2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

AIM: The "2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery" provides recommendations to guide clinicians in the perioperative cardiovascular evaluation and management of adult patients undergoing noncardiac surgery. METHODS: A comprehensive literature search was conducted from August 2022 to March 2023 to identify clinical studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE: Recommendations from the "2014 ACC/AHA Guideline on Perioperative Cardiovascular Evaluation and Management of Patients Undergoing Noncardiac Surgery" have been updated with new evidence consolidated to guide clinicians; clinicians should be advised this guideline supersedes the previously published 2014 guideline. In addition, evidence-based management strategies, including pharmacological therapies, perioperative monitoring, and devices, for cardiovascular disease and associated medical conditions, have been developed.

2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

AIM: The "2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery" provides recommendations to guide clinicians in the perioperative cardiovascular evaluation and management of adult patients undergoing noncardiac surgery. METHODS: A comprehensive literature search was conducted from August 2022 to March 2023 to identify clinical studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE: Recommendations from the "2014 ACC/AHA Guideline on Perioperative Cardiovascular Evaluation and Management of Patients Undergoing Noncardiac Surgery" have been updated with new evidence consolidated to guide clinicians; clinicians should be advised this guideline supersedes the previously published 2014 guideline. In addition, evidence-based management strategies, including pharmacological therapies, perioperative monitoring, and devices, for cardiovascular disease and associated medical conditions, have been developed.

Predictive Performance of Cardiovascular Risk Scores in Cancer Survivors From the UK Biobank.

Background: Cardiovascular preventive strategies are guided by risk scores with unknown validity in cancer cohorts. Objectives: This study aimed to evaluate the predictive performance of 7 established cardiovascular risk scores in cancer survivors from the UK Biobank. Methods: The predictive performance of QRISK3, Systematic Coronary Risk Evaluation 2 (SCORE2)/Systematic Coronary Risk Evaluation for Older Persons (SCORE-OP), Framingham Risk Score, Pooled Cohort equations to Prevent Heart Failure (PCP-HF), CHARGE-AF, QStroke, and CHA2DS2-VASc was calculated in participants with and without a history of cancer. Participants were propensity matched on age, sex, deprivation, health behaviors, family history, and metabolic conditions. Analyses were stratified into any cancer, breast, lung, prostate, brain/central nervous system, hematologic malignancies, Hodgkin lymphoma, and non-Hodgkin lymphoma. Incident cardiovascular events were tracked through health record linkage over 10 years of follow-up. The area under the receiver operating curve, balanced accuracy, and sensitivity were reported. Results: The analysis included 31,534 cancer survivors and 126,136 covariate-matched controls. Risk score distributions were near identical in cases and controls. Participants with any cancer had a significantly higher incidence of all cardiovascular outcomes than matched controls. Performance metrics were significantly worse for all risk scores in cancer cases than in matched controls. The most notable differences were among participants with a history of hematologic malignancies who had significantly higher outcome rates and poorer risk score performance than their matched controls. The performance of risk scores for predicting stroke in participants with brain/central nervous system cancer was very poor, with predictive accuracy more than 30% lower than noncancer controls. Conclusions: Existing cardiovascular risk scores have significantly worse predictive accuracy in cancer survivors compared with noncancer comparators, leading to an underestimation of risk in this cohort.

Cardiovascular risk of dementia is associated with brain-behaviour changes in cognitively healthy, middle-aged individuals.

Alzheimer's Disease (AD) neuropathology start decades before clinical manifestations, but whether risk factors are associated with early cognitive and brain changes in midlife remains poorly understood. We examined whether AD risk factors were associated with cognition and functional connectivity (FC) between the Locus Coeruleus (LC) and hippocampus - two key brain structures in AD neuropathology - cross-sectionally and longitudinally in cognitively healthy midlife individuals. Neuropsychological assessments and functional Magnetic Resonance Imaging were obtained at baseline (N=210), and two-years follow-up (N=188). Associations of cognition and FC with apolipoprotein ε4 (APOE ε4) genotype, family history of dementia, and the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) score were investigated. Cross-sectionally, higher CAIDE scores were associated with worse cognition. Menopausal status interacted with the CAIDE risk on cognition. Furthermore, the CAIDE score significantly moderated the relationship between cognition and LC-Hippocampus FC. Longitudinally, the LC-Hippocampus FC decreased significantly over 2 years. These results suggest that cardiovascular risk of dementia is associated with brain-behaviour changes in cognitively healthy, middle-aged individuals.

Urinary Epinephrine Sulfate Can Predict Cardiovascular Risk in Moderate-to-Severe OSA: A Metabolomics-Based Study.

Purpose: There are currently no ideal indicators for predicting the cardiovascular risk of obstructive sleep apnea (OSA). This study aimed to employ urinary metabolomics to detect early cardiovascular risk in patients with moderate-to-severe OSA. Patients and Methods: Male participants who underwent polysomnography from November 2020 to May 2021 were screened. Clinical data, polysomnography data and urine samples were collected. Untargeted metabolomics analyses of urine were performed. Multivariate analyses and receiver operating characteristic (ROC) curve analyses were subsequently performed to identify potential biomarkers. Associations between metabolites and clinical indicators and cardiovascular risk were examined through linear regression analyses with interaction and mediation analyses. Results: Thirty-six male participants were included in the study, comprising 22 males with moderate-to-severe OSA and 14 age-matched controls, with an average age of 39.6 ± 9.2 years. We identified 65 metabolites in the study, involving pathways including pyrimidine, androgen, estrogen, vitamin B6 and sulfate/sulfite metabolism. Among them, epinephrine sulfate was the most significantly altered metabolite. ROC analyses highlighted that epinephrine sulfate had the highest area under the curve (AUC=0.883) for detecting moderate-to-severe OSA. Epinephrine sulfate was statistically correlated with OSA severity, hypoxia-related indicators (apnea-hypopnea index: r=0.685; oxygen desaturation index: r=0.743, p<0.0001), arterial stiffness (arterial augmentation index: r=0.361, p=0.031) and long-term cardiovascular risk (Framingham cardiovascular risk: r=0.375, p=0.024). Linear regression analysis revealed that epinephrine sulfate was significantly associated with an increased in the Framingham risk (ß = 0.004, 95% CI = 0.000-0.009, p = 0.049), with the effect partly mediated by systolic blood pressure (27.6%) and not moderated by other factors. Additionally, it also significantly associated with the increased in the arterial augmentation index (ß = 0.019, 95% CI = 0.000-0.037, p = 0.046), with the effect fully mediated by blood pressure and not moderated by other indices statistically. Conclusion: There are significant metabolic pathway alterations in moderate-to-severe OSA patients. Urinary epinephrine sulfate markedly predicts early cardiovascular risk in OSA patients.

Circulating Metabolite Profiles and Risk of Coronary Heart Disease Among Racially and Geographically Diverse Populations.

BACKGROUND: Metabolomics may reveal novel biomarkers for coronary heart disease (CHD). We aimed to identify circulating metabolites and construct a metabolite risk score (MRS) associated with incident CHD among racially and geographically diverse populations. METHODS: Untargeted metabolomics was conducted using baseline plasma samples from 900 incident CHD cases and 900 age-/sex-/race-matched controls (300 pairs of Black Americans, White Americans, and Chinese adults, respectively), which detected 927 metabolites with known identities among ≥80% of samples. After quality control, 896 case-control pairs remained and were randomly divided into discovery (70%) and validation (30%) sets within each race. In the discovery set, conditional logistic regression and least absolute shrinkage and selection operator over 100 subsamples were applied to identify metabolites robustly associated with CHD risk and construct the MRS. The MRS-CHD association was evaluated using conditional logistic regression and the C-index. Mediation analysis was performed to examine if MRS mediated associations between conventional risk factors and incident CHD. The results from the validation set were presented as the main findings. RESULTS: Twenty-four metabolites selected in ≥90% of subsamples comprised the MRS, which was significantly associated with incident CHD (odds ratio per 1 SD, 2.21 [95% CI, 1.62-3.00] after adjusting for sociodemographics, lifestyles, family history, and metabolic health status). MRS could distinguish incident CHD cases from matched controls (C-index, 0.69 [95% CI, 0.63-0.74]) and improve CHD risk prediction when adding to conventional risk factors (C-index, 0.71 [95% CI, 0.65-0.76] versus 0.67 [95% CI, 0.61-0.73]; P<0.001). The odds ratios and C-index were similar across subgroups defined by race, sex, socioeconomic status, lifestyles, metabolic health, family history, and follow-up duration. The MRS mediated large portions (46.0%-74.2%) of the associations for body mass index, smoking, diabetes, hypertension, and dyslipidemia with incident CHD. CONCLUSIONS: In a diverse study sample, we identified 24 circulating metabolites that, when combined into an MRS, were robustly associated with incident CHD and modestly improved CHD risk prediction beyond conventional risk factors.

Machine Learning-Assisted Analysis of Sublingual Microcirculatory Dysfunction for Early Cardiovascular Risk Evaluation and Cardiovascular-Kidney-Metabolic Syndrome Stage in Patients With Type 2 Diabetes Mellitus.

AIMS: To examine whether sublingual microcirculation can be used as an effective and noninvasive method for assessing cardiovascular, kidney, and metabolic risks in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: This cross-sectional observational study enrolled 186 patients with T2DM. All patients were evaluated using the Framingham General Cardiovascular Risk Score (FGCRS) and cardiovascular-kidney-metabolic (CKM) syndrome stage. Side-stream dark-field microscopy was used for sublingual microcirculation, including total and perfused vessel density (TVD and PVD). Multiple machine-learning prediction models have been developed for CKM risk and stage assessment in T2DM patients. Receiver operating characteristic (ROC) curves were generated to determine cutoff points. RESULTS: Compared to patients with T2DM, diabetic patients with subclinical atherosclerosis (SA) had a greater CV risk, as measured by the FGCRS, accompanied by markedly decreased microcirculation perfusion. Microcirculatory parameters (TVD and PVD), including carotid intima-media thickness (IMT), brachial-ankle pulse wave velocity (ba-PWV), and FGCRS, were closely associated with SA incidence. Microcirculatory parameters, Index (DMSA screen), and cut-off points were used to screen for SA in patients with T2DM. Furthermore, a new set of four factors identified through machine learning showed optimal sensitivity and specificity for detecting CKM risk in patients with T2DM. Decreased microcirculatory perfusion served as a useful early marker for CKM syndrome risk stratification in patients with T2DM without SA. CONCLUSIONS: Sublingual microcirculatory dysfunction is closely correlated with the risk of SA and CKM risk in T2DM patients. Sublingual microcirculation could be a novel tool for assessing the CKM syndrome stage in patients with T2DM.

A Cross-Sectional Evaluation of Cardiovascular Risk Assessment in Type 2 Diabetes Mellitus Patients Using the Framingham Risk Score.

BACKGROUND: The global burden of type 2 diabetes mellitus (T2DM) is continuously increasing, particularly in India. The risk of cardiovascular disease (CVD) is higher in T2DM individuals when compared to non-diabetics, which imposes significant morbidity and mortality. The main aim of the present study was to assess the risk factors for CVD in T2DM patients. The secondary aim was to assess the association between cardiovascular risk profile and 10-year cardiovascular risk using the Framingham risk score. METHODS: This was a cross-sectional study conducted on 110 T2DM patients, and the anthropometric and biochemical parameters were analyzed. The Framingham cardiovascular risk prediction model was used to calculate the 10-year risk for CVD. The CVD risk factor was compared among the genders. Further, the association between the Framingham cardiovascular risk and the various categories of risk factors was also analyzed. RESULTS: Based on the Framingham cardiovascular risk score, 23 (20.9%) were at low risk, 39 (35.5%) were at moderate risk, and 48 (43.6%) were at low risk. A higher proportion of males had hypertension (55.2 vs. 17.3%; p=0.007), elevated cholesterol levels (48.3% vs. 23.1%; p=0.008), and smoking or tobacco use (31% vs. 7.7%; p=0.006) as compared to females. The significant risk factors for high 10-year CVD risk were hypertension (p=0.001), elevated total cholesterol (p=0.03), smoking or tobacco use (p=0.007), and glycemic control (p=0.04). CONCLUSION: The Framingham cardiovascular risk score estimates reveal that male gender, hypertension, smoking, and uncontrolled diabetes are the important risk factors for CVD progression among diabetic patients. Therefore, it is imperative to generate awareness regarding the potential risks and then implement suitable interventions during the early phases at the primary healthcare level.

Comparison of Four Predictive Scores for Cardiovascular Risk in Mexican People with HIV.

Persons with HIV (PWH) face an increased risk of cardiovascular events due to immune activation, comorbidities, and certain antiretrovirals (ARVs). However, the current cardiovascular risk (CVR) scores are not specifically directed toward PWH. This study aimed to assess the agreement between different predictive CVR scores and explore their relationship with clinical and demographic data in Mexican PWH. A descriptive cross-sectional analysis was conducted in 200 PWH with a mean age of 42 years who were treated at a Mexican urban center from 2017 to 2018. The majority (83%) was on ARV treatment and 79.5% had undetectable viral loads (VLs). Moderate- to high-risk scores were infrequent, with Framingham Risk Score for Hard Coronary Heart Disease scores showing higher values, with very low concordance among all scores. Logistic regression analysis revealed significant associations between the CVR scores and the initial recorded VL, CD4 cell count, and elevated triglyceride levels. However, no associations were found with measures such as body mass index or abdominal circumference. Treatment with integrase strand transfer inhibitors (INSTIs), particularly first-generation inhibitors, showed strong associations with all predictive scores, notably ASCVD (odds ratio = 7.03, 95% confidence interval 1.67-29.64). The poor concordance among the CVR scores in PWH highlights the need for a specific score that considers comorbidities and ARV drugs. Despite the relatively young age of the participants, significant correlations were observed between INSTI use, initial VL, CD4 cell count, and triglyceride levels, which are factors not considered in the existing risk scores. Regardless of the actual value of the scores, screening for CVR in PWH is recommended.