Hasil untuk "Diseases of the circulatory (Cardiovascular) system"

Zhao‐Xia Fei, Ying‐Jie Dai, Xin‐Hong Wang et al.

Background Head down position (HDP) shows potential benefits in acute ischemic stroke. Although −20° HDP appears safe, feasible, and potentially beneficial in patients with large artery atherosclerosis without reperfusion therapy, its value before endovascular treatment (EVT) in acute large vessel occlusion (LVO) stroke remains unknown. This trial aims to investigate the efficacy and safety of −20° HDP in patients with acute large vessel occlusion stroke before planned EVT. Methods The HOPES5 (Head Down Position Before Endovascular Treatment for Large Vessel Occlusion) trial is a prospective, randomized, open label, blinded‐end point, multicenter study. Eligible patients with large vessel occlusion will be randomized 1:1 to −20° HDP or a flat (0°) head position before EVT, alongside standard guideline‐based care. Primary outcome is early neurological improvement, defined as ≥4 National Institutes of Health Stroke Scale score reduction within 24 hours post EVT. Safety outcomes are HDP‐related adverse events. Based on a prospective cohort, the proportion of early neurological improvement after EVT was ∼31%. A 20% absolute early neurological improvement increase (51%) in the HDP group is assumed. With 2‐sided α=0.05, 80% power, 10% follow‐up loss, and interim analysis alpha consumption, 210 patients (105 per group) are enrolled. All outcomes will have blinded assessment and will be analyzed on the intention‐to‐treat basis. The primary analysis will be stratified by age, sex, diabetes, baseline systolic blood pressure, location of index vessel, baseline National Institutes of Health Stroke Scale score, onset to HDP time, onset to thrombectomy time. Conclusions The results of HOPES5 will provide initial evidence on the effect of HDP in patients with acute large vessel occlusion stroke before EVT within 24 h of onset. Registration URL: https://clinicaltrials.gov/; Unique Identifier: NCT07172789.

Sri Varsha Mulakala, G. Neeharika, P. Vinay Kumar et al.

The recent increase in morbidity is primarily due to chronic diseases including Diabetes, Heart disease, Lung cancer, and brain tumours. The results for patients can be improved, and the financial burden on the healthcare system can be lessened, through the early detection and prevention of certain disorders. In this study, we built a machine-learning model for predicting the existence of numerous diseases utilising datasets from various sources, including Kaggle, Dataworld, and the UCI repository, that are relevant to each of the diseases we intended to predict. Following the acquisition of the datasets, we used feature engineering to extract pertinent features from the information, after which the model was trained on a training set and improved using a validation set. A test set was then used to assess the correctness of the final model. We provide an easy-to-use interface where users may enter the parameters for the selected ailment. Once the right model has been run, it will indicate whether the user has a certain ailment and offer suggestions for how to treat or prevent it.

Karina Gelis-Cadena, Michael Daniels, Juned Siddique

We address causal estimation in semi-competing risks settings, where a non-terminal event may be precluded by one or more terminal events. We define a principal-stratification causal estimand for treatment effects on the non-terminal event, conditional on surviving past a specified landmark time. To estimate joint event-time distributions, we employ both vine-copula constructions and Bayesian nonparametric Enriched Dirichlet-process mixtures (EDPM), enabling inference under minimal parametric assumptions. We index our causal assumptions with sensitivity parameters. Posterior summaries via MCMC yield interpretable estimates with credible intervals. We illustrate the proposed method using data from a cardiovascular health study.

Diego Rojo, Houda Lamqaddam, Lucija Gosak et al.

Cardiovascular diseases (CVDs), the leading cause of death worldwide, can be prevented in most cases through behavioral interventions. Therefore, effective communication of CVD risk and projected risk reduction by risk factor modification plays a crucial role in reducing CVD risk at the individual level. However, despite interest in refining risk estimation with improved prediction models such as SCORE2, the guidelines for presenting these risk estimations in clinical practice remained essentially unchanged in the last few years, with graphical score charts (GSCs) continuing to be one of the prevalent systems. This work describes the design and implementation of Petal-X, a novel tool to support clinician-patient shared decision-making by explaining the CVD risk contributions of different factors and facilitating what-if analysis. Petal-X relies on a novel visualization, Petal Product Plots, and a tailor-made global surrogate model of SCORE2, whose fidelity is comparable to that of the GSCs used in clinical practice. We evaluated Petal-X compared to GSCs in a controlled experiment with 88 healthcare students, all but one with experience with chronic patients. The results show that Petal-X outperforms GSC in critical tasks, such as comparing the contribution to the patient's 10-year CVD risk of each modifiable risk factor, without a significant loss of perceived transparency, trust, or intent to use. Our study provides an innovative approach to the visualization and explanation of risk in clinical practice that, due to its model-agnostic nature, could continue to support next-generation artificial intelligence risk assessment models.

Jixun Yao, Nikita Kuzmin, Qing Wang et al.

Speaker anonymization is an effective privacy protection solution that conceals the speaker's identity while preserving the linguistic content and paralinguistic information of the original speech. To establish a fair benchmark and facilitate comparison of speaker anonymization systems, the VoicePrivacy Challenge (VPC) was held in 2020 and 2022, with a new edition planned for 2024. In this paper, we describe our proposed speaker anonymization system for VPC 2024. Our system employs a disentangled neural codec architecture and a serial disentanglement strategy to gradually disentangle the global speaker identity and time-variant linguistic content and paralinguistic information. We introduce multiple distillation methods to disentangle linguistic content, speaker identity, and emotion. These methods include semantic distillation, supervised speaker distillation, and frame-level emotion distillation. Based on these distillations, we anonymize the original speaker identity using a weighted sum of a set of candidate speaker identities and a randomly generated speaker identity. Our system achieves the best trade-off of privacy protection and emotion preservation in VPC 2024.

Taijyu Satoh, Nobuhiro Yaoita, Satoshi Higuchi et al.

ABSTRACT Patients with borderline pulmonary hypertension (PH) often experience shortness of breath or exacerbation of PH during exercise, known as exercise‐induced PH. However, the pathogenesis of exercise‐induced post‐capillary PH (post‐EIPH) and its treatment strategies remain unclear. Recent guidelines and consensus documents have highlighted the benefits of sodium‐glucose cotransporter‐2 (SGLT2) inhibitors in heart failure and chronic kidney disease (CKD). This study aimed to investigate the effects of SGLT2 inhibitors in patients with post‐EIPH and CKD. This single‐center prospective cohort study enroled 10 patients with CKD (age, 68 years; female, 60%) who exhibited post‐EIPH between 1 July 2022 and 31 December 2023. Post‐EIPH was defined as a pulmonary capillary wedge pressure (PCWP)/cardiac output (CO) slope > 2 and peak PCWP during exercise ≥ 25 mmHg measured by catheterization. The patients received SGLT2 inhibitor treatment for 6 months. At rest, patients with post‐EIPH had borderline‐PH (21.5 ± 1.8 mmHg), with preserved left and right ventricular function. SGLT2 inhibitors treatment significantly reduced the PCWP/CO slope during exercise (3.9 ± 1.2 vs. 2.4 ± 1.2 mmHg/L/min, p = 0.013) and improved the 6‐min walking distance (489.9 ± 80.2 vs. 568.3 ± 91.9 m, p = 0.014). Magnetic resonance imaging revealed a lower left ventricular global longitudinal strain in patients with post‐EIPH, which was increased by SGLT2 inhibitor treatment (−13.8 ± 2.0 vs. −17.3 ± 2.0%, p = 0.003). SGLT2 treatment inhibitors mitigated post‐EIPH hemodynamic abnormalities and exercise intolerance, suggesting their potential as its therapeutic option.

Hai-Bing Li, Chang Liu, Xiang-Di Mao et al.

ObjectiveAortic dissection (AD) is a severe aortic disease with high mortality, and its pathogenesis remains elusive. To explore the regulatory mechanisms of AD, we integrated public RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) datasets to screen the hub genes of AD and further analyzed their functions, which may provide references to the diagnosis and treatment of AD.MethodsFour AD-related datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis and differential expression analysis were applied to identify overlapping genes in dataset GSE153434. Protein–protein interaction (PPI) network was constructed based on overlapping genes. Five methods (closeness, degree, EPC, MCC, and MNN) were used to pick hub genes. The receiver operating characteristic curve was used to evaluate the diagnostic efficiency of the hub genes in extra datasets GSE98770 and GSE52093. scRNA-seq dataset GSE213740 was used to explore the expression and function of the hub genes at the single-cell level. Quantitative real-time polymerase chain reaction was used to verify the expression of hub genes in beta-aminopropionitrile (BAPN)-induced mouse thoracic aortic aneurysm and dissection (TAAD) model.ResultsA total of 71 overlapping genes were screened by intersecting the significant genes in the pink module and the differentially expressed genes. A PPI network with 45 nodes and 74 edges was generated, and five top hub genes (HIF1A, HGF, HMOX1, ITGA5, and ITGB3) were identified. All the hub genes had area under the curve values above 0.55. scRNA-seq data analysis showed that HIF1A was significantly upregulated in macrophages and HGF was significantly upregulated in vascular smooth muscle cells (SMCs) of the ascending aortas in AD patients. HIF1A may transcriptionally regulate multiple downstream target genes involving inflammation (TLR2, ALOX5AP, and MIF), glycolysis (ENO1, LDHA, and GAPDH), tissue remodeling (PLAU), and angiogenesis (SERPIN and VEGFA). HGF may participate in the signaling among SMCs, fibroblasts, and endothelial cells through binding to different receptors (MET, EGFR, IGF1R, and KDR). The mRNA expression of Hif1a, Hgf, and their target genes, including Alox5ap, Serpine1, Tlr2, Plau, Egfr, and Igf1r, was significantly upregulated in aortic tissues of BAPN-treated mice.ConclusionBy integrating RNA-seq and scRNA-seq data, we identified HIF1A and HGF as two hub genes with good diagnostic efficiency for AD. HIF1A in macrophages may promote AD formation by promoting inflammation, glycolysis, tissue remodeling, and angiogenesis, and HGF may mediate signaling among SMCs, fibroblasts, and endothelial cells in the development of AD.

Joseph D. Bozzay, MD, Peter J. Kneuertz, MD, David S. Xu, MD et al.

Thoracic endovascular aortic repair (TEVAR) enables rapid and effective treatment of life-threatening aortic injuries. The occurrence of long-term complications from TEVAR and their management is ill-defined in young patients. This report describes a complex case of a 38-year-old male patient who underwent staged interventions for different acute pathologies instigated by blunt thoracic spinal trauma. The patient was initially treated with a TEVAR for aortic pseudoaneurysm in the setting of infected spinal hardware, which later resulted in an aortobronchial fistula and eroded spinal hardware. This report illustrates a successful multidisciplinary approach for definitive treatment with graft explant and aortic reconstruction.

Katarzyna Kmiotek, Anna Zoccarato, Rafael R. Oexner et al.

J-W. Park, D. Dischl, K. Aschbacher et al.

Wentao Zhang, Yujun Huang, Tong Zhang et al.

Currently intelligent diagnosis systems lack the ability of continually learning to diagnose new diseases once deployed, under the condition of preserving old disease knowledge. In particular, updating an intelligent diagnosis system with training data of new diseases would cause catastrophic forgetting of old disease knowledge. To address the catastrophic forgetting issue, an Adapter-based Continual Learning framework called ACL is proposed to help effectively learn a set of new diseases at each round (or task) of continual learning, without changing the shared feature extractor. The learnable lightweight task-specific adapter(s) can be flexibly designed (e.g., two convolutional layers) and then added to the pretrained and fixed feature extractor. Together with a specially designed task-specific head which absorbs all previously learned old diseases as a single "out-of-distribution" category, task-specific adapter(s) can help the pretrained feature extractor more effectively extract discriminative features between diseases. In addition, a simple yet effective fine-tuning is applied to collaboratively fine-tune multiple task-specific heads such that outputs from different heads are comparable and consequently the appropriate classifier head can be more accurately selected during model inference. Extensive empirical evaluations on three image datasets demonstrate the superior performance of ACL in continual learning of new diseases. The source code is available at https://github.com/GiantJun/CL_Pytorch.

Felipe M. Dias, Marcelo A. F. Toledo, Diego A. C. Cardenas et al.

Photoplethysmography (PPG) is a non-invasive technology that measures changes in blood volume in the microvascular bed of tissue. It is commonly used in medical devices such as pulse oximeters and wrist worn heart rate monitors to monitor cardiovascular hemodynamics. PPG allows for the assessment of parameters (e.g., heart rate, pulse waveform, and peripheral perfusion) that can indicate conditions such as vasoconstriction or vasodilation, and provides information about microvascular blood flow, making it a valuable tool for monitoring cardiovascular health. However, PPG is subject to a number of sources of variations that can impact its accuracy and reliability, especially when using a wearable device for continuous monitoring, such as motion artifacts, skin pigmentation, and vasomotion. In this study, we extracted 27 statistical features from the PPG signal for training machine-learning models based on gradient boosting (XGBoost and CatBoost) and Random Forest (RF) algorithms to assess quality of PPG signals that were labeled as good or poor quality. We used the PPG time series from a publicly available dataset and evaluated the algorithm s performance using Sensitivity (Se), Positive Predicted Value (PPV), and F1-score (F1) metrics. Our model achieved Se, PPV, and F1-score of 94.4, 95.6, and 95.0 for XGBoost, 94.7, 95.9, and 95.3 for CatBoost, and 93.7, 91.3 and 92.5 for RF, respectively. Our findings are comparable to state-of-the-art reported in the literature but using a much simpler model, indicating that ML models are promising for developing remote, non-invasive, and continuous measurement devices.

Amanda J. Lea, Andrew G. Clark, Andrew W. Dahl et al.

Globally, we are witnessing the rise of complex, non-communicable diseases (NCDs) related to changes in our daily environments. Obesity, asthma, cardiovascular disease, and type 2 diabetes are part of a long list of "lifestyle" diseases that were rare throughout human history but are now common. A key idea from anthropology and evolutionary biology--the evolutionary mismatch hypothesis--seeks to explain this phenomenon. It posits that humans evolved in environments that radically differ from the ones experienced by most people today, and thus traits that were advantageous in past environments may now be "mismatched" and disease-causing. This hypothesis is, at its core, a genetic one: it predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions and have differential health effects in ancestral versus modern environments. Here, we discuss how this concept could be leveraged to uncover the genetic architecture of NCDs in a principled way. Specifically, we advocate for partnering with small-scale, subsistence-level groups that are currently transitioning from environments that are arguably more "matched" with their recent evolutionary history to those that are more "mismatched". These populations provide diverse genetic backgrounds as well as the needed levels and types of environmental variation necessary for mapping GxE interactions in an explicit mismatch framework. Such work would make important contributions to our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and sociocultural contexts.

Zeynep Hilal Kilimci, Mustafa Yalcin, Ayhan Kucukmanisa et al.

Heart disease, also known as cardiovascular disease, is a prevalent and critical medical condition characterized by the impairment of the heart and blood vessels, leading to various complications such as coronary artery disease, heart failure, and myocardial infarction. The timely and accurate detection of heart disease is of paramount importance in clinical practice. Early identification of individuals at risk enables proactive interventions, preventive measures, and personalized treatment strategies to mitigate the progression of the disease and reduce adverse outcomes. In recent years, the field of heart disease detection has witnessed notable advancements due to the integration of sophisticated technologies and computational approaches. These include machine learning algorithms, data mining techniques, and predictive modeling frameworks that leverage vast amounts of clinical and physiological data to improve diagnostic accuracy and risk stratification. In this work, we propose to detect heart disease from ECG images using cutting-edge technologies, namely vision transformer models. These models are Google-Vit, Microsoft-Beit, and Swin-Tiny. To the best of our knowledge, this is the initial endeavor concentrating on the detection of heart diseases through image-based ECG data by employing cuttingedge technologies namely, transformer models. To demonstrate the contribution of the proposed framework, the performance of vision transformer models are compared with state-of-the-art studies. Experiment results show that the proposed framework exhibits remarkable classification results.

Guido Iaccarino

Yoichi Kawahira, Takashi Shibuya, Akira Tomokuni et al.

We herein reported an extremely rare adult case with a congenitally absent superior mesenteric artery associated with polysplenia, who successfully underwent aneurysmectomy and revascularization for superior mesenteric artery aneurysm. To investigate the major splanchnic arteries before a laparotomy in polysplenia patients might be needed to prevent rare but life-threatening complications.

Michael P. O’Shea, Suganya Arunachalam Karikalan, Ali Yusuf et al.

Abstract Background Immune checkpoint inhibitor (ICI) myocarditis is associated with significant mortality risk. Electrocardiogram (ECG) changes in ICI myocarditis have strong prognostic value. However the impact of complete heart block (CHB) is not well defined. This study sought to evaluate the impact of CHB on mortality in ICI myocarditis, and to identify clinical predictors of mortality and CHB incidence. Methods We conducted a retrospective cohort study of patients with ICI myocarditis at three Mayo Clinic sites from 1st January 2010 to 31st September 2022 to evaluate mortality rates at 180 days. Clinical, laboratory, ECG, echocardiographic, and cardiac magnetic resonance imaging (CMR) characteristics were assessed. Cox and logistic regression were performed for associations with mortality and CHB respectively. Results Of 34 identified cases of ICI myocarditis, 7 (20.6%) had CHB. CHB was associated with higher mortality (HR 7.41, p = 0.03, attributable fraction 86.5%). Among those with CHB, troponin T (TnT) < 1000 ng/dL, low white blood cell count and high ventricular rate at admission were protective. There was trend towards increased survival among patients who underwent permanent pacemaker insertion (p = 0.051), although most experienced device lead complications. Factors associated with development of CHB included prolonged PR and QRS intervals and low Sokolow Lyon Index. Where these were normal and TnT was < 1000 ng/dL, no deaths occurred. Impaired myocardial longitudinal strain was sensitive for ICI myocarditis but was not prognostically significant. Conclusion There is a strong temporal association between CHB and early mortality in people with ICI myocarditis. Focusing on arrhythmogenic complications can be helpful in predicting outcomes for this group of critically ill individuals.

Suddharsan Dhanakoti Subbramaniyam, Nooraldaem Yousif, Sadananda Shivappa et al.

Spontaneous coronary artery dissection (SCAD) is an uncommon cause of acute myocardial ischemia. SCAD complicated by coronary artery aneurysm (CAA) is rare and seldom reported. Coronary angiography is the gold standard for the diagnosis of SCAD. However, an obscure intimal flap may not be recognized with a conventional coronary angiogram, and intravascular imaging modalities are important in the diagnosis of SCAD. Optical coherence tomography contributes to providing information about the size, shape, and location of CAAs. Herein, we are presenting a challenging and unique case of a woman presenting with SCAD complicated by a CAA.

Ying Xiao, Zhengqing Ba, Shurui Pang et al.

Lipid-lowering therapy is of great importance in reducing the burden of atherosclerotic cardiovascular disease. Statins act as first-line therapy in the current lipid management guidelines. However, statin use is limited in (1) statin-induced adverse events, including statin-associated muscle symptoms, new-onset diabetes mellitus, drug-induced liver injuries, acute kidney injuries, cognitive effects, hemorrhagic strokes, and cataracts; (2) special populations, including pregnant and lactating patients, patients with decompensated cirrhosis, and patients on dialysis; (3) coadministration with statin-interactive drugs, such as anti-human immunodeficiency virus drugs, anti-hepatitis C virus drugs, and immunosuppressive drugs. These considerable statin-limited groups are in urgent need of safer alternative lipid-lowering options. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors are attracting widespread attention for their documented safety in general populations and superior lipid-lowering properties. Therefore, questions have been raised whether PCSK9 inhibitors could be a safe alternative in patients who are intolerant to statin therapy. In this review, we discuss the safety of PCSK9 inhibitors in statin-limited conditions. We conclude that PCSK9 inhibitors are a safe alternative lipid-lowering therapy in various statin-limited conditions. Furthermore, we identify several limitations in the current literature and suggest future directions, for the refinement of lipid management regimens.