Abstract
Background
The SARS-CoV-2 outbreak poses a challenge to health care systems due to its high complication rates in patients with cardiometabolic diseases. Here, we identify risk factors and ...propose a clinical score to predict COVID-19 lethality, including specific factors for diabetes and obesity, and its role in improving risk prediction.
Methods
We obtained data of confirmed and negative COVID-19 cases and their demographic and health characteristics from the General Directorate of Epidemiology of the Mexican Ministry of Health. We investigated specific risk factors associated to COVID-19 positivity and mortality and explored the impact of diabetes and obesity on modifying COVID-19-related lethality. Finally, we built a clinical score to predict COVID-19 lethality.
Results
Among the 177 133 subjects at the time of writing this report (May 18, 2020), we observed 51 633 subjects with SARS-CoV-2 and 5,332 deaths. Risk factors for lethality in COVID-19 include early-onset diabetes, obesity, chronic obstructive pulmonary disease, advanced age, hypertension, immunosuppression, and chronic kidney disease (CKD); we observed that obesity mediates 49.5% of the effect of diabetes on COVID-19 lethality. Early-onset diabetes conferred an increased risk of hospitalization and obesity conferred an increased risk for intensive care unit admission and intubation. Our predictive score for COVID-19 lethality included age ≥ 65 years, diabetes, early-onset diabetes, obesity, age < 40 years, CKD, hypertension, and immunosuppression and significantly discriminates lethal from non-lethal COVID-19 cases (C-statistic = 0.823).
Conclusions
Here, we propose a mechanistic approach to evaluate the risk for complications and lethality attributable to COVID-19, considering the effect of obesity and diabetes in Mexico. Our score offers a clinical tool for quick determination of high-risk susceptibility patients in a first-contact scenario.
Abstract
Background
COVID-19 has had a disproportionate impact on older adults. Mexico’s population is younger, yet COVID-19’s impact on older adults is comparable to countries with older population ...structures. Here, we aim to identify health and structural determinants that increase susceptibility to COVID-19 in older Mexican adults beyond chronological aging.
Methods
We analyzed confirmed COVID-19 cases in older adults using data from the General Directorate of Epidemiology of Mexican Ministry of Health. We modeled risk factors for increased COVID-19 severity and mortality, using mixed models to incorporate multilevel data concerning healthcare access and marginalization. We also evaluated structural factors and comorbidity profiles compared to chronological age for COVID-19 mortality risk prediction.
Results
We analyzed 20 804 confirmed SARS-CoV-2 cases in adults aged 60 and older. Male sex, smoking, diabetes, and obesity were associated with pneumonia, hospitalization, and intensive care unit (ICU) admission in older adults, CKD and COPD were associated with hospitalization. High social lag indexes and access to private care were predictors of COVID-19 severity and mortality. Age was not a predictor of COVID-19 severity in individuals without comorbidities and combination of structural factors and comorbidities were better predictors of COVID-19 lethality and severity compared to chronological age alone. COVID-19 baseline lethality hazards were heterogeneously distributed across Mexican municipalities, particularly when comparing urban and rural areas.
Conclusions
Structural factors and comorbidity explain excess risk for COVID-19 severity and mortality over chronological age in older Mexican adults. Clinical decision-making related to COVID-19 should focus away from chronological aging onto more a comprehensive geriatric care approach.
Data-driven diabetes subgroups were proposed as an alternative to address diabetes heterogeneity. However, changes in trends for these subgroups have not been reported.
Here, we analyzed trends of ...diabetes subgroups, stratified by sex, race, education level, age categories, and time since diabetes diagnosis in the United States.
We used data from consecutive NHANES cycles spanning the 1988-2018 period. Diabetes subgroups (mild obesity-related MOD, severe insulin-deficient SIDD, severe insulin-resistant SIRD, and mild age-related diabetes MARD) were classified using validated self-normalizing neural networks. Severe autoimmune diabetes (SAID) was assessed for NHANES-III. Prevalence was estimated using examination sample weights considering bicyclic changes (BCs) to evaluate trends and changes over time.
Diabetes prevalence in the United States increased from 7.5% (95% CI 7.1-7.9) in 1988-1989 to 13.9% (95% CI 13.4-14.4) in 2016-2018 (BC 1.09%, 95% CI 0.98-1.31, P < .001). Non-Hispanic Black people had the highest prevalence. Overall, MOD, MARD, and SIDD had an increase during the studied period. Particularly, non-Hispanic Black people had sharp increases in MARD and SIDD, Mexican Americans in SIDD, and non-Hispanic White people in MARD. Males, subjects with secondary/high school, and adults aged 40-64 years had the highest increase in MOD prevalence. Trends in diabetes subgroups sustained after stratifying time since diabetes diagnosis.
Prevalence of diabetes and its subgroups in the United States has increased from 1988 to 2018. These trends were different across sex, ethnicities, education, and age categories, indicating significant heterogeneity in diabetes within the US obesity burden, population aging, socioeconomic disparities, and lifestyle aspects could be implicated in the increasing trends of diabetes in the United States.
Abstract Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. NAFLD is strongly associated with obesity and metabolic syndrome (MetS). Current ...treatment of NAFLD is based on weight reduction. Bariatric surgery is the most effective treatment for morbid obesity and its associated metabolic comorbidities. There is evidence indicating that bariatric surgery improves histological and biochemical parameters of NAFLD, but currently is not considered a treatment option for NAFLD. The aim of this work is to review the evidence for the effects of bariatric surgery on NAFLD and the MetS. We found that insulin resistance, alterations in glucose metabolism, hypertension, plasma lipids, transaminases, liver steatosis, steatohepatitis and fibrosis improve after bariatric surgery. Weight loss and improvement of NAFLD are greater after RYGB than after other interventions. These findings were obtained from retrospective or cohort studies. There are no studies designed to evaluate liver-specific mortality, liver transplantation, or quality of life. Patients with indications for bariatric surgery will benefit from the improvements in the MetS and NAFLD.
Interest has been focused on differentiating anatomical, molecular, and physiological characteristics of the types of mammalian adipose tissues. White adipose tissue (WAT) and brown adipose tissue ...(BAT) are the two main forms of adipose tissue in humans. WAT functions as an endocrine organ and serves as a reservoir of energy in the form of triglycerides. The hormones released by WAT are called adipokines. BAT consists of a group of specialized cells with abundant uncoupling protein 1 (UCP1) in the inner mitochondrial membrane and also fulfills endocrine functions. Following the identification of functional (BAT) in human adults, there has been a great deal of interest in finding out how it is induced, its localization, and the mechanisms by which it regulates thermogenesis. Fibroblast growth factor 21 (FGF21) is a key regulator of the differentiation to brown adipocytes. The main mechanisms occur through enhancing UCP1 expression. In addition, following exposure to cold or exercise, FGF21 induces upregulation of local peroxisome proliferator-activated receptor gamma co-activator (PGC)-1-alfa and thus promotes thermogenesis in adipose tissue and skeletal muscle. FGF21 integrates several pathways allowing the regulation of human energy balance, glucose levels, and lipid metabolism. Such mechanisms and their clinical relevance are summarized in this review.
The effects of non-nutritive sweeteners (NNS) on glucose metabolism and appetite regulating hormones are not clear. There is an ongoing debate concerning NNS use and deleterious changes in ...metabolism.
The aim of this review is to analyze the scientific available evidence regarding the effects of NNS on glucose metabolism and appetite regulating hormones.
We identified human observational studies evaluating the relation between NNS consumption and obesity, diabetes, and metabolic syndrome, in addition to clinical trials evaluating the effects of NNS in glucose metabolism and appetite regulating hormones.
Fourteen observational studies evaluating the association between NNS consumption and the development of metabolic diseases and twenty-eight clinical trials studying the effects of NNS on metabolism were included. Finally, two meta-analyses evaluating the association between the consumption of NNS-containing beverages and the development of type 2 diabetes were identified.
Some observational studies suggest an association between NNS consumption and development of metabolic diseases; however, adiposity is a confounder frequently found in observational studies. The effects of the NNS on glucose metabolism are not clear. The results of the identified clinical trials are contradictory and are not comparable because of the major existing differences between them. Studies evaluating specific NNS, with an adequate sample size, including a homogeneous study group, identifying significant comorbidities, with an appropriate control group, with an appropriate exposure time, and considering adjustment for confounder variables such as adiposity are needed.
Background
Little is known about the achievement of low density lipoprotein cholesterol (LDL-C) targets in patients at cardiovascular risk receiving stable lipid-lowering therapy (LLT) in countries ...outside Western Europe.
Methods
This cross-sectional observational study was conducted in 452 centres (August 2015−August 2016) in 18 countries in Eastern Europe, Asia, Africa, the Middle East and Latin America. Patients (n = 9049) treated for ≥3 months with any LLT and in whom an LDL-C measurement on stable LLT was available within the previous 12 months were included.
Results
The mean±SD age was 60.2 ± 11.7 years, 55.0% of patients were men and the mean ± SD LDL-C value on LLT was 2.6 ± 1.3 mmol/L (101.0 ± 49.2 mg/dL). At enrolment, 97.9% of patients were receiving a statin (25.3% on high intensity treatment). Only 32.1% of the very high risk patients versus 51.9% of the high risk and 55.7% of the moderate risk patients achieved their LDL-C goals. On multivariable analysis, factors independently associated with not achieving LDL-C goals were no (versus lower dose) statin therapy, a higher (versus lower) dose of statin, statin intolerance, overweight and obesity, female sex, neurocognitive disorders, level of cardiovascular risk, LDL-C value unknown at diagnosis, high blood pressure and current smoking. Diabetes was associated with a lower risk of not achieving LDL-C goals.
Conclusions
These observational data suggest that the achievement of LDL-C goals is suboptimal in selected countries outside Western Europe. Efforts are needed to improve the management of patients using combination therapy and/or more intensive LLTs.
During the COVID-19 pandemic, risk stratification has been used to decide patient eligibility for inpatient, critical and domiciliary care. Here, we sought to validate the MSL-COVID-19 score, ...originally developed to predict COVID-19 mortality in Mexicans. Also, an adaptation of the formula is proposed for the prediction of COVID-19 severity in a triage setting (Nutri-CoV).
We included patients evaluated from March 16th to August 17th, 2020 at the Instituto Nacional de Ciencias Médicas y Nutrición, defining severe COVID-19 as a composite of death, ICU admission or requirement for intubation (n = 3,007). We validated MSL-COVID-19 for prediction of mortality and severe disease. Using Elastic Net Cox regression, we trained (n = 1,831) and validated (n = 1,176) a model for prediction of severe COVID-19 using MSL-COVID-19 along with clinical assessments obtained at a triage setting.
The variables included in MSL-COVID-19 are: pneumonia, early onset type 2 diabetes, age > 65 years, chronic kidney disease, any form of immunosuppression, COPD, obesity, diabetes, and age <40 years. MSL-COVID-19 had good performance to predict COVID-19 mortality (c-statistic = 0.722, 95%CI 0.690-0.753) and severity (c-statistic = 0.777, 95%CI 0.753-0.801). The Nutri-CoV score includes the MSL-COVID-19 plus respiratory rate, and pulse oximetry. This tool had better performance in both training (c-statistic = 0.797, 95%CI 0.765-0.826) and validation cohorts (c-statistic = 0.772, 95%CI 0.0.745-0.800) compared to other severity scores.
MSL-COVID-19 predicts inpatient COVID-19 lethality. The Nutri-CoV score is an adaptation of MSL-COVID-19 to be used in a triage environment. Both scores have been deployed as web-based tools for clinical use in a triage setting.
Abstract
Recent advances in human genetics, together with a large body of epidemiologic, preclinical, and clinical trial results, provide strong support for a causal association between triglycerides ...(TG), TG-rich lipoproteins (TRL), and TRL remnants, and increased risk of myocardial infarction, ischaemic stroke, and aortic valve stenosis. These data also indicate that TRL and their remnants may contribute significantly to residual cardiovascular risk in patients on optimized low-density lipoprotein (LDL)-lowering therapy. This statement critically appraises current understanding of the structure, function, and metabolism of TRL, and their pathophysiological role in atherosclerotic cardiovascular disease (ASCVD). Key points are (i) a working definition of normo- and hypertriglyceridaemic states and their relation to risk of ASCVD, (ii) a conceptual framework for the generation of remnants due to dysregulation of TRL production, lipolysis, and remodelling, as well as clearance of remnant lipoproteins from the circulation, (iii) the pleiotropic proatherogenic actions of TRL and remnants at the arterial wall, (iv) challenges in defining, quantitating, and assessing the atherogenic properties of remnant particles, and (v) exploration of the relative atherogenicity of TRL and remnants compared to LDL. Assessment of these issues provides a foundation for evaluating approaches to effectively reduce levels of TRL and remnants by targeting either production, lipolysis, or hepatic clearance, or a combination of these mechanisms. This consensus statement updates current understanding in an integrated manner, thereby providing a platform for new therapeutic paradigms targeting TRL and their remnants, with the aim of reducing the risk of ASCVD.
Graphical Abstract
Formation of triglyceride-rich lipoprotein remnants and their role in atherogenesis. Metabolic scheme for the generation and clearance of triglyceride-rich lipoprotein remnant particles (A). In hypertriglyceridaemia, overproduction and inefficient lipolysis of both very low-density lipoprotein and chylomicrons lead to increased remnant formation. Triglyceride-rich lipoprotein remnants contribute to the initiation and progression of atherosclerotic lesions (B). Particle retention in the subendothelial space is followed by inflammation, cholesterol deposition, and macrophage foam cell formation.
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