Calf rEF: Impact of Calf Muscle Pump Dysfunction With Reduced Ejection Fraction on All-Cause Mortality.

OBJECTIVE: To evaluate mortality outcomes by varying degrees of reduced calf muscle pump (CMP) ejection fraction (EF). PATIENTS AND METHODS: Consecutive adult patients who underwent venous air plethysmography testing at the Mayo Clinic Gonda Vascular Laboratory (January 1, 2012, through December 31, 2022) were divided into groups based on CMP EF for the assessment of all-cause mortality. Other venous physiology included measures of valvular incompetence and clinical venous disease (CEAP [clinical presentation, etiology, anatomy, and pathophysiology] score). Mortality rates were calculated using the Kaplan-Meier method. RESULTS: During the study, 5913 patients met the inclusion criteria. During 2.84-year median follow-up, there were 431 deaths. Mortality rates increased with decreasing CMP EF. Compared with EF of 50% or higher, the hazard ratios (95% CIs) for mortality were as follows: EF of 40% to 49%, 1.4 (1.0 to 2.0); EF of 30% to 39%, 1.6 (1.2 to 2.4); EF of 20% to 29%, 1.7 (1.2 to 2.4); EF of 10% to 19%, 2.4 (1.7 to 3.3) (log-rank P≤.001). Although measures of venous valvular incompetence did not independently predict outcomes, venous disease severity assessed by CEAP score was predictive. After adjusting for several clinical covariates, both CMP EF and clinical venous disease severity assessed by CEAP score remained independent predictors of mortality. CONCLUSION: Mortality rates are higher in patients with reduced CMP EF and seem to increase with each 10% decrement in CMP EF. The mortality mechanism does not seem to be impacted by venous valvular incompetence and may represent variables intrinsic to muscular physiology.

Vascular Diseases in Women: Do Women Suffer from Them Differently?

According to the World Health Organization, cardiovascular disease (CVD) is the leading cause of death among women worldwide, yet its magnitude is often underestimated. Biological and gender differences affect health, diagnosis, and healthcare in numerous ways. The lack of sex and gender awareness in health research and healthcare is an ongoing issue that affects not only research but also treatment and outcomes. The importance of recognizing the impacts of both sex and gender on health and of knowing the differences between the two in healthcare is beginning to gain ground. There is more appreciation of the roles that biological differences (sex) and sociocultural power structures (gender) have, and both sex and gender affect health behavior, the development of diseases, their diagnosis, management, and the long-term effects of an illness. An important issue is the knowledge and awareness of women about vascular diseases. The risk of cardiovascular events is drastically underestimated by women themselves, as well as by those around them. The purpose of this review is to draw attention to improving the medical care and treatment of women with vascular diseases.

Artificial intelligence of arterial Doppler waveforms to predict major adverse outcomes among patients with diabetes mellitus.

OBJECTIVE: Patients with diabetes mellitus (DM) are at increased risk for peripheral artery disease (PAD) and its complications. Arterial calcification and non-compressibility may limit test interpretation in this population. Developing tools capable of identifying PAD and predicting major adverse cardiac event (MACE) and limb event (MALE) outcomes among patients with DM would be clinically useful. Deep neural network analysis of resting Doppler arterial waveforms was used to detect PAD among patients with DM and to identify those at greatest risk for major adverse outcome events. METHODS: Consecutive patients with DM undergoing lower limb arterial testing (April 1, 2015-December 30, 2020) were randomly allocated to training, validation, and testing subsets (60%, 20%, and 20%). Deep neural networks were trained on resting posterior tibial arterial Doppler waveforms to predict all-cause mortality, MACE, and MALE at 5 years using quartiles based on the distribution of the prediction score. RESULTS: Among 11,384 total patients, 4211 patients with DM met study criteria (mean age, 68.6 ± 11.9 years; 32.0% female). After allocating the training and validation subsets, the final test subset included 856 patients. During follow-up, there were 262 deaths, 319 MACE, and 99 MALE. Patients in the upper quartile of prediction based on deep neural network analysis of the posterior tibial artery waveform provided independent prediction of death (hazard ratio [HR], 3.58; 95% confidence interval [CI], 2.31-5.56), MACE (HR, 2.06; 95% CI, 1.49-2.91), and MALE (HR, 13.50; 95% CI, 5.83-31.27). CONCLUSIONS: An artificial intelligence enabled analysis of a resting Doppler arterial waveform permits identification of major adverse outcomes including all-cause mortality, MACE, and MALE among patients with DM.

Venous and arterial thrombosis in patients with VEXAS syndrome.

ABSTRACT: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome, caused by somatic mutations in UBA1, is an autoinflammatory disorder with diverse systemic manifestations. Thrombosis is a prominent clinical feature of VEXAS syndrome. The risk factors and frequency of thrombosis in VEXAS syndrome are not well described, due to the disease's recent discovery and the paucity of large databases. We evaluated 119 patients with VEXAS syndrome for venous and arterial thrombosis and correlated their presence with clinical outcomes and survival. Thrombosis occurred in 49% of patients, mostly venous thromboembolism (VTE; 41%). Almost two-thirds of VTEs were unprovoked, 41% were recurrent, and 20% occurred despite anticoagulation. The cumulative incidence of VTE was 17% at 1 year from symptom onset and 40% by 5 years. Cardiac and pulmonary inflammatory manifestations were associated with time to VTE. M41L was positively associated specifically with pulmonary embolism by univariate (odds ratio [OR]: 4.58, confidence interval [CI] 1.28-16.21, P = .02) and multivariate (OR: 16.94, CI 1.99-144.3, P = .01) logistic regression. The cumulative incidence of arterial thrombosis was 6% at 1 year and 11% at 5 years. The overall survival of the entire patient cohort at median follow-up time of 4.8 years was 88%, and there was no difference in survival between patients with or without thrombosis (P = .8). Patients with VEXAS syndrome are at high risk of VTE; thromboprophylaxis should administered be in high-risk settings unless strongly contraindicated.

Cervical radiculopathy secondary to vertebral artery dissection: clinical features and outcomes.

PURPOSE: Cervical radiculopathy due to various mechanical causes is commonly seen, however, cervical vertebral artery dissection (cVAD)-related radiculopathy is very rare with poorly characterized clinical outcomes. Thus, we conducted a systematic review of published literature and reported an institutional case to provide a better illustration of this rare entity. METHODS: We systematically reviewed the PubMed literature and queried the clinical database at our center for cVAD-related radiculopathy. We described the baseline characteristics of patients with cVAD-related radiculopathy, the involved segment, diagnostic approach and treatment options. RESULT: 14 previously published studies met the inclusion criteria and along with the case we identified in our center, our study included 17 patients total (median age: 35 years, 9 females). C5 was the most commonly affected root and ipsilateral shoulder/arm pain along with shoulder abduction weakness was most common presentation. Antiplatelet or anticoagulant therapy was the treatment of choice. Most cases managed conservatively (82%). Majority of the cases (92%) had either complete or partial resolution of their symptoms. CONCLUSION: Despite its limitations, this study show that cVAD related radiculopathy is a relatively benign entity with excellent clinical outcomes when managed medically.

Artificial Intelligence of Arterial Doppler Waveforms to Predict Major Adverse Outcomes Among Patients Evaluated for Peripheral Artery Disease.

BACKGROUND: Patients with peripheral artery disease are at increased risk for major adverse cardiac events, major adverse limb events, and all-cause death. Developing tools capable of identifying those patients with peripheral artery disease at greatest risk for major adverse events is the first step for outcome prevention. This study aimed to determine whether computer-assisted analysis of a resting Doppler waveform using deep neural networks can accurately identify patients with peripheral artery disease at greatest risk for adverse outcome events. METHODS AND RESULTS: Consecutive patients (April 1, 2015, to December 31, 2020) undergoing ankle-brachial index testing were included. Patients were randomly allocated to training, validation, and testing subsets (60%/20%/20%). Deep neural networks were trained on resting posterior tibial arterial Doppler waveforms to predict major adverse cardiac events, major adverse limb events, and all-cause death at 5 years. Patients were then analyzed in groups based on the quartiles of each prediction score in the training set. Among 11 384 total patients, 10 437 patients met study inclusion criteria (mean age, 65.8±14.8 years; 40.6% women). The test subset included 2084 patients. During 5 years of follow-up, there were 447 deaths, 585 major adverse cardiac events, and 161 MALE events. After adjusting for age, sex, and Charlson comorbidity index, deep neural network analysis of the posterior tibial artery waveform provided independent prediction of death (hazard ratio [HR], 2.44 [95% CI, 1.78-3.34]), major adverse cardiac events (HR, 1.97 [95% CI, 1.49-2.61]), and major adverse limb events (HR, 11.03 [95% CI, 5.43-22.39]) at 5 years. CONCLUSIONS: An artificial intelligence-enabled analysis of Doppler arterial waveforms enables identification of major adverse outcomes among patients with peripheral artery disease, which may promote early adoption and adherence of risk factor modification.

Risk Stratification and Management of Intermediate-Risk Acute Pulmonary Embolism.

Pulmonary embolism (PE) is the third most common cause of cardiovascular death and necessitates prompt, accurate risk assessment at initial diagnosis to guide treatment and reduce associated mortality. Intermediate-risk PE, defined as the presence of right ventricular (RV) dysfunction in the absence of hemodynamic compromise, carries a significant risk for adverse clinical outcomes and represents a unique diagnostic challenge. While small clinical trials have evaluated advanced treatment strategies beyond standard anticoagulation, such as thrombolytic or endovascular therapy, there remains continued debate on the optimal care for this patient population. Here, we review the most recent risk stratification models, highlighting differences between prediction scores and their limitations, and discuss the utility of serologic biomarkers and imaging modalities to detect right ventricular dysfunction. Additionally, we examine current treatment recommendations including anticoagulation strategies, use of thrombolytics at full and reduced doses, and utilization of invasive treatment options. Current knowledge gaps and ongoing studies are highlighted.