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

Anísio Uchoa Leite Santana, Samuel Katsuyuki Shinjo

Resumo Fundamento As associações clínicas e de imagem iniciais na arterite de Takayasu (AT) são pouco definidas. Objetivos Caracterizar as manifestações iniciais, suas associações e os resultados a longo prazo em uma coorte de pacientes com AT. Métodos Um estudo de coorte retrospectivo unicêntrico (2000 a 2024) incluiu pacientes diagnosticados com AT. O nível de significância foi definido em p<0,05. Resultados Dos 203 pacientes identificados, 54 foram excluídos devido a dados incompletos. A coorte final foi composta por 149 pacientes (89,9% do sexo feminino), com mediana de idade ao diagnóstico de 31 anos. Ao diagnóstico, 92,6% apresentavam sintomas. A claudicação dos membros superiores (36,2%) e inferiores (30,9%) foi frequente, juntamente com lesão vascular avançada, como estenose (85,9%) e oclusões (52,3%). A claudicação dos membros superiores foi predita independentemente pela redução dos pulsos nos membros superiores (OR=4,83; IC 95%=2,08-11,24; p=0,001) e pela oclusão da artéria subclávia direita (OR=8,06; IC 95%=1,94-33,44; p=0,004). A claudicação dos membros inferiores foi prevista pela oclusão da artéria subclávia direita (OR=6,65; IC 95%=2,05-21,61; p=0,002), espessamento da artéria subclávia direita (OR=5,12; IC 95%=1,18-22,71; p=0,029) e estenose da artéria subclávia esquerda (OR=2,71; IC 95%=1,21-60,56; p=0,016). Durante um acompanhamento mediano de 10 anos, apesar da remissão em 91,3% dos casos, houve aumento das comorbidades cardiovasculares e 26,8% dos pacientes necessitaram de cirurgia. Conclusões A claudicação intermitente dos membros é um importante indicador prognóstico de lesão radiológica avançada e atraso no diagnóstico. Isso é reforçado pela dissociação a longo prazo entre alta remissão clínica e doença vascular progressiva, o que exige monitoramento vigilante.

Giang Pham, Rebecca Finetti, Caterina Graziani et al.

Alkaptonuria (AKU) is an ultra-rare autosomal recessive metabolic disorder caused by mutations in the HGD (Homogentisate 1,2-Dioxygenase) gene, leading to a pathological accumulation of homogentisic acid (HGA) in body fluids and tissues. This leads to systemic manifestations, including premature spondyloarthropathy, renal and prostatic stones, and cardiovascular complications. Being ultra-rare, the amount of data related to the disease is limited, both in terms of clinical data and literature. Knowledge graphs (KGs) can help connect the limited knowledge about the disease (basic mechanisms, manifestations and existing therapies) with other knowledge; however, AKU is frequently underrepresented or entirely absent in existing biomedical KGs. In this work, we apply a text-mining methodology based on PubTator3 for large-scale extraction of biomedical relations. We construct two KGs of different sizes, validate them using existing biochemical knowledge and use them to extract genes, diseases and therapies possibly related to AKU. This computational framework reveals the systemic interactions of the disease, its comorbidities, and potential therapeutic targets, demonstrating the efficacy of our approach in analyzing rare metabolic disorders.

Richard Dorent, Julien Guihaire, Thomas Kerforne et al.

Marnie K. McLean, MS, Bradley J. Petek, MD, Lidija McGrath, MD et al.

The purpose of this narrative review was to summarize perinatal exercise guidelines and associations of perinatal physical activity and/or exercise with cardiovascular disease (CVD) risk. Observational studies, randomized controlled trials, systematic reviews, and meta-analyses were included. Gaps in literature and suggestions for future studies were identified. Despite concordant international guidelines, data to support nuanced activity advice for some subgroups are limited. Perinatal physical activity and exercise are consistently recommended to combat traditional CVD risk factors during the perinatal period, like excessive gestational weight gain, high blood pressure, and high blood glucose. Physical activity and exercise appear to improve nontraditional risk factors such as poor sleep and depression. Data are emerging regarding associations with some pregnancy-specific factors, such as placental characteristics. Further research investigating associations with pregnancy-specific CVD risk factors and associations in the longer term, as well as data to support uptake, adherence, and resistance exercise prescription is warranted.

Zi Wang, Mingkai Huang, Zhang Shi et al.

Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD) diagnosis and underlying mechanisms. Despite decades of advancements, its widespread clinical adoption remains constrained by prolonged scan times and heterogeneity across medical environments. This underscores the urgent need for a generalist reconstruction foundation model for ultra-fast CMR imaging, one capable of adapting across diverse imaging scenarios and serving as the essential substrate for all downstream analyses. To enable this goal, we curate MMCMR-427K, the largest and most comprehensive multimodal CMR k-space database to date, comprising 427,465 multi-coil k-space data paired with structured metadata across 13 international centers, 12 CMR modalities, 15 scanners, and 17 CVD categories in populations across three continents. Building on this unprecedented resource, we introduce CardioMM, a generalist reconstruction foundation model capable of dynamically adapting to heterogeneous fast CMR imaging scenarios. CardioMM unifies semantic contextual understanding with physics-informed data consistency to deliver robust reconstructions across varied scanners, protocols, and patient presentations. Comprehensive evaluations demonstrate that CardioMM achieves state-of-the-art performance in the internal centers and exhibits strong zero-shot generalization to unseen external settings. Even at imaging acceleration up to 24x, CardioMM reliably preserves key cardiac phenotypes, quantitative myocardial biomarkers, and diagnostic image quality, enabling a substantial increase in CMR examination throughput without compromising clinical integrity. Together, our open-access MMCMR-427K database and CardioMM framework establish a scalable pathway toward high-throughput, high-quality, and clinically accessible cardiovascular imaging.

Kui Li, Xueyuan Yang, Yunhang Li et al.

Abstract Background The stress hyperglycaemic ratio (SHR), a new marker that reflects the true hyperglycaemic state of patients with acute coronary syndrome (ACS), is strongly associated with adverse clinical outcomes in these patients. Studies on the relationship between the SHR and in-hospital cardiac arrest (IHCA) incidence are limited. This study elucidated the relationship between the SHR and incidence of IHCA in patients with ACS. Methods In total, 1,939 patients with ACS who underwent percutaneous coronary intervention (PCI) at the Affiliated Hospital of Zunyi Medical University were included. They were divided into three groups according to the SHR: group T1 (SHR ≤ 0.838, N = 646), group T2 (0.838< SHR ≤ 1.140, N = 646), and group T3 (SHR3 > 1.140, N = 647). The primary endpoint was IHCA incidence. Results The overall IHCA incidence was 4.1% (N = 80). After adjusting for covariates, SHR was significantly associated with IHCA incidence in patients with ACS who underwent PCI (odds ratio [OR] =  2.6800; 95% confidence interval [CI] =  1.6200–4.4300; p<0.001), and compared with the T1 group, the T3 group had an increased IHCA risk (OR =  2.1800; 95% CI =  1.2100–3.9300; p =  0.0090). In subgroup analyses, after adjusting for covariates, patients with ST-segment elevation myocardial infarction (STEMI) (OR =  3.0700; 95% CI =  1.4100–6.6600; p =  0.0050) and non-STEMI (NSTEMI) (OR =  2.9900; 95% CI =  1.1000–8.1100; p =  0.0310) were at an increased IHCA risk. After adjusting for covariates, IHCA risk was higher in patients with diabetes mellitus (DM) (OR =  2.5900; 95% CI =  1.4200–4.7300; p =  0.0020) and those without DM (non-DM) (OR =  3.3000; 95% CI =  1.2700–8.5800; p =  0.0140); patients with DM in the T3 group had an increased IHCA risk compared with those in the T1 group (OR =  2.4200; 95% CI =  1.0800–5.4300; p =  0.0320). The restriction cubic spline (RCS) analyses revealed a dose-response relationship between IHCA incidence and SHR, with an increased IHCA risk when SHR was higher than 1.773. Adding SHR to the baseline risk model improved the predictive value of IHCA in patients with ACS treated with PCI (net reclassification improvement [NRI]: 0.0734 [0.0058–0.1409], p =  0.0332; integrated discrimination improvement [IDI]: 0.0218 [0.0063–0.0374], p =  0.0060). Conclusions In patients with ACS treated with PCI, the SHR was significantly associated with the incidence of IHCA. The SHR may be a useful predictor of the incidence of IHCA in patients with ACS. The addition of the SHR to the baseline risk model had an incremental effect on the predictive value of IHCA in patients with ACS treated with PCI.

Isabel C. Sánchez-Escobar, Silvia J. Galvis-Blanco, Luis H. Díaz-Medina et al.

Antecedentes: Los aneurismas de la aorta ascendente son patologías poco frecuentes en la infancia, sobre todo en ausencia de enfermedades previas como el síndrome de Marfan. Objetivo: Dar a conocer la posibilidad del manejo endovascular exitoso de los aneurismas de grandes vasos, usando stent y micro catéter con embolización del saco aneurismático. Método: Presentamos el caso de una paciente de 10 años y 2 meses, previamente sana, en quien se documentó un pseudoaneurisma entre el origen de la arteria carótida común izquierda y la arteria subclavia izquierda, que logró manejarse de forma endovascular, inicialmente con un stent cubriendo el cuello del aneurisma con el fin de remodelarlo y posteriormente por medio de microcatéter se realizó embolización del saco del aneurisma con coils, con resultado exitoso. Resultados: Los aneurismas de los grandes vasos, como la arteria carótida común y la arteria subclavia, tienen riesgo de ruptura con complicaciones devastadoras; el manejo endovascular se plantea como una opción poco invasiva de manejo, con resultados favorables. Conclusión: El manejo de aneurismas de grandes vasos, por vía endovascular usando stent y microcatéter con embolización del saco aneurismático, es una opción novedosa de manejo que logra resultados exitosos.

Richard Kazibwe, Muhammad Imtiaz Ahmad, Sanjay Singh et al.

ABSTRACT Background Silent myocardial infarction (SMI) frequently goes undetected, yet it is associated with increased cardiovascular morbidity and mortality. The impact of intensive systolic blood pressure (SBP) lowering on the risk of SMI in those with hypertension remains uncertain. Methods In this post hoc analysis of the Systolic Blood Pressure Intervention Trial (SPRINT), participants with serial electrocardiograms (ECGs) during the trial were included. SPRINT investigated the benefit of intensive SBP lowering, aiming for < 120 mmHg compared to the standard SBP goal of < 140 mmHg. Incident SMI was defined as evidence of new MI on an ECG without adjudicated recognized myocardial infarction (RMI). Results During a median follow‐up of 3.9 years, a total of 234 MI events (55 SMI and 179 RMI) occurred. Intensive, compared to standard, SBP lowering resulted in a lower rate of SMI (incidence rate 1.1 vs. 2.3 cases per 1000 person‐years, respectively; HR [95% CI]: 0.48 [0.27–0.84]). Similarly, intensive, compared to standard, BP lowering reduced the risk of RMI (incidence rate 4.6 vs. 6.5 cases per 1000 person‐years, respectively; HR [95% CI]: 0.71 [0.52–0.95]). No significant differences were noted between the strength of the association of intensive BP control on lowering the risk of SMI and RMI (p‐value for HR differences = 0.23). Conclusions This study shows that in adults with hypertension, the benefits of intensive SBP lowering, compared with standard BP lowering, go beyond the prevention of RMI to include the prevention of SMI. Trial Registration ClinicalTrials.gov Identifier: NCT01206062.

Bimarsha Khanal, Paras Poudel, Anish Chapagai et al.

Plant diseases significantly impact our food supply, causing problems for farmers, economies reliant on agriculture, and global food security. Accurate and timely plant disease diagnosis is crucial for effective treatment and minimizing yield losses. Despite advancements in agricultural technology, a precise and early diagnosis remains a challenge, especially in underdeveloped regions where agriculture is crucial and agricultural experts are scarce. However, adopting Deep Learning applications can assist in accurately identifying diseases without needing plant pathologists. In this study, the effectiveness of various computer vision models for detecting paddy diseases is evaluated and proposed the best deep learning-based disease detection system. Both classification and detection using the Paddy Doctor dataset, which contains over 20,000 annotated images of paddy leaves for disease diagnosis are tested and evaluated. For detection, we utilized the YOLOv8 model-based model were used for paddy disease detection and CNN models and the Vision Transformer were used for disease classification. The average mAP50 of 69% for detection tasks was achieved and the Vision Transformer classification accuracy was 99.38%. It was found that detection models are effective at identifying multiple diseases simultaneously with less computing power, whereas classification models, though computationally expensive, exhibit better performance for classifying single diseases. Additionally, a mobile application was developed to enable farmers to identify paddy diseases instantly. Experiments with the app showed encouraging results in utilizing the trained models for both disease classification and treatment guidance.

Elham Baradari and, Ozgur B Akan

Parkinson's disease (PD) is a progressive neurodegenerative disease, and it is caused by the loss of dopaminergic neurons in the basal ganglia (BG). Currently, there is no definite cure for PD, and available treatments mainly aim to alleviate its symptoms. Due to impaired neurotransmitter-based information transmission in PD, molecular communication-based approaches can be employed as potential solutions to address this issue. Molecular Communications (MC) is a bio-inspired communication method utilizing molecules for carrying information. This mode of communication stands out for developing bio-compatible nanomachines for diagnosing and treating, particularly in addressing neurodegenerative diseases like PD, due to its compatibility with biological systems. This study presents a novel treatment method that introduces an Intelligent Dopamine Rate Modulator (IDRM), which is located in the synaptic gap between the substantia nigra pars compacta (SNc) and striatum to compensate for insufficiency dopamine release in BG caused by PD. For storing dopamine in the IDRM, dopamine compound (DAC) is swallowed and crossed through the digestive system, blood circulatory system, blood-brain barrier (BBB), and brain extracellular matrix uptakes with IDRMs. Here, the DAC concentration is calculated in these regions, revealing that the required exogenous dopamine consistently reaches IDRM. Therefore, the perpetual dopamine insufficiency in BG associated with PD can be compensated. This method reduces drug side effects because dopamine is not released in other brain regions. Unlike other treatments, this approach targets the root cause of PD rather than just reducing symptoms.

Grace Guo, Lifu Deng, Animesh Tandon et al.

The recent prevalence of publicly accessible, large medical imaging datasets has led to a proliferation of artificial intelligence (AI) models for cardiovascular image classification and analysis. At the same time, the potentially significant impacts of these models have motivated the development of a range of explainable AI (XAI) methods that aim to explain model predictions given certain image inputs. However, many of these methods are not developed or evaluated with domain experts, and explanations are not contextualized in terms of medical expertise or domain knowledge. In this paper, we propose a novel framework and python library, MiMICRI, that provides domain-centered counterfactual explanations of cardiovascular image classification models. MiMICRI helps users interactively select and replace segments of medical images that correspond to morphological structures. From the counterfactuals generated, users can then assess the influence of each segment on model predictions, and validate the model against known medical facts. We evaluate this library with two medical experts. Our evaluation demonstrates that a domain-centered XAI approach can enhance the interpretability of model explanations, and help experts reason about models in terms of relevant domain knowledge. However, concerns were also surfaced about the clinical plausibility of the counterfactuals generated. We conclude with a discussion on the generalizability and trustworthiness of the MiMICRI framework, as well as the implications of our findings on the development of domain-centered XAI methods for model interpretability in healthcare contexts.

Cécile Trottet, Manuel Schürch, Ahmed Allam et al.

We propose a deep generative approach using latent temporal processes for modeling and holistically analyzing complex disease trajectories, with a particular focus on Systemic Sclerosis (SSc). We aim to learn temporal latent representations of the underlying generative process that explain the observed patient disease trajectories in an interpretable and comprehensive way. To enhance the interpretability of these latent temporal processes, we develop a semi-supervised approach for disentangling the latent space using established medical knowledge. By combining the generative approach with medical definitions of different characteristics of SSc, we facilitate the discovery of new aspects of the disease. We show that the learned temporal latent processes can be utilized for further data analysis and clinical hypothesis testing, including finding similar patients and clustering SSc patient trajectories into novel sub-types. Moreover, our method enables personalized online monitoring and prediction of multivariate time series with uncertainty quantification.

O. A. Osipova, R. N. Shepel, R. Yu. Shevtsov et al.

Coronary artery disease is the most common cause of death world­wide. On­pump coronary artery bypass grafting and cardioplegia remains the gold standard for the treatment of multivessel coronary disease. However, this method of surgical treatment has a number of perioperative complications, the most common of which is post­operative cognitive dysfunction (POCD).Aim. To develop a mathematical model for predicting the binary outcome "presence/absence of POCD deterioration" using Mini­Mental State Examination (MMSE) and Frontal Assessment Battery (FAB) for timely prevention of cognitive impairment in the early postoperative period.Material and methods. The study included 180 patients with coronary artery disease with stable angina who underwent on­pump coronary artery bypass grafting. The patients’ age [Me (Q25­-Q75)] was 62 [56­-67] years. After the operation, all patients were divided into 2 groups: 108 patients without POCD and 72 patients with cognitive deficit of various severity. The study was conducted in three stages: stage I — 2 days before surgery; stage II — during the operation; stage III — 7 days after the operation. Assessment of cognitive status using FAB, MMSE tests was carried out at stages I and III. At the second stage, biochemical parameters were assessed: in arterial blood — lactate and hemoglobin levels, in venous blood — pH, partial pressure of carbon dioxide (pCO2, mm Hg) and partial pressure of oxygen (pO2, mm Hg), as well as the duration of operation, cardiopulmonary bypass and myocardial anoxia. Discriminant analysis was used to develop a mathematical model for predicting a binary outcome.Results. Two groups of the most informative indicators were identified that were included in prediction algorithms for binary outcomes "presence/absence of negative dynamics of POCD" for MMSE and FAB. Group 1 included perioperative MMSE values, atrial fibrillation before surgery, cardiopulmonary bypass time and pO2. Group 2 included cardiopulmonary bypass time and intraoperative venous pH. Conclusion. Mathematical models have been developed for predicting the binary outcome "presence/absence of POCD deterioration" ac­cording to the MMSE and FAB cognitive tests, which make it possible to assess the possibility of postoperative cognitive dysfunction. The proposed algorithms are implemented using spreadsheets and a computer program.

Yasaman Torabi, Shahram Shirani, James P. Reilly

Auscultation provides a rich diversity of information to diagnose cardiovascular and respiratory diseases. However, sound auscultation is challenging due to noise. In this study, a modified version of the affine non-negative matrix factorization (NMF) approach is proposed to blindly separate lung and heart sounds recorded by a digital stethoscope. This method applies a novel NMF algorithm, which embodies a parallel structure of multilayer units on the input signal, to find a proper estimation of source signals. Another key innovation is the use of the periodic property of the signals which improves accuracy compared to previous works. The method is tested on 100 cases. Each case consists of two synthesized mixtures of real measurements. The effect of different parameters is discussed, and the results are compared to other current methods. Results demonstrate improvements in the source-to-distortion ratio (SDR), source-to-interference ratio (SIR), and source-to-artifacts ratio (SAR) of heart and lung sounds, respectively.

Cuncun Hua, Qizhe Cai, Xiao-Ying Xi et al.

BackgroundWhether perfusion/metabolism imaging differs between matched ST-segment elevation myocardial infarction (STEMI) patients with and without cardiogenic shock (CS) remains unknown.MethodsSeventeen STEMI patients with CS (13 men, 60 ± 12 years) and 16 matched STEMI patients without CS (15 men, 54 ± 15 years) were prospectively recruited. All patients underwent baseline 99mTc-sestamibi/18F-fluorodeoxyglucose (FDG) imaging and echocardiography 6 ± 2 days post-infarction. Nine patients with CS and seven without CS had repeated imaging 98 ± 7 days post-infarction. The total perfusion deficit (TPD) and total FDG uptake deficit (TFD) were calculated to assess the percentages of impaired perfusion and metabolism over the left ventricle. Patients were followed up for 337 days (213–505 days) and the major adverse cardiac events (MACE) were recorded.ResultsTPD was greater in patient with CS and was independently related to the presence of CS (OR: 4.36, p = 0.013). Both acute- and convalescent TFD were inversely related to the improvement ratio of LVEF (r-values: −0.62, −0.73; both p &lt; 0.05). MACE occurred in 16 patients (10 CS and 6 non-CS), and acute TFD was predictive of MACE in those with CS (HR: 2.06, p = 0.038).ConclusionIn this pilot study, we demonstrated that STEMI patients with CS had a significantly increased TPD, which was relevant to the presence of CS. Acute TFD was associated with improvement in LVEF, and was predictive of MACE in patients with CS.

Praveen Sridhar, MD, Brian Mitzman, MD

Julien Guihaire, Simon Dang Van

Zhengyang Chen, Bing Han, Xu Xiang et al.

This report describes the SJTU-AISPEECH system for the Voxceleb Speaker Recognition Challenge 2022. For track1, we implemented two kinds of systems, the online system and the offline system. Different ResNet-based backbones and loss functions are explored. Our final fusion system achieved 3rd place in track1. For track3, we implemented statistic adaptation and jointly training based domain adaptation. In the jointly training based domain adaptation, we jointly trained the source and target domain dataset with different training objectives to do the domain adaptation. We explored two different training objectives for target domain data, self-supervised learning based angular proto-typical loss and semi-supervised learning based classification loss with estimated pseudo labels. Besides, we used the dynamic loss-gate and label correction (DLG-LC) strategy to improve the quality of pseudo labels when the target domain objective is a classification loss. Our final fusion system achieved 4th place (very close to 3rd place, relatively less than 1%) in track3.

L. David

Diabetes mellitus (DM) has an increasing prevalence worldwide, it is a well-known risk factor for cardiovascular diseases. Vascular complications of diabetes are important causes of morbidity and mortality among diabetic patients. Venous thromboembolism (VTE) is the third most common circulatory disorder in Western populations, and pulmonary embolism the third most common cause of death from cardiovascular disease after heart attack and stroke.Diabetes may facilitate thrombosis through activation of the coagulation system and impairing fibrinolysis, thus leading to a hypercoagulable state and is coupled with other prothrombotic factors such as chronic inflammation, enhanced oxidative stress, and decreased expression of protective endothelial factors. Several epidemiological and clinical studies have investigated the correlation between DM and VTE, but the results were conflicting. Some reported a positive association between diabetes and risk of VTE, whereas others failed to detect a significant relationship. This review summarize the current state of the literature on the link between diabetes and risk of VTE.

Yu. A. Vasyuk, E. Yu. Shupenina, G. A. Namazova et al.

Heart failure with preserved ejection fraction (HFpEF) is a complex clinical syndrome associated with frequent hospitalizations, high mortality rates, and an absence of proven effective therapy. This type of heart failure is often accompanied by comorbidity that complicate the diagnosis of the underlying disease. The algorithm developed in 2016 does not take into account the heterogeneity of patients and course of HFpEF. Recently, new diagnostic algorithms (H2FPEF, HFA-PEFF) and biomarkers have appeared that allow detecting HFpEF at an early stage, taking into account the pathogenesis, which may contribute to development of new effective treatment methods.