Outcomes of prosthetic upper arm arteriovenous graft vs brachiobasilic fistula for hemodialysis access.

OBJECTIVE: Primary arteriovenous access such as radiocephalic and brachiocephalic fistulas are initial choices for creating vascular access in dialysis patients. When neither of these choices is an option, upper arm arteriovenous graft or brachiobasilic transposition is recommended. Although primary fistula is better than prosthetic graft for suitable patients, there is little data to guide the best treatment strategy in the absence of suitable vein for primary access creation. This study identifies factors that influence patency rates and compares outcomes of patients treated with brachiobasilic fistula vs upper arm graft in patients who have failed forearm access or are not candidates for primary access. METHODS: A prospectively maintained database of patients with dialysis-dependent renal failure from 2010 to 2022 was analyzed. Primary, primary assisted, and secondary patency rates were calculated. Incidence rates of complications and reinterventions were compared. RESULTS: There were 148 patients with brachiobasilic fistulas and 157 patients with upper arm grafts. The graft group was older (70.1 ± 14.7 vs 62.5 ± 14.6 years; P = .003) and had a higher incidence of pacemakers (11.9% vs 4.1%; P = .005). Brachiobasilic fistulas had higher 6-month (77.0% vs 64.3%; P = .02) and 1-year (68.2% vs 55.4%; P = .03) primary-assisted patency. Secondary patency rates were better for upper arm grafts at 1-year (82.2% vs 72.3%; P = .05). Access complications of non-maturation and aneurysm were higher in basilic vein transposition (21.6% vs 1.3%; P < .0001; 15.5% vs 6.4%; P = .017). Grafts had higher rates of occlusion (58.0% vs 25.7%; P < .0001). In terms of interventions, upper arm grafts had higher rates of thrombectomy (50.3% vs 18.9%; P < .0001), but there was no difference seen in angioplasty, stent, surgical revision, or steal procedures. Basilic vein transpositions had longer time to cannulation (104.6 ± 81.1 vs 32.5 ± 22.4 days; P < .0001), longer total catheter days (251.1 ± 181.7 vs 72.9 ± 56.3 days; P < .0001), and higher number of procedures to aid maturity (0.7 ± 0.7 vs 0.1 ± 0.3; P < .0001). CONCLUSIONS: In this retrospective analysis, when forearm access or primary arteriovenous access is not an option, basilic vein transposition and upper arm grafts have fairly equivalent primary patency. Primary assisted patency is slightly better in basilic vein fistulas, but secondary patency is better in upper arm grafts at 1 year. Basilic fistulas also had longer time to cannulation, longer total catheter days, and more procedures to aid maturity.

Emergence of the natural history of Myhre syndrome: 47 patients evaluated in the Massachusetts General Hospital Myhre Syndrome Clinic (2016-2023).

Myhre syndrome is an increasingly diagnosed ultrarare condition caused by recurrent germline autosomal dominant de novo variants in SMAD4. Detailed multispecialty evaluations performed at the Massachusetts General Hospital (MGH) Myhre Syndrome Clinic (2016-2023) and by collaborating specialists have facilitated deep phenotyping, genotyping and natural history analysis. Of 47 patients (four previously reported), most (81%) patients returned to MGH at least once. For patients followed for at least 5 years, symptom progression was observed in all. 55% were female and 9% were older than 18 years at diagnosis. Pathogenic variants in SMAD4 involved protein residues p.Ile500Val (49%), p.Ile500Thr (11%), p.Ile500Leu (2%), and p.Arg496Cys (38%). Individuals with the SMAD4 variant p.Arg496Cys were less likely to have hearing loss, growth restriction, and aortic hypoplasia than the other variant groups. Those with the p.Ile500Thr variant had moderate/severe aortic hypoplasia in three patients (60%), however, the small number (n = 5) prevented statistical comparison with the other variants. Two deaths reported in this cohort involved complex cardiovascular disease and airway stenosis, respectively. We provide a foundation for ongoing natural history studies and emphasize the need for evidence-based guidelines in anticipation of disease-specific therapies.

Initial Outcomes of the Gore TAG Thoracic Branch Endoprosthesis for Endovascular Repair of Blunt Thoracic Aortic Injury.

BACKGROUND: Endovascular repair of blunt thoracic aortic injury (BTAI) has dramatically reduced the morbidity and mortality of intervention. Injuries requiring zone 2 coverage of the aorta traditionally require left subclavian artery (LSA) sacrifice or open revascularization. Furthermore, these injuries are associated with an increased risk of in-hospital mortality and long-term morbidity. Here we report 1-year outcomes of total endovascular repair of BTAI with the GORE® TAG® Thoracic Branch Endoprosthesis for LSA preservation. METHODS: Across 34 investigative sites, 9 patients with BTAI requiring LSA coverage were enrolled in a nonrandomized, prospective study of a single-branched aortic endograft. The thoracic branch endoprosthesis device allows for graft placement proximal to the LSA and incorporates a single side branch for LSA perfusion. RESULTS: This initial cohort included 8 male and 1 female patient with a median age of 43 (22, 76) and 12 months of follow-up. Five total years of follow-up are planned. All participants had grade 3 BTAI. All procedures took place between 2018 and 2019. The median injury severity score was 2 (0, 66). The median procedure time was 109 min (78, 162). All aortic injuries were repaired under general anesthesia and with heparinization. A spinal drain was used in one patient. Post-deployment balloon angioplasty was conducted in one case at the distal landing zone. There was one asymptomatic LSA branch occlusion 6 months after repair. It was attributed to the purposeful proximal deployment of the branch stent to accommodate an early vertebral takeoff. The occlusion did not require revascularization. There were no strokes, mortalities, or aortic adverse events (migration, endoleak, native aortic expansion, dissection, or thrombosis) through 12 months of follow-up. CONCLUSIONS: Initial cohort outcomes suggest that endovascular repair of zone 2 BTAI is feasible and has favorable outcomes using the thoracic branch device with LSA preservation. Additional cases and longer-term follow-up are required for a definitive assessment of the device's safety and durability in traumatic aortic injuries.

Using Machine Learning to Predict Outcomes of Patients with Blunt Traumatic Aortic Injuries.

INTRODUCTION: The optimal management of blunt thoracic aortic injury (BTAI) remains controversial, with experienced centers offering therapy ranging from medical management to TEVAR. We investigated the utility of a machine learning (ML) algorithm to develop a prognostic model of risk factors on mortality in patients with BTAI. METHODS: The Aortic Trauma Foundation registry was utilized to examine demographics, injury characteristics, management and outcomes of patients with BTAI. A STREAMLINE (A Simple, Transparent, End-To-End Automated Machine Learning Pipeline Facilitating Data Analysis and Algorithm Comparison) model as well as logistic regression (LR) analysis with imputation using chained equations was developed and compared. RESULTS: From a total of 1018 patients in the registry, 702 patients were included in the final analysis. Of the 258 (37%) patients who were medically managed, 44 (17%) died during admission, 14 (5.4%) of which were aortic related deaths. 444 (63%) patients underwent TEVAR and 343 of which underwent TEVAR within 24 hours of admission. Amongst TEVAR patients, 39 (8.8%) patients died and 7 (1.6%) had aortic related deaths. (Table 1) Comparison of the STREAMLINE and LR model showed no significant difference in ROC curves and high AUCs of 0.869 (95% CI, 0.813 - 0.925) and 0.840 (95% CI, 0.779 - 0.900) respectively in predicting in-hospital mortality. Unexpectedly, however, the variables prioritized in each model differed between models (Figure 1A-B). The top three variables identified from the LR model were similar to that from existing literature. The STREAMLINE model, however, prioritized location of the injury along the lesser curve, age and aortic injury grade (Figure 1A). CONCLUSIONS: Machine learning provides insight on prioritization of variables not typically identified in standard multivariable logistic regression. Further investigation and validation in other aortic injury cohorts are needed to delineate the utility of ML models. LEVEL OF EVIDENCE: Level IIIStudy TypeOriginal research (prognostic/epidemiological).

Unraveling implicit human behavioral effects on dynamic characteristics of Covid-19 daily infection rates in Taiwan.

We investigate the dynamic characteristics of Covid-19 daily infection rates in Taiwan during its initial surge period, focusing on 79 districts within the seven largest cities. By employing computational techniques, we extract 18 features from each district-specific curve, transforming unstructured data into structured data. Our analysis reveals distinct patterns of asymmetric growth and decline among the curves. Utilizing theoretical information measurements such as conditional entropy and mutual information, we identify major factors of order-1 and order-2 that influence the peak value and curvature at the peak of the curves, crucial features characterizing the infection rates. Additionally, we examine the impact of geographic and socioeconomic factors on the curves by encoding each of the 79 districts with two binary characteristics: North-vs-South and Urban-vs-Suburban. Furthermore, leveraging this data-driven understanding at the district level, we explore the fine-scale behavioral effects on disease spread by examining the similarity among 96 age-group-specific curves within urban districts of Taipei and suburban districts of New Taipei City, which collectively represent a substantial portion of the nation's population. Our findings highlight the implicit influence of human behaviors related to living, traveling, and working on the dynamics of Covid-19 transmission in Taiwan.

Treatment of calcific arterial disease via enhancement of autophagy using GSK343.

Vascular calcification is a hallmark of atherosclerotic disease and serves as a strong predictor and risk factor for cardiovascular events. Growing evidence suggests that autophagy may play a protective role in early atherosclerosis. The precise effects of autophagy on VSMC-mediated calcification remain unknown. In this study, we utilized multi-omic profiling to investigate impaired autophagy at the transcriptional level as a key driver of VSMC calcification. Our findings revealed that impaired autophagy is an essential determinant of VSMC calcification. We observed that an osteogenic environment affects the open chromatin status of VSMCs, compromising the transcriptional activation of autophagy initiation genes. In vivo experiments involve pharmacological and genetic activation of autophagy using mouse models of spontaneous large (Mgp-/-) and small (Abcc6-/-) artery calcification. Taken together, these data advance our mechanistic understanding of vascular calcification and provide important insights for a broad range of cardiovascular diseases involving VSMC phenotype switch.

The Genetic Determinants of Aortic Distention.

BACKGROUND: As the largest conduit vessel, the aorta is responsible for the conversion of phasic systolic inflow from ventricular ejection into more continuous peripheral blood delivery. Systolic distention and diastolic recoil conserve energy and are enabled by the specialized composition of the aortic extracellular matrix. Aortic distensibility decreases with age and vascular disease. OBJECTIVES: In this study, we sought to discover epidemiologic correlates and genetic determinants of aortic distensibility and strain. METHODS: We trained a deep learning model to quantify thoracic aortic area throughout the cardiac cycle from cardiac magnetic resonance images and calculated aortic distensibility and strain in 42,342 UK Biobank participants. RESULTS: Descending aortic distensibility was inversely associated with future incidence of cardiovascular diseases, such as stroke (HR: 0.59 per SD; P = 0.00031). The heritabilities of aortic distensibility and strain were 22% to 25% and 30% to 33%, respectively. Common variant analyses identified 12 and 26 loci for ascending and 11 and 21 loci for descending aortic distensibility and strain, respectively. Of the newly identified loci, 22 were not significantly associated with thoracic aortic diameter. Nearby genes were involved in elastogenesis and atherosclerosis. Aortic strain and distensibility polygenic scores had modest effect sizes for predicting cardiovascular outcomes (delaying or accelerating disease onset by 2%-18% per SD change in scores) and remained statistically significant predictors after accounting for aortic diameter polygenic scores. CONCLUSIONS: Genetic determinants of aortic function influence risk for stroke and coronary artery disease and may lead to novel targets for medical intervention.

Genetics and mechanisms of thoracic aortic disease.

Aortic disease has many forms including aortic aneurysm and dissection, aortic coarctation or abnormalities in aortic function, such as loss of aortic distensibility. Genetic analysis in humans is one of the most important experimental approaches in uncovering disease mechanisms, but the relative infrequency of thoracic aortic disease compared with other cardiovascular conditions such as coronary artery disease has hindered large-scale identification of genetic associations. In the past decade, advances in machine learning technology coupled with large imaging datasets from biobank repositories have facilitated a rapid expansion in our capacity to measure and genotype aortic traits, resulting in the identification of dozens of genetic associations. In this Review, we describe the history of technological advances in genetic discovery and explain how newer technologies such as deep learning can rapidly define aortic traits at scale. Furthermore, we integrate novel genetic observations provided by these advances into our current biological understanding of thoracic aortic disease and describe how these new findings can contribute to strategies to prevent and treat aortic disease.

Long-term exposure to particulate matter was associated with increased dementia risk using both traditional approaches and novel machine learning methods.

Air pollution exposure has been linked to various diseases, including dementia. However, a novel method for investigating the associations between air pollution exposure and disease is lacking. The objective of this study was to investigate whether long-term exposure to ambient particulate air pollution increases dementia risk using both the traditional Cox model approach and a novel machine learning (ML) with random forest (RF) method. We used health data from a national population-based cohort in Taiwan from 2000 to 2017. We collected the following ambient air pollution data from the Taiwan Environmental Protection Administration (EPA): fine particulate matter (PM2.5) and gaseous pollutants, including sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen oxide (NOx), nitric oxide (NO), and nitrogen dioxide (NO2). Spatiotemporal-estimated air quality data calculated based on a geostatistical approach, namely, the Bayesian maximum entropy method, were collected. Each subject's residential county and township were reviewed monthly and linked to air quality data based on the corresponding township and month of the year for each subject. The Cox model approach and the ML with RF method were used. Increasing the concentration of PM2.5 by one interquartile range (IQR) increased the risk of dementia by approximately 5% (HR = 1.05 with 95% CI = 1.04-1.05). The comparison of the performance of the extended Cox model approach with the RF method showed that the prediction accuracy was approximately 0.7 by the RF method, but the AUC was lower than that of the Cox model approach. This national cohort study over an 18-year period provides supporting evidence that long-term particulate air pollution exposure is associated with increased dementia risk in Taiwan. The ML with RF method appears to be an acceptable approach for exploring associations between air pollutant exposure and disease.

A Mendelian randomization-based exploration of red blood cell distribution width and mean corpuscular volume with risk of hemorrhagic strokes.

Red blood cell distribution width (RCDW) and mean corpuscular volume (MCV) are associated with different risk factors for hemorrhagic stroke. However, whether RCDW and MCV are causally related to hemorrhagic stroke remains poorly understood. Therefore, we explored the causality between RCDW/MCV and nontraumatic hemorrhagic strokes using Mendelian randomization (MR) methods. We extracted exposure and outcome summary statistics from the UK Biobank and FinnGen. We evaluated the causality of RCDW/MCV on four outcomes (subarachnoid hemorrhage [SAH], intracerebral hemorrhage [ICH], nontraumatic intracranial hemorrhage [nITH], and a combination of SAH, cerebral aneurysm, and aneurysm operations) using univariable MR (UMR) and multivariable MR (MVMR). We further performed colocalization and mediation analyses. UMR and MVMR revealed that higher genetically predicted MCV is protective of ICH (UMR: odds ratio [OR] = 0.89 [0.8-0.99], p = 0.036; MVMR: OR = 0.87 [0.78-0.98], p = 0.021) and nITH (UMR: OR = 0.89 [0.82-0.97], p = 0.005; MVMR: OR = 0.88 [0.8-0.96], p = 0.004). There were no strong causal associations between RCDW/MCV and any other outcome. Colocalization analysis revealed a shared causal variant between MCV and ICH; it was not reported to be associated with ICH. Proportion mediated via diastolic blood pressure was 3.1% (0.1%,14.3%) in ICH and 3.4% (0.2%,15.8%) in nITH. The study constitutes the first MR analysis on whether genetically elevated RCDW and MCV affect the risk of hemorrhagic strokes. UMR, MVMR, and mediation analysis revealed that MCV is a protective factor for ICH and nITH, which may inform new insights into the treatments for hemorrhagic strokes.

Aortic Cellular Diversity and Quantitative Genome-Wide Association Study Trait Prioritization Through Single-Nuclear RNA Sequencing of the Aneurysmal Human Aorta.

BACKGROUND: Mural cells in ascending aortic aneurysms undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore this biology, we analyzed the transcriptional features of thoracic aortic tissue. METHODS: Single-nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm, and 7 without aneurysm. Individual transcriptomes were then clustered based on transcriptional profiles. Clusters were used for between-disease differential gene expression analyses, subcluster analysis, and analyzed for intersection with genetic aortic trait data. RESULTS: We sequenced 71 689 nuclei from human thoracic aortas and identified 14 clusters, aligning with 11 cell types, predominantly vascular smooth muscle cells (VSMCs) consistent with aortic histology. With unbiased methodology, we found 7 vascular smooth muscle cell and 6 fibroblast subclusters. Differentially expressed genes analysis revealed a vascular smooth muscle cell group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. Differentially expressed genes were used to prioritize genes at aortic diameter and distensibility genome-wide association study loci highlighting the genes JUN, LTBP4 (latent transforming growth factor beta-binding protein 1), and IL34 (interleukin 34) in fibroblasts, ENTPD1, PDLIM5 (PDZ and LIM domain 5), ACTN4 (alpha-actinin-4), and GLRX in vascular smooth muscle cells, as well as LRP1 in macrophage populations. CONCLUSIONS: Using nuclear RNA sequencing, we describe the cellular diversity of healthy and aneurysmal human ascending aorta. Sporadic aortic aneurysm is characterized by differential gene expression within known cellular classes rather than by the appearance of novel cellular forms. Single-nuclear RNA sequencing of aortic tissue can be used to prioritize genes at aortic trait loci.

Machine learning algorithms identify demographics, dietary features, and blood biomarkers associated with stroke records.

OBJECTIVE: We conducted a comprehensive evaluation of features associated with stroke records. METHODS: We screened the dietary nutrients, blood biomarkers, and clinical information from the National Health and Nutrition Examination Survey (NHANES) 2015-16 database to assess a self-reported history of all strokes (136 strokes, n = 4381). We computed feature importance, built machine learning (ML) models, developed a nomogram, and validated the nomogram on NHANES 2007-08, 2017-18, and the baseline UK Biobank. We calculated the odds ratios with/without adjusting sampling weights (OR/ORw). RESULTS: The clinical features have the best predictive power compared to dietary nutrients and blood biomarkers, with 22.8% increased average area under the receiver operating characteristic curves (AUROC) in ML models. We further modeled with ten most important clinical features without compromising the predictive performance. The key features positively associated with stroke include age, cigarette smoking, tobacco smoking, Caucasian or African American race, hypertension, diabetes mellitus, asthma history; the negatively associated feature is the family income. The nomogram based on these key features achieved good performances (AUROC between 0.753 and 0.822) on the test set, the NHANES 2007-08, 2017-18, and the UK Biobank. Key features from the nomogram model include age (OR = 1.05, ORw = 1.06), Caucasian/African American (OR = 2.68, ORw = 2.67), diabetes mellitus (OR = 2.30, ORw = 1.99), asthma (OR = 2.10, ORw = 2.41), hypertension (OR = 1.86, ORw = 2.10), and income (OR = 0.83, ORw = 0.81). CONCLUSIONS: We identified clinical key features and built predictive models for assessing stroke records with high performance. A nomogram consisting of questionnaire-based variables would help identify stroke survivors and evaluate the potential risk of stroke.

A study of forecasting tennis matches via the Glicko model.

Tennis is a popular sport, and professional tennis matches are probably the most watched games globally. Many studies consider statistical or machine learning models to predict the results of professional tennis matches. In this study, we propose a statistical approach for predicting the match outcomes of Grand Slam tournaments, in addition to applying exploratory data analysis (EDA) to explore variables related to match results. The proposed approach introduces new variables via the Glicko rating model, a Bayesian method commonly used in professional chess. We use EDA tools to determine important variables and apply classification models (e.g., logistic regression, support vector machine, neural network and light gradient boosting machine) to evaluate the classification results through cross-validation. The empirical study is based on men's and women's single matches of Grand Slam tournaments (2000-2019). Our analysis results show that professional tennis ranking is the most important variable and that the accuracy of the proposed Glicko model is slightly higher than that of other models.

Virtual Simulation of Intra-operative Decision-Making for Open Abdominal Aortic Aneurysm Repair: A Mixed Methods Analysis.

OBJECTIVE: To create and pilot test a novel open abdominal aortic aneurysm (AAA) repair virtual simulation focused on intraoperative decision-making. To identify if the simulation replicated real-time intra-operative decision-making and discover how learners' respond to this type of simulation. DESIGN: An explanatory sequential mixed methods study. We developed a step-by-step outline of major intra-operative decision points within a standard open AAA repair. Perioperative and intraoperative decision-making trees were developed and coded into an online virtual simulation. The simulation was piloted. Quantitative data was collected from the simulation platform. We then performed a qualitative thematic analysis on feedback from interviewed participants. SETTING: Four academic general and vascular surgical training programs across the US. PARTICIPANTS: Seventeen vascular and general surgery trainees and 6 vascular surgery faculty. RESULTS: Participants spent on average 27 minutes (range: 8-45 minutes) interacting with the interface. 93% of participants reported feeling they were making real intraoperative decisions. 85% said it added to their knowledge base. 96% requested additional simulations. 22 interviews were completed: 241 primary codes were collapsed into 21 parent codes, and 6 emerging themes identified. Themes included the benefit of how (1) "Virtual Learning Could Standardize the Training Experience"; how (2) "Dealing with the Unexpected" as a trainee is an important part of surgical education growth, and that this (3) "Choose Your Own Adventure" virtual format simulates this intraoperative growth experience. Participants requested a (4) "Looping Feature Feedback Diagram" for future simulation iterations and highlighted that (5) "Fancier is Not Necessarily More Educational." Finally, many trainees wondered about (6) "The Attending Impact" from the simulation: if faculty would notice a difference between trainees who did vs did not utilize the simulation for case preparation. CONCLUSIONS: Operative simulation training should focus on both technical skills and intra-operative decision-making, particularly "dealing with the unexpected." The learners' responses indicate that a low-fidelity, scalable, virtual platform can effectively deliver knowledge and allow for intra-operative decision-making practice in a remote learning environment.

Vascular trainee perceptions of diversity, equity, and inclusion within United States vascular surgery training programs.

OBJECTIVES: Vascular surgery training programs face multiple pressures, including attracting and retaining trainees. Current knowledge of trainees' views with respect to diversity and equity in vascular training programs is limited. We sought to understand United States vascular surgery trainees' perceptions and expectations regarding diversity, equity, and inclusion (DEI). METHODS: The Association of Program Directors in Vascular Surgery designed and administered the Annual Training Survey to specifically address DEI and administered it to all trainees (Integrated Residents/Fellows; n = 637) at 122 institutions in August 2020. RESULTS: Of the 637 vascular trainees, 227 (35%) responded. The respondents included 115 male and 62 female trainees, with 50 not disclosing or not answering the question. The majority of respondents (96.9%) believed their programs incorporated a diverse background of trainees. Of the trainees, 89.8% felt that the faculty were similarly comprised of a diverse background. The majority of respondents (63.6%) felt that their training program was both more diverse and focused on inclusion compared with other training programs at their institution. However, 20% of respondents had experienced discrimination. Seventy-three percent (n = 143) of trainees felt empowered to disagree or engage in a discussion should they observe a faculty member make a disparaging remark about a patient's background/race/gender, although 27% (n = 35) trainees expressed fear of retaliation as a reason to not engage. Trainees view their program director (82.6%), faculty mentor (60.9%), and Graduate Medical Education office (52.7%) as potential resources for support. Overall, 83.7% (n = 160) of trainees believe that their program has been open to discussion of race relations within the medical community. CONCLUSIONS: Trainees are committed to multifaceted diversity and inclusion. The perception of trainees regarding DEI issues within vascular surgery training programs appears to be positive; however, trainees did describe discrimination and gender biases in their institutions. This data has the potential to improve institutional education of faculty and trainees about the multidimensional levels of diversity and increased awareness and incorporation of this philosophy can assist in the recruitment of diverse vascular surgeons.

Risk factors and consequences of graft infection after femoropopliteal bypass: A 25-year experience.

OBJECTIVE: In this multi-institutional series, we aimed to determine the incidence, risk factors, and long-term outcomes of graft infection in patients post-femoropopliteal bypass. METHODS: A multi-institutional database was retrospectively queried for all femoropopliteal bypass procedures from 1995 through 2020. Cumulative incidence function estimated the long-term rate of bypass graft infection (BGI), and the Fine-Gray model was used to determine independent risk factors for BGI to account for death as a competing risk. RESULTS: Over the 25-year period, 1315 femoral popliteal bypasses were identified with a median follow-up of 2.89 years (interquartile range, 0.75-6.55 years). BGI was diagnosed in 34 patients (2.6%). BGI occurred between 9 days and 11.2 years postoperatively, with a median of 109 days. Estimated 1- and 5-year incidence of BGI was 2.1% (95% confidence interval [CI], 1.4%-3.1%) and 2.8% (95% CI, 1.9%-3.9%), respectively. Medical comorbidities, indications for bypass, and popliteal bypass targets (above- vs below-knee) were similar between patients with BGI and all patients (P = not significant for each). Patients with BGI were more frequently complicated by postoperative hematoma (14.7% vs 3.7%), superficial wound infection (38.2% vs 19.2%), lymphocele/lymphorrhea (8.8% vs 2.1%), and 30-day readmission rates (47.1% vs 21.3%) (P < .05 for each). Most commonly isolated pathogens were Staphylococcus aureus (n = 19; 55.9%) and polymicrobial cultures (n = 5; 14.7%). Reoperation for BGI involved incision and drainage (n = 7; 20.6%), graft excision without reconstruction (n = 12; 35.3%), graft excision with in-line reconstruction (n = 11; 32.4%), and graft excision with extra-anatomic reconstruction (n = 2; 5.9%). Nine patients with BGI (26.5%) ultimately required major amputation. Prosthetic bypass (subdistribution hazard ratio [SHR], 3.73; 95% CI, 1.64-8.51; P = .002), postoperative hematoma (SHR, 3.44; 95% CI, 1.23-9.61; P = .018), and 30-day readmission (SHR, 2.75; 95% CI, 1.27-5.44; P = .010) were independently associated with BGI. One-year amputation-free survival was 50% (95% CI, 31.9%-65.7%) after BGI. CONCLUSIONS: BGI is a rare complication of femoral-popliteal bypass with significant morbidity. Graft infection is associated with the use of prosthetic grafts, postoperative hematoma, and unplanned hospital readmission. Mitigation of these risk factors may decrease the risk of this dreaded complication.

Fibrillar Collagen Variants in Spontaneous Coronary Artery Dissection.

IMPORTANCE: Spontaneous coronary artery dissection (SCAD) is an increasingly recognized nonatherosclerotic cause of acute myocardial infarction enriched among individuals with early-onset myocardial infarction but is of unclear etiology. OBJECTIVE: To assess which genes contribute to the development of SCAD. DESIGN, SETTING, AND PARTICIPANTS: To prioritize genes influencing risk for SCAD, whole-exome sequencing was performed among individuals with SCAD in the discovery and replication cohorts from a tertiary care hospital outpatient specialty clinic, and gene set enrichment analyses were also performed for disruptive coding variants. All patients were sequentially enrolled beginning July 2013. Aggregate prevalence of rare disruptive variants for prioritized gene sets was compared between individuals with SCAD with population-based controls comprising 46 468 UK Biobank participants with whole-exome sequencing. Complementary mice models were used for in vivo validation. Analysis took place between June 2020 and January 2021. MAIN OUTCOMES AND MEASURES: The frequency and identity of rare genetic variants in individuals with SCAD. RESULTS: Of 130 patients, 109 (83.8%) were female (26 of 32 [81.2%] in the discovery cohort and 83 of 98 [84.7%] in the replication cohort) with mean (SD) age at first SCAD event of 48.41 (8.76) years in the discovery cohort and 47.74 (10.09) years in the replication cohort. Across all patients with SCAD, rare disruptive variants were found within 10 collagen genes (COL3A1, COL5A1, COL4A1, COL6A1, COL5A2, COL12A1, COL4A5, COL1A1, COL1A2, and COL27A1) were 17-fold (P = 1.5 × 10-9) enriched among individuals with SCAD compared with a background of 2506 constrained genes expressed in coronary artery. Furthermore, compared with individuals from the UK Biobank, individuals with SCAD were 1.75-fold (P = .04) more likely to carry disruptive rare variants within fibrillar collagen genes. Complementary mice models haploinsufficient for Col3a1 or Col5a1, the 2 most common collagen gene variants identified in SCAD cases, demonstrated increased risk of arterial dissection and increased size of arterial diameters especially in female mice, with resulting changes in collagen fibril organization and diameter. CONCLUSIONS AND RELEVANCE: Unbiased gene discovery in patients with SCAD with independent human and murine validation highlights the role of the extracellular matrix dysfunction in SCAD.

Unraveling Hidden Major Factors by Breaking Heterogeneity into Homogeneous Parts within Many-System Problems.

For a large ensemble of complex systems, a Many-System Problem (MSP) studies how heterogeneity constrains and hides structural mechanisms, and how to uncover and reveal hidden major factors from homogeneous parts. All member systems in an MSP share common governing principles of dynamics, but differ in idiosyncratic characteristics. A typical dynamic is found underlying response features with respect to covariate features of quantitative or qualitative data types. Neither all-system-as-one-whole nor individual system-specific functional structures are assumed in such response-vs-covariate (Re-Co) dynamics. We developed a computational protocol for identifying various collections of major factors of various orders underlying Re-Co dynamics. We first demonstrate the immanent effects of heterogeneity among member systems, which constrain compositions of major factors and even hide essential ones. Secondly, we show that fuller collections of major factors are discovered by breaking heterogeneity into many homogeneous parts. This process further realizes Anderson's "More is Different" phenomenon. We employ the categorical nature of all features and develop a Categorical Exploratory Data Analysis (CEDA)-based major factor selection protocol. Information theoretical measurements-conditional mutual information and entropy-are heavily used in two selection criteria: C1-confirmable and C2-irreplaceable. All conditional entropies are evaluated through contingency tables with algorithmically computed reliability against the finite sample phenomenon. We study one artificially designed MSP and then two real collectives of Major League Baseball (MLB) pitching dynamics with 62 slider pitchers and 199 fastball pitchers, respectively. Finally, our MSP data analyzing techniques are applied to resolve a scientific issue related to the Rosenberg Self-Esteem Scale.

Vascular smooth muscle cell phenotype switching in carotid atherosclerosis.

Carotid plaque instability contributes to large vessel ischemic stroke. Although vascular smooth muscle cells (VSMCs) affect atherosclerotic growth and instability, no treatments aimed at improving VSMC function are available. Large genetic studies investigating atherosclerosis and carotid disease in relation to the risk of stroke have implicated polymorphisms at the HDAC9 locus. The HDAC9 protein has been shown to affect the VSMC phenotype; however, how this might affect carotid disease is unknown. We conducted a pilot investigation using single nuclei RNA sequencing of human carotid tissue to identify cells expressing HDAC9 and specifically investigate the role of the HDAC9 in carotid atherosclerosis. We found that carotid VSMCs express HDAC9 and genes typically associated with immune characteristics. Using cellular assays, we have demonstrated that recruitment of macrophages can be modulated by HDAC9 expression. HDAC9 expression might affect carotid plaque stability and progression through its effects on the VSMC phenotype and recruitment of immune cells.

Surgical resection and graft replacement for primary inferior vena cava leiomyosarcoma: A multicenter experience.

OBJECTIVE: Primary leiomyosarcoma of the inferior vena cava (IVC) is best managed with surgical resection when technically feasible. However, consensus is lacking regarding the best choice of conduit and reconstruction technique. The aim of the present multicenter study was to perform a comprehensive assessment through the VLFDC (Vascular Low Frequency Disease Consortium) to determine the most effective method for caval reconstruction after resection of primary leiomyosarcoma of the IVC. METHODS: A multicenter, standardized database review of patients who had undergone surgical resection and reconstruction of the IVC for primary leiomyosarcoma from 2007 to 2017 was performed. The demographics, periprocedural details, and postoperative outcomes were analyzed. RESULTS: A total of 92 patients (60 women and 32 men), with a mean age of 60.1 years (range, 30-88 years) were treated. Metastatic disease was present in 22%. The tumor location was below the renal veins in 49 (53%), between the renal and hepatic veins in 52 (57%), and above the hepatic veins in 13 patients (14%). The conduits used for reconstruction included ringed polytetrafluoroethylene (PTFE; n = 80), nonringed PTFE (n = 1), Dacron (n = 1), autogenous vein (n = 1), bovine pericardium (n = 4), and cryopreserved tissue (n = 5). Complete R0 resection was accomplished in 73 patients (79%). In-hospital mortality was 2%, with a median length of stay of 8 days. The primary patency of PTFE reconstructed IVCs was 97% and 92% at 1 and 5 years, respectively, compared with 73% at 1 and 5 years for the non-PTFE reconstructed IVCs. The overall 1-, 3-, and 5-year survival for the entire cohort were 94%, 86%, and 65%, respectively CONCLUSIONS: The findings from our multi-institutional study have demonstrated that complete en bloc resection of IVC leiomyosarcoma with vascular surgical reconstruction in selected patients results in low perioperative mortality and is associated with excellent long-term patency. A ringed PTFE graft was the most commonly used conduit for caval reconstruction, yielding excellent long-term primary patency.