longer hospitalization.

CONCLUSION

Inflammatory markers and disease severity indices were strongly associated with disease outcomes and hyperglycemia across all subgroups.

Connections between Diabetes Mellitus and Metabolic Syndrome and the Outcome of Cardiac Dysfunctions Diagnosed during the Recovery from COVID-19 in Patients without a Previous History of Cardiovascular Diseases

(1) Background: Throughout the COVID-19 pandemic, it became obvious that individuals suffering with obesity, diabetes mellitus (T2DM), and metabolic syndrome (MS) frequently developed persisting cardiovascular complications, which were partially able to explain the onset of the long-COVID-19 syndrome. (2) Methods: Our aim was to document, by transthoracic echocardiography (TTE), the presence of cardiac alterations in 112 patients suffering from post-acute COVID-19 syndrome and T2DM, MS, and/or obesity, in comparison to 91 individuals without metabolic dysfunctions (MD); (3) Results: in patients with MD, TTE borderline/abnormal left (LVF) and/or right ventricular function (RVF), alongside diastolic dysfunction (DD), were more frequently evidenced, when compared to controls (p ˂ 0.001). Statistically significant associations between TTE parameters and the number of factors defining MS, the triglyceride-glucose (TyG) index, the severity of the SARS-CoV-2 infection, and the number of persisting symptoms (p ˂ 0.001) were noted. Significant predictive values for the initial C-reactive protein and TyG index levels, both for the initial and the 6-month follow-up levels of these TTE abnormalities (p ˂ 0.001), were highlighted by means of a multivariate regression analysis. (4) Conclusions: in diabetic patients with MS and/or obesity with comorbid post-acute COVID-19 syndrome, a comprehensive TTE delineates various cardiovascular alterations, when compared with controls. After 6 months, LVF and RVF appeared to normalize, however, the DD-although somewhat improved-did persist in approximately a quarter of patients with MD, possibly due to chronic myocardial changes.

Correspondence between Aortic and Arterial Stiffness, and Diastolic Dysfunction in Apparently Healthy Female Patients with Post-Acute COVID-19 Syndrome

(1) Background: Abnormally increased arterial and aortic stiffness (AS and AoS), which are often associated with diastolic dysfunction (DD), represent common alterations in COVID-19. In this study, we aimed to assess, by transthoracic echocardiography (TTE) and pulse-wave velocity (PWV), the frequency of these dysfunctions in patients with post-acute COVID-19 syndrome and to highlight potential correlations between their severity and multiple clinical and laboratory parameters. (2) Methods: In total, 121 women were included in our study, all of whom were younger than 55 and had been diagnosed with post-COVID-19 syndrome. Of those women, 67 also had metabolic syndrome (MS) (group A), whereas the other 54 did not (group B); 40 age-matched healthy subjects were used as controls (group C). (3) Results: Patients in group A had worse values of indexes characterizing AS and AoS and had more frequent DD compared to those from group B and group C (p < 0.0001). The statistical analysis evidenced significant associations between these indexes and the time that had elapsed since COVID-19 diagnosis, the factors that characterize the severity of the acute disease and those that specify MS. Multivariate regression analysis identified the following as the main independent predictors for DD: values of the AoS index, the C-reactive protein, and the triglyceride-glucose index. (4) Conclusions: Altered AS, AoS, and DD are common in patients with post-COVID-19 syndrome, especially with concurrent MS, and these parameters are apparently associated not only with the severity and time elapsed since COVID-19 diagnosis but also with MS.

Comorbid Asthma Increased the Risk for COVID-19 Mortality in Asia: A Meta-Analysis

We aimed to explore the influence of comorbid asthma on the risk for mortality among patients with coronavirus disease 2019 (COVID-19) in Asia by using a meta-analysis. Electronic databases were systematically searched for eligible studies. The pooled odds ratio (OR) with 95% confidence interval (CI) was estimated by using a random-effect model. An inconsistency index (I2) was utilized to assess the statistical heterogeneity. A total of 103 eligible studies with 198,078 COVID-19 patients were enrolled in the meta-analysis; our results demonstrated that comorbid asthma was significantly related to an increased risk for COVID-19 mortality in Asia (pooled OR = 1.42, 95% CI: 1.20−1.68; I2 = 70%, p < 0.01). Subgroup analyses by the proportion of males, setting, and sample sizes generated consistent findings. Meta-regression indicated that male proportion might be the possible sources of heterogeneity. A sensitivity analysis exhibited the reliability and stability of the overall results. Both Begg’s analysis (p = 0.835) and Egger’s analysis (p = 0.847) revealed that publication bias might not exist. In conclusion, COVID-19 patients with comorbid asthma might bear a higher risk for mortality in Asia, at least among non-elderly individuals.