Autonomic dysfunction, diabetes and metabolic syndrome

The associations among glycemic control, heart variability, and autonomic brain function in healthy individuals: Age- and sex-related differences

INTRODUCTION

The purpose of this study was to clarify the relationships between glycemia and function of the autonomic nervous system (ANS), assessed via resting-state functional connectivity (FC) and heart-rate variability (HRV).

METHODS

Data for this study were extracted from the Leipzig Study for Mind-Body-Emotion Interactions, including 146 healthy adults (114 young, 32 older). Variables of interest were glycated hemoglobin (HbA1c), resting-state FC in the salience aspect of the central-autonomic (S-CAN) and salience network (SN) and HRV (RMSSD and high-frequency HRV (HF-HRV)).

RESULTS

HbA1c was inversely correlated with FC in the S-CAN but not SN. HbA1c was inversely correlated with HRV. Both RMSSD and log(HF-HRV) were correlated with FC in the S-CAN and SN. Age- (not sex-related) differences were observed in the Hb1Ac-FC associations (stronger in older adults) while sex- (not age-related) differences were observed in the HRV-FC (stronger in females).

CONCLUSIONS

These findings extend the diabetes literature to healthy adults in relating glycemia and brain function. The age- and sex-related differences in these relationships highlight the need to account for the potential effects of age and sex in future investigations.

Longitudinal economic burden of incident complications among metabolic syndrome populations

BACKGROUND

This study quantifies the longitudinal economic burden for a wide spectrum of incident complications, metabolic syndrome (MS)-related risk factors, and comorbidities in patients with MS.

METHODS

This retrospective study utilized linked data from the 2013 National Health Interview Survey and the 2012-2021 National Health Insurance Research Database to identify MS individuals and their characteristics. The incidence rate of each complication was calculated as the number of complication events in the study period divided by the total person-years during follow-up. The healthcare costs of complications were analyzed using a generalized estimating equation model to determine the cost impact of complications after adjustment for patients' characteristics. Sensitivity analyses on variables with high missing rates (i.e., cause of death, body mass index) were performed.

RESULTS

Among 837 identified MS individuals over 8.28 (± 1.35) years of follow-up, the most frequent complications were microvascular diseases (incidence rate for nephropathy/retinopathy/neuropathy: 6.49/2.64/2.08 events per 100 person-years), followed by cardiovascular diseases (2.47), peripheral vascular diseases (2.01), and cancers (1.53). Death was the costliest event (event-year cost per person: USD 16,429) and cancers were the most expensive complications (USD 9,127-11,083 for non-MS- and MS-related cancers). Developing non-MS/MS-related cancers, cardiovascular diseases, and obesity-related medical conditions increased annual costs by 273% (95% CI: 181-397%)/175% (105-269%), 159% (118-207%), and 140% (84-214%), respectively. Microvascular diseases had the lowest cost impact on annual costs (i.e., 27% [17-39%]/27% [11-46%]/24% [11-37%] increases for nephropathy/neuropathy/retinopathy, respectively). Having existing comorbidities increased annual costs by 20% (osteoarthritis) to 108% (depression). Having morbid obesity (i.e., body mass index ≥ 35 kg/m2) increased annual costs by 58% (30-91%).

CONCLUSIONS

The economic burden from costly incident complications (i.e., cardiovascular diseases, peripheral vascular diseases, cancers), MS-related risk factors (i.e., morbid obesity), and comorbidities (i.e., depression) highlight the urgent need for early intervention to prevent MS and its progression. The comprehensive cost estimates reported in this study can facilitate the parameterization of economic analyses to identify cost-effective interventions for these patients.

Modal Analysis of Cerebrovascular Effects for Digital Health Integration of Neurostimulation Therapies-A Review of Technology Concepts

Transcranial electrical stimulation (tES) is increasingly recognized for its potential to modulate cerebral blood flow (CBF) and evoke cerebrovascular reactivity (CVR), which are crucial in conditions like mild cognitive impairment (MCI) and dementia. This study explores the impact of tES on the neurovascular unit (NVU), employing a physiological modeling approach to simulate the vascular response to electric fields generated by tES. Utilizing the FitzHugh-Nagumo model for neuroelectrical activity, we demonstrate how tES can initiate vascular responses such as vasoconstriction followed by delayed vasodilation in cerebral arterioles, potentially modulated by a combination of local metabolic demands and autonomic regulation (pivotal locus coeruleus). Here, four distinct pathways within the NVU were modeled to reflect the complex interplay between synaptic activity, astrocytic influences, perivascular potassium dynamics, and smooth muscle cell responses. Modal analysis revealed characteristic dynamics of these pathways, suggesting that oscillatory tES may finely tune the vascular tone by modulating the stiffness and elasticity of blood vessel walls, possibly by also impacting endothelial glycocalyx function. The findings underscore the therapeutic potential vis-à-vis blood-brain barrier safety of tES in modulating neurovascular coupling and cognitive function needing the precise modulation of NVU dynamics. This technology review supports the human-in-the-loop integration of tES leveraging digital health technologies for the personalized management of cerebral blood flow, offering new avenues for treating vascular cognitive disorders. Future studies should aim to optimize tES parameters using computational modeling and validate these models in clinical settings, enhancing the understanding of tES in neurovascular health.

Comparative Analysis of Biomarkers in Type 2 Diabetes Patients With and Without Comorbidities: Insights Into the Role of Hypertension and Cardiovascular Disease

Background

Type 2 diabetes mellitus (T2DM) are 90% of diabetes cases, and its prevalence and incidence, including comorbidities, are rising worldwide. Clinically, diabetes and associated comorbidities are identified by biochemical and physical characteristics including glycemia, glycated hemoglobin (HbA1c), and tests for cardiovascular, eye and kidney disease.

Objectives

Diabetes may have a common etiology based on inflammation and oxidative stress that may provide additional information about disease progression and treatment options. Thus, identifying high-risk individuals can delay or prevent diabetes and its complications.

Design

In patients with or without hypertension and cardiovascular disease, as part of progression from no diabetes to T2DM, this research studied the changes in biomarkers between control and prediabetes, prediabetes to T2DM, and control to T2DM, and classified patients based on first-attendance data. Control patients and patients with hypertension, cardiovascular, and with both hypertension and cardiovascular diseases are 156, 148, 61, and 216, respectively.

Methods

Linear discriminant analysis is used for classification method and feature importance, This study examined the relationship between Humanin and mitochondrial protein (MOTSc), mitochondrial peptides associated with oxidative stress, diabetes progression, and associated complications.

Results

MOTSc, reduced glutathione and glutathione disulfide ratio (GSH/GSSG), interleukin-1β (IL-1β), and 8-isoprostane were significant (P < .05) for the transition from prediabetes to t2dm, highlighting importance of mitochondrial involvement. complement component 5a (c5a) is a biomarker associated with disease progression and comorbidities, gsh gssg, monocyte chemoattractant protein-1 (mcp-1), 8-isoprostane being most important biomarkers.

Conclusions

Comorbidities affect the hypothesized biomarkers as diabetes progresses. Mitochondrial oxidative stress indicators, coagulation, and inflammatory markers help assess diabetes disease development and provide appropriate medications. Future studies will examine longitudinal biomarker evolution.

Sympathetic Overactivity and Parasympathetic Impairment in Type 2 Diabetes: An Analysis of Cardiovascular Autonomic Functions

Background Cardiovascular autonomic dysregulation is a known complication of Type 2 diabetes mellitus (T2DM), characterized by dysregulation in heart rate (HR) and blood pressure (BP). These disruptions in cardiovascular autonomic control can significantly influence the morbidity and mortality associated with the disease. Objectives This study aims to investigate how T2DM affects cardiovascular autonomic functions by comparing responses in HR, BP, and specific autonomic function tests between a control group without diabetes and a study group with diabetes. The research questions focus on assessing HR variability, baroreflex sensitivity, and other autonomic parameters to determine the extent of cardiovascular autonomic dysregulation in diabetic patients.  Methods This cross-sectional study involved 200 adults, divided equally between a control group (n = 100) and a T2DM study group (n = 100). The exclusion criteria included cardiovascular diseases and renal impairment. Data collection involved assessing baseline characteristics such as age and BMI. Cardiovascular measures, including HR, systolic blood pressure (SBP), and diastolic blood pressure (DBP), were recorded after a five-minute rest. Autonomic function tests assessed sympathetic and parasympathetic responses, including the cold pressor test and the isometric hand grip exercise test. The statistical analysis was conducted using IBM SPSS Statistics for Windows, Version 25 (Released 2017; IBM Corp., Armonk, New York, United States), focusing on independent t-tests to compare between groups, considering p-values <0.05 as significant. Potential confounding variables like age and BMI were accounted for in the analysis to ensure robust findings  Results The study group showed a higher average BMI (28.95 ± 5.60) compared to the control group (26.50 ± 5.70) and an increased resting HR (74.20 ± 8.60 bpm vs. 69.30 ± 9.10 bpm). The SBP was slightly higher in the study group (115.00 ± 19.00 mmHg vs. 114.50 ± 8.90 mmHg), while the DBP was lower (71.50 ± 10.70 mmHg vs. 72.80 ± 6.70 mmHg). The autonomic function tests showed a smaller increase in SBP (106.80 ± 11.00 mmHg) and a larger increase in DBP (75.90 ± 8.30 mmHg) upon standing in the study group compared to controls. The cold pressor test indicated increased sympathetic activity in the study group, with significant rises in SBP (133.70 ± 10.30 mmHg) and DBP (83.40 ± 9.00 mmHg) compared to the control group (SBP: 114.31 ± 11.87 mmHg, DBP: 71.85 ± 8.67 mmHg). These findings demonstrate marked differences in cardiovascular autonomic responses between the groups. Conclusions This study demonstrates that T2DM significantly impacts cardiovascular autonomic functions, with diabetic patients showing altered HR and BP indicative of increased sympathetic and decreased parasympathetic activity. These autonomic dysfunctions may heighten cardiovascular risk in diabetic individuals. Our findings highlight the importance of monitoring and managing cardiovascular autonomic functions in diabetic patients to reduce their risk of cardiovascular complications. Further research should investigate the underlying mechanisms and the effectiveness of interventions to improve autonomic function in this population.

Metabolic Dysregulation and Its Multifaceted Impact on Cardiovascular Autonomic Control in Type 2 Diabetes Mellitus: Insights From Comprehensive Assessment

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with a spectrum of metabolic dysfunctions that significantly elevate the risk of cardiovascular disorders. Understanding the intricate relationship between metabolic control and cardiovascular autonomic function in individuals with T2DM is crucial for effective management and the prevention of associated complications. This insight is foundational in developing targeted strategies that can mitigate the heightened cardiovascular risks inherent to this condition, thereby enhancing patient outcomes and quality of life.

AIM

The primary aim of the study was to explore the interconnections between various aspects of metabolic control in individuals with T2DM. This includes examining how glycemic variability, lipid profiles, body mass index (BMI), duration of diabetes, inflammatory markers, and cardiovascular autonomic function are interrelated.

METHODS

A cross-sectional study was conducted involving 100 individuals with T2DM and 100 control participants. HbA1C levels, glycemic variability, lipid profile, BMI, duration of diabetes, and inflammatory markers were assessed. Cardiovascular autonomic function parameters, including resting heart rate and blood pressure responses, were evaluated using standardized tests.

RESULTS

People with T2DM had significantly higher levels of glycosylated hemoglobin (HbA1C) compared to controls (mean difference = 2.95%, p < 0.001). Elevated HbA1C levels were correlated with increased resting heart rate (mean difference = 10 bpm, p < 0.001) and aberrant blood pressure responses during autonomic function assessments (p < 0.01 for systolic blood pressure; p < 0.05 for diastolic blood pressure). Glycemic variability (correlation coefficient (𝑟) = 0.75, p < 0.001) and dyslipidemia (elevated triglycerides and LDL cholesterol, reduced HDL cholesterol) were associated with cardiovascular autonomic dysfunction. Higher BMI values in T2DM individuals were independently correlated with alterations in autonomic function (𝑟 = 0.60, p < 0.001). The prolonged duration of diabetes was linked to greater impairment in autonomic function (mean decrease = 0.5 points per year, p < 0.01). In the T2DM group, higher levels of inflammatory markers (C-reactive protein and interleukin-6) were seen, which may have led to problems with the autonomic nervous system.

CONCLUSION

Metabolic dysregulation, such as high HbA1C levels, glycemic variability, dyslipidemia, obesity, having diabetes for a long time, and inflammation, is linked to cardiovascular autonomic dysfunction in T2DM. Early intervention targeting these metabolic abnormalities may mitigate the risk of cardiovascular complications in individuals with T2DM.

The Role of Pro-Opiomelanocortin Derivatives in the Development of Type 2 Diabetes-Associated Myocardial Infarction: Possible Links with Prediabetes

Myocardial infarction is a major contributor to CVD-related mortality. T2DM is a risk factor for MI. Stress activates the HPA axis, SNS, and endogenous OPS. These POMC derivatives increase the blood glucose and cardiovascular response by inhibiting the PI3K/AkT insulin signaling pathway and increasing cardiac contraction. Opioids regulate the effect of the HPA axis and SNS and they are cardioprotective. The chronic activation of the stress response may lead to insulin resistance, cardiac dysfunction, and MI. Stress and T2DM, therefore, increase the risk of MI. T2DM is preceded by prediabetes. Studies have shown that prediabetes is associated with an increased risk of MI because of inflammation, hyperlipidemia, endothelial dysfunction, and hypertension. The HPA axis is reported to be dysregulated in prediabetes. However, the SNS and the OPS have not been explored during prediabetes. The effect of prediabetes on POMC derivatives has yet to be fully explored and understood. The impact of stress and prediabetes on the cardiovascular response needs to be investigated. This study sought to review the potential impact of prediabetes on the POMC derivatives and pathways that could lead to MI.

Autonomic modulation and the risk of dementia in a middle-aged cohort: A 17-year follow-up study

BACKGROUND

Altered autonomic modulation, measured by heart rate variability (HRV), has been found to be associated with dementia risk in the elderly. However, long-term follow-up study evaluating the association between autonomic modulation from middle-age and the incidence of dementia has been limited.

METHODS

This retrospective cohort analyzed data from Taiwan's National Health Insurance Database covering the period from 2001 to 2017, with a linkage to citywide health examinations conducted by Tainan Metropolitan City, Taiwan. We included subjects aged 45-64 years. The mean follow-up period was 15.75 ± 3.40 years. The measurements of HRV included resting heart rate, high frequency (HF), low frequency (LF), standard deviation of normal-to-normal R-R intervals (SDNN), ratio between the 30th and 15th R-R interval after standing up from the supine position (30/15 ratio), ratio between the R-R intervals during expiration and inspiration, and the ratio between the high- and low-frequency components (LF/HF). The main study outcome was the incidence of dementia. We performed multivariable Cox proportional hazard regression models to compare the risk of dementia among different HRV subgroups.

RESULTS

We included 565 participants with a mean age of 53 (SD: 6) years, of whom 44% were male. The risk of dementia was significantly increased in association with lower parasympathetic HRV modulation, including SDNN (HR: 3.23, 95% CI: 1.55-6.73) and 30/15 ratio (HR: 3.52, 95%CI: 1.67-7.42). Moreover, the risk of dementia was increased in subjects with higher LF/HF ratios (HR: 2.05, 95% CI: 1.12-3.72).

CONCLUSIONS

Lower parasympathetic activity and higher sympathetic-vagal imbalance in middle-age were associated with dementia risk.

A High intensity Interval training (running and swimming) and resistance training intervention on heart rate variability and the selected biochemical factors in boys with type 1 diabetes

OBJECTIVE

The purpose of this research is to investigate the effect of High Intensity Interval Training and Resistance training (HIITR) on heart rate variability (HRV), blood glucose, and plasma biomarkers levels in adolescents with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

24 boys with T1D (FBS: 274.66 ± 52.99, age: 15.2 ± 1.78 years, and BMI = 19.61 ± 1.11) and 12 healthy boys (FBS: 92.75 ± 5.22, age: 15.08 ± 1.67 years, and BMI = 20.26 ± 2.66) were divided into three groups: Diabetes Training (DT, n = 12), Diabetes Control (DC, n = 12), and Healthy Control (HC, n = 12). HRV (24 h) was computed in time and frequency domains, anthropometric, biochemical parameters at rest, and aerobic capacity (VO2peak) obtained during a graded exercise testing (GXT). All variables were evaluated at the baseline and following 12 weeks of exercise training, done 3 days weekly. The statistical method used for data analysis was analysis of covariance (ANCOVA) test.

RESULTS

HRV, Hemoglobin A1c (HbA1c) and Fasting blood sugar (FBS), VO2peak, norepinephrine (NEP), and HDL-C indicated significant differences between both T1D groups compared to HC at baseline (p < 0.001). BMI, LDL-C, TC, and TG parameters were similar in all groups. HRV parameters, VO2peak and HDL-C, and NEP were significantly improved by exercise training, and HbA1c and FBS levels were significantly reduced (p < 0.001). There is a negative and significant correlation between LF/HF Ratio Difference (post-test minus pre-test) and VO2Peak Difference variables (post-test minus pre-test) (p < 0.001).

CONCLUSIONS

The present study suggests the importance of early screening for CVD risk factors in adolescent males with T1D. Also, it was revealed HIITR training compared to other training patterns, and cardiovascular health improves via enhancement of autonomic modulation, VO2peak, plasma lipids, and catecholamine levels.

Short-Term Heart Rate Variability in Metabolic Syndrome: A Systematic Review and Meta-Analysis

BACKGROUND

Our aim was to determine the differences in short-term heart rate variability (HRV) between patients with metabolic syndrome (MS) and healthy controls.

METHODS

We searched electronic databases for primary works with short-term HRV recordings (≤30 min) that made comparisons between individuals with MS versus healthy controls. This systematic review and meta-analysis (MA) was performed according to PRISMA guidelines and registered at PROSPERO (CRD42022358975).

RESULTS

Twenty-eight articles were included in the qualitative synthesis and nineteen met the criteria for the MA. Patients with MS showed decreased SDNN (-0.36 [-0.44, -0.28], p < 0.001), rMSSD (-7.59 [-9.98, -5.19], p < 0.001), HF (-0.36 [-0.51, -0.20], p < 0.00001) and LF (-0.24 [-0.38, -0.1], p = 0.001). In subsequent subanalyses, we found a decrease in SDNN (-0.99 (-1.45, -0.52], p < 0.001), rMSSD (-10.18 [-16.85, -3.52], p < 0.01) and HF (-1.04 [-1.97, -0.1] p < 0.05) in women. In men, only LF showed a significant lower value (-0.26 [-0.5, -0.02], p < 0.05). We could not perform MA for non-linear variables.

CONCLUSIONS

Patients with MS showed changes in time-domain analyses, with lower values in SDNN and rMSSD. Regarding frequency-domain analyses, MS patients showed a decrease in HF and LF When sex was used as a grouping variable, the MA was only possible in one of both sexes (men or women) in rMSSD and LF/HF. Lastly, when data for both men and women were available, subanalyses showed a different behavior compared to mixed analyses for SDNN, HF and LF, which might point towards a different impact of MS in men and women.

Combining Celiac and Hepatic Vagus Nerve Neuromodulation Reverses Glucose Intolerance and Improves Glycemic Control in Pre- and Overt-Type 2 Diabetes Mellitus

Neurological disorders and type 2 diabetes mellitus (T2DM) are deeply intertwined. For example, autonomic neuropathy contributes to the development of T2DM and continued unmanaged T2DM causes further progression of nerve damage. Increasing glycemic control has been shown to prevent the onset and progression of diabetic autonomic neuropathies. Neuromodulation consisting of combined stimulation of celiac vagal fibers innervating the pancreas with concurrent electrical blockade of neuronal hepatic vagal fibers innervating the liver has been shown to increase glycemic control in animal models of T2DM. The present study demonstrated that the neuromodulation reversed glucose intolerance in alloxan-treated swine in both pre- and overt stages of T2DM. This was demonstrated by improved performance on oral glucose tolerance tests (OGTTs), as assessed by area under the curve (AUC). In prediabetic swine (fasting plasma glucose (FPG) range: 101-119 mg/dL) the median AUC decreased from 31.9 AUs (IQR = 28.6, 35.5) to 15.9 AUs (IQR = 15.1, 18.3) p = 0.004. In diabetic swine (FPG range: 133-207 mg/dL) the median AUC decreased from 54.2 AUs (IQR = 41.5, 56.6) to 16.0 AUs (IQR = 15.4, 21.5) p = 0.003. This neuromodulation technique may offer a new treatment for T2DM and reverse glycemic dysregulation at multiple states of T2DM involved in diabetic neuropathy including at its development and during progression.

Fecal Microbiota Composition, Their Interactions, and Metagenome Function in US Adults with Type 2 Diabetes According to Enterotypes

T2DM etiology differs among Asians and Caucasians and may be associated with gut microbiota influenced by different diet patterns. However, the association between fecal bacterial composition, enterotypes, and T2DM susceptibility remained controversial. We investigated the fecal bacterial composition, co-abundance network, and metagenome function in US adults with T2DM compared to healthy adults based on enterotypes. We analyzed 1911 fecal bacterial files of 1039 T2DM and 872 healthy US adults from the Human Microbiome Projects. Operational taxonomic units were obtained after filtering and cleaning the files using Qiime2 tools. Machine learning and network analysis identified primary bacteria and their interactions influencing T2DM incidence, clustered into enterotypes, Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Prevotellaceae (ET-P). ET-B showed higher T2DM incidence. Alpha-diversity was significantly lower in T2DM in ET-L and ET-P (p < 0.0001), but not in ET-B. Beta-diversity revealed a distinct separation between T2DM and healthy groups across all enterotypes (p < 0.0001). The XGBoost model exhibited high accuracy and sensitivity. Enterocloster bolteae, Facalicatena fissicatena, Clostridium symbiosum, and Facalibacterium prausnitizii were more abundant in the T2DM group than in the healthy group. Bacteroides koreensis, Oscillibacter ruminantium, Bacteroides uniformis, and Blautia wexlerae were lower in the T2DM than in the healthy group regardless of the enterotypes in the XGBoost model (p < 0.0001). However, the patterns of microbial interactions varied among different enterotypes affecting T2DM risk. The interaction between fecal bacteria was more tightly regulated in the ET-L than in the ET-B and ET-P groups (p < 0.001). Metagenomic analysis revealed an inverse association between bacteria abundance in T2DM, energy utility, butanoate and propanoate metabolism, and the insulin signaling pathway (p < 0.0001). In conclusion, fecal bacteria play a role in T2DM pathogenesis, particularly within different enterotypes, providing valuable insights into the link between gut microbiota and T2DM in the US population.

Differences in Long-Term Heart Rate Variability between Subjects with and without Metabolic Syndrome: A Systematic Review and Meta-Analysis

BACKGROUND

Our aim was to determine the impact that metabolic syndrome (MS) produces in long-term heart rate variability (HRV), quantitatively synthesizing the results of published studies to characterize the cardiac autonomic dysfunction in MS.

METHODS

We searched electronic databases for original research works with long-term HRV recordings (24 h) that compared people with MS (MS+) versus healthy people as a control group (MS-). This systematic review and meta-analysis (MA) was performed according to PRISMA guidelines and registered at PROSPERO (CRD42022358975).

RESULTS

A total of 13 articles were included in the qualitative synthesis, and 7 of them met the required criteria to be included in the MA. SDNN (-0.33 [-0.57, 0.09], p = 0.008), LF (-0.32 [-0.41, -0.23], p < 0.00001), VLF (-0.21 [-0.31, -0.10], p = 0.0001) and TP (-0.20 [-0.33, -0.07], p = 0.002) decreased in patients with MS. The rMSSD (p = 0.41), HF (p = 0.06) and LF/HF ratio (p = 0.64) were not modified.

CONCLUSIONS

In long-term recordings (24 h), SDNN, LF, VLF and TP were consistently decreased in patients with MS. Other parameters that could be included in the quantitative analysis were not modified in MS+ patients (rMSSD, HF, ratio LF/HF). Regarding non-linear analyses, the results are not conclusive due to the low number of datasets found, which prevented us from conducting an MA.

Wavelet analysis of laser Doppler microcirculatory signals: Current applications and limitations

Laser Doppler flowmetry (LDF) has long been considered a gold standard for non-invasive assessment of skin microvascular function. Due to the laser Doppler (LD) microcirculatory signal's complex biological and physiological context, using spectral analysis is advisable to extract as many of the signal's properties as feasible. Spectral analysis can be performed using either a classical Fourier transform (FT) technique, which has the disadvantage of not being able to localize a signal in time, or wavelet analysis (WA), which provides both the time and frequency localization of the inspected signal. So far, WA of LD microcirculatory signals has revealed five characteristic frequency intervals, ranging from 0.005 to 2 Hz, each of which being related to a specific physiological influence modulating skin microcirculatory response, providing for a more thorough analysis of the signals measured in healthy and diseased individuals. Even though WA is a valuable tool for analyzing and evaluating LDF-measured microcirculatory signals, limitations remain, resulting in a lack of analytical standardization. As a more accurate assessment of human skin microcirculation may better enhance the prognosis of diseases marked by microvascular dysfunction, searching for improvements to the WA method is crucial from the clinical point of view. Accordingly, we have summarized and discussed WA application and its limitations when evaluating LD microcirculatory signals, and presented insight into possible future improvements. We adopted a novel strategy when presenting the findings of recent studies using WA by focusing on frequency intervals to contrast the findings of the various studies undertaken thus far and highlight their disparities.

Waist Circumference Is an Essential Factor in Predicting Insulin Resistance and Early Detection of Metabolic Syndrome in Adults

BACKGROUND

Metabolic syndrome (Met-S) is considered one of the most important health problems of the 21st century. It includes a group of metabolic disorders that increase the risk of cardiovascular diseases such as overweight and obesity, elevated lipid profile and blood pressure and insulin resistance (IR). Based on the information mentioned above in which there seems to be a relationship between IR and Met-S, the objective of this work was twofold: on the one hand, to assess the relationship between the values of different insulin resistance risk scales and Met-S determined with three different scales, and on the other, to determine whether any of the components of Met-S predispose more to the appearance of IR.

METHODS

A descriptive cross-sectional study of 418,343 workers. Waist circumference was measured and evaluated together with six formulas to assess the insulin resistance index. Categorical variables were evaluated by calculating the frequency and distribution of each one. For quantitative variables, mean and standard deviation were determined, and Student's t-test was applied, while for qualitative variables, the chi-square test was performed. The usefulness of the different risk scales for insulin resistance for predicting metabolic syndrome was evaluated using ROC curves, the area under the curve (AUC), as well as their cut-off points for sensitivity, specificity, and the Youden index.

RESULTS

People with metabolic syndrome applying any criteria had higher values in the IR risk scales. The different IR scales made it possible to adequately classify people with metabolic syndrome. Of the three definitions of Met-S, the one that showed the greatest relationship with IR was IDF.

CONCLUSIONS

Most risk scales for insulin resistance enable the presence of metabolic syndrome to be adequately classified, finding the best ones if the International Diabetes Federation (IDF) criteria are applied. Of the elements included in the Met-S, the one that seems to increase the risk of presenting IR the most is waist circumference; hence, the Met-S definition that is most related to IR is that of the IDF, which is the only one of the three in which a high value of waist circumference is necessary to be able to diagnose Met-S. Waist circumference can be considered the central essential component for detecting insulin resistance and, therefore, the early detection of metabolic syndrome.

Early atrial remodeling predicts the risk of cardiovascular events in patients with metabolic syndrome: a retrospective cohort study

Background

This study aims to assess the prevalence of atrial cardiomyopathy (ACM) in patients with new-onset metabolic syndrome (MetS) and investigate whether ACM could be a predictor of hospital admission for cardiovascular (CV) events.

Methods

Patients with MetS who were free of clinically proven atrial fibrillation and other CV diseases (CVDs) at baseline were included in the present study. The prevalence of ACM was compared between MetS patients with and without left ventricular hypertrophy (LVH). The time to first hospital admission for a CV event between subgroups was assessed using the Cox proportional hazard model.

Results

A total of 15,528 MetS patients were included in the final analysis. Overall, LVH patients accounted for 25.6% of all newly diagnosed MetS patients. ACM occurred in 52.9% of the cohort and involved 74.8% of LVH patients. Interestingly, a significant percentage of ACM patients (45.4%) experienced MetS without LVH. After 33.2 ± 20.6 months of follow-up, 7,468 (48.1%) patients had a history of readmission due to CV events. Multivariable Cox regression analysis revealed that ACM was associated with an increased risk of admission for CVDs in the MetS patients with LVH [hazard ratio (HR), 1.29; 95% confidence interval (CI), 1.142-1.458; P < 0.001]. Likewise, ACM was found to be independently associated with hospital readmission due to CVD-related events in MetS patients without LVH (HR, 1.175; 95% CI, 1.105-1.250; P < 0.001).

Conclusion

ACM is a marker of early myocardial remodeling and predicts hospitalization for CV events in patients with MetS.

Clinical trials on the pharmacological treatment of long COVID: A systematic review

The postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC), also known as post-acute coronavirus disease 19 (COVID-19) or the long COVID syndrome (long COVID) is an emerging public health concern. A substantial proportion of individuals may remain symptomatic months after initial recovery. An updated review of published and ongoing trials focusing on managing long COVID will help identify gaps and address the unmet needs of patients suffering from this potentially debilitating syndrome. A comprehensive literature search was conducted on the international databases and clinical trial registries from inception to 31 July 2022. This review included 6 published trials and 54 trial registration records. There is significant heterogeneity in the characterization of long COVID and ascertainment of primary outcomes. Most of the trials are focused on individual symptoms of long COVID or isolated organ dysfunction, classified according to cardiovascular, respiratory and functional capacity, neurological and psychological, fatigue, and olfactory dysfunction. Most of the interventions are related to the mechanisms causing the individual symptoms. Although the six published trials showed significant improvement in the symptoms or organ dysfunction studied, these initial studies lack internal and external validity limiting the generalizability. This review provides an update of the pharmacological agents that could be used to treat long COVID. Further standardization of the diagnostic criteria, inclusion of participants with concomitant chronic cardiometabolic diseases and standardization of outcomes will be essential in future clinical trials.

Non-alcoholic fatty liver disease (NAFLD) and mental illness: Mechanisms linking mood, metabolism and medicines

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in the world and one of the leading indications for liver transplantation. It is one of the many manifestations of insulin resistance and metabolic syndrome as well as an independent risk factor for cardiovascular disease. There is growing evidence linking the incidence of NAFLD with psychiatric illnesses such as schizophrenia, bipolar disorder and depression mechanistically via genetic, metabolic, inflammatory and environmental factors including smoking and psychiatric medications. Indeed, patients prescribed antipsychotic medications, regardless of diagnosis, have higher incidence of NAFLD than population norms. The mechanistic pharmacology of antipsychotic-associated NAFLD is beginning to emerge. In this review, we aim to discuss the pathophysiology of NAFLD including its risk factors, insulin resistance and systemic inflammation as well as its intersection with psychiatric illnesses.