-
Texas Heart Institute Journal Jun 2024
Topics: Humans; Hemodynamics; Heart-Assist Devices; Aorta; Models, Cardiovascular; Computer Simulation; Blood Vessel Prosthesis Implantation; Heart Failure
PubMed: 38917113
DOI: 10.14503/THIJ-24-8472 -
Frontiers in Medicine 2024[This corrects the article DOI: 10.3389/fmed.2024.1285067.].
[This corrects the article DOI: 10.3389/fmed.2024.1285067.].
PubMed: 38915763
DOI: 10.3389/fmed.2024.1431299 -
BMC Medical Informatics and Decision... Jun 2024With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges. Various studies have emerged utilizing Artificial Intelligence (AI)...
With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges. Various studies have emerged utilizing Artificial Intelligence (AI) and Data Science techniques for disease detection. Although COVID-19 cases have declined, there are still cases and deaths around the world. Therefore, early detection of COVID-19 before the onset of symptoms has become crucial in reducing its extensive impact. Fortunately, wearable devices such as smartwatches have proven to be valuable sources of physiological data, including Heart Rate (HR) and sleep quality, enabling the detection of inflammatory diseases. In this study, we utilize an already-existing dataset that includes individual step counts and heart rate data to predict the probability of COVID-19 infection before the onset of symptoms. We train three main model architectures: the Gradient Boosting classifier (GB), CatBoost trees, and TabNet classifier to analyze the physiological data and compare their respective performances. We also add an interpretability layer to our best-performing model, which clarifies prediction results and allows a detailed assessment of effectiveness. Moreover, we created a private dataset by gathering physiological data from Fitbit devices to guarantee reliability and avoid bias.The identical set of models was then applied to this private dataset using the same pre-trained models, and the results were documented. Using the CatBoost tree-based method, our best-performing model outperformed previous studies with an accuracy rate of 85% on the publicly available dataset. Furthermore, this identical pre-trained CatBoost model produced an accuracy of 81% when applied to the private dataset. You will find the source code in the link: https://github.com/OpenUAE-LAB/Covid-19-detection-using-Wearable-data.git .
Topics: Humans; COVID-19; Artificial Intelligence; Early Diagnosis; Heart Rate; Wearable Electronic Devices
PubMed: 38915001
DOI: 10.1186/s12911-024-02576-2 -
JACC. Case Reports Jul 2024An 82-year-old patient experienced symptomatic intra-prosthetic aortic regurgitation 5 years after self-expandable transcatheter heart valve (THV) implantation....
An 82-year-old patient experienced symptomatic intra-prosthetic aortic regurgitation 5 years after self-expandable transcatheter heart valve (THV) implantation. Redo-transcatheter aortic valve replacement was initially considered at high risk of coronary obstruction. Using a systematic computed tomography-based approach planning a low implantation with a SAPIEN 3 Ultra THV, we effectively mitigated risks.
PubMed: 38912321
DOI: 10.1016/j.jaccas.2024.102388 -
Journal of Clinical Lipidology Apr 2024The International Atherosclerosis Society (IAS) published an evidence-informed guidance for familial hypercholesterolemia (FH) that provides both clinical and...
BACKGROUND
The International Atherosclerosis Society (IAS) published an evidence-informed guidance for familial hypercholesterolemia (FH) that provides both clinical and implementation recommendations. We reference examples of strategies from the literature to explore how these implementation recommendations can be tailored into implementation strategies at the local-level for stakeholders guided by a framework proposed by Sarkies and Jones.
METHODS
Four authors of the IAS guidance selected two published exemplar implementation recommendations for detection, management, and general implementation. Each recommendation was described as an implementation strategy using Proctor's guidance for specifying and reporting implementation strategies. It recommends reporting the actor (who), action (what), action-target (who is impacted), temporality (how often), and dose (how much) for each implementation strategy.
RESULTS
Detection: A centralized cascade testing model, mobilized nurses (actor) to relative's homes, after the diagnosis of the proband (temporality), once (dose) to consent, obtain a blood sample and health information (action) on relatives (action-target).
MANAGEMENT
A primary care initiative to improve FH management included an educational session (action) with clinicians (action-target), computer-based reminder message and message to patients to have their cholesterol screened once (dose) at a visit or outreach (temporality) by researchers (actor). General: A partnership between a statewide public pathology provider, local public hospital network, primary health network, government health ministry, and an academic university (actors) was established to implement a primary-tertiary shared care model (action) to improve the detection of FH (action-target).
CONCLUSIONS
We demonstrate that implementation recommendations can be specified and reported for different local contexts with examples on monitoring, evaluation, and sustainability in practice.
PubMed: 38910104
DOI: 10.1016/j.jacl.2024.03.010 -
Journal of Cardiovascular Magnetic... Jun 2024Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and... (Review)
Review
Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently advancements in artificial intelligence (AI) technology have shown great potential to address many CMR limitations. While the developments are remarkable, translation of AI-based methods into real-world CMR clinical practice remains at a nascent stage and much work lies ahead to realize the full potential of AI for CMR. Herein we review recent cutting-edge and representative examples demonstrating how AI can advance CMR in areas such as exam planning, accelerated image reconstruction, post-processing, quality control, classification and diagnosis. These advances can be applied to speed up and simplify essentially every application including cine, strain, late gadolinium enhancement, parametric mapping, 3D whole heart, flow, perfusion and others. AI is a unique technology based on training models using data. Beyond reviewing the literature, this paper discusses important AI-specific issues in the context of CMR, including (1) properties and characteristics of datasets for training and validation, (2) previously published guidelines for reporting CMR AI research, (3) considerations around clinical deployment, (4) responsibilities of clinicians and the need for multi-disciplinary teams in the development and deployment of AI in CMR, (5) industry considerations, and (6) regulatory perspectives. Understanding and consideration of all these factors will contribute to the effective and ethical deployment of AI to improve clinical CMR.
PubMed: 38909656
DOI: 10.1016/j.jocmr.2024.101051 -
The Canadian Journal of Cardiology Jun 2024
PubMed: 38908789
DOI: 10.1016/j.cjca.2024.06.014 -
Cardiovascular Diabetology Jun 2024Pretransplant type 2 diabetes mellitus (T2DM) is associated with increased cardiovascular and all-cause mortality after heart transplant (HT), but the underlying causes...
BACKGROUND
Pretransplant type 2 diabetes mellitus (T2DM) is associated with increased cardiovascular and all-cause mortality after heart transplant (HT), but the underlying causes of this association remain unclear. The purpose of this research was to examine the impact of T2DM on left ventricular (LV) myocardial deformation and myocardial perfusion following heart transplantation using cardiovascular magnetic resonance imaging.
METHODS
We investigated thirty-one HT recipients with pretransplant T2DM [HT(DM+)], thirty-four HT recipients without pretransplant T2DM [HT(DM-)] and thirty-six controls. LV myocardial strains, including the global longitudinal, radial, and circumferential strain (GLS, GRS and GCS, respectively), were calculated and compared among groups, as were resting myocardial perfusion indices, which included time to peak myocardial signal intensity (TTM), maximum signal intensity (MaxSI), and Upslope. The relationships between LV strain parameters or perfusion indices and biochemical indicators were determined through Spearman's analysis. The impact of T2DM on LV strains in HT recipients was assessed using multivariable linear regression analyses with backward stepwise selection.
RESULTS
In the HT(DM+) group, the LV GLS, GRS, and GCS exhibited significantly lower magnitudes than those in both the HT(DM-) and control groups. TTM was higher in the HT(DM+) group than in both the HT(DM-) and control groups, while no significant differences were observed among the groups regarding Upslope and MaxSI. There was a negative correlation between glycated hemoglobin and the magnitude of strains (longitudinal, r = - 0.399; radial, r = - 0.362; circumferential, r = - 0.389) (all P < 0.05), and a positive correlation with TTM (r = 0.485, P < 0.001). Regression analyses that included both pretransplant T2DM and perfusion indices revealed that pretransplant T2DM, rather than perfusion indices, was an independent determinant of LV strain (β = longitudinal, - 0.508; radial, - 0.370; circumferential, - 0.371) (all P < 0.05).
CONCLUSION
In heart transplant recipients, pretransplant T2DM has a detrimental effect on subclinical left ventricular systolic function and could potentially impact myocardial microcirculation following HT.
Topics: Humans; Heart Transplantation; Male; Middle Aged; Female; Ventricular Function, Left; Diabetes Mellitus, Type 2; Myocardial Perfusion Imaging; Predictive Value of Tests; Ventricular Dysfunction, Left; Coronary Circulation; Treatment Outcome; Adult; Magnetic Resonance Imaging, Cine; Risk Factors; Aged; Case-Control Studies; Time Factors; Biomechanical Phenomena; Biomarkers; Myocardial Contraction
PubMed: 38907259
DOI: 10.1186/s12933-024-02323-x -
Frontiers in Sports and Active Living 2024The present study aimed to evaluate the effect of acute aerobic exercise on certain cognitive functions known to be affected by Alzheimer's disease (AD), with a...
INTRODUCTION
The present study aimed to evaluate the effect of acute aerobic exercise on certain cognitive functions known to be affected by Alzheimer's disease (AD), with a particular emphasis on sex differences.
METHODS
A total of 53 patients, with a mean age of 70.54 ± 0.88 years and moderate AD, voluntarily participated in the study. Participants were randomly assigned to two groups: the experimental group (EG), which participated in a 20-min moderate-intensity cycling session (60% of the individual maximum target heart rate recorded at the end of the 6-min walk test); and the control group (CG), which participated in a 20-min reading activity. Cognitive abilities were assessed before and after the physical exercise or reading session using the Stroop test for selective attention, the forward and backward digit span test for working memory, and the Tower of Hanoi task for problem-solving abilities.
RESULTS
At baseline, both groups had comparable cognitive performance ( > 0.05 in all tests). Regardless of sex, aerobic acute exercise improved attention in the Stroop test ( < 0.001), enhanced memory performance in both forward ( < 0.001) and backward ( < 0.001) conditions, and reduced the time required to solve the problem in the Tower of Hanoi task ( < 0.001). No significant differences were observed in the number of movements. In contrast, the CG did not significantly improve after the reading session for any of the cognitive tasks ( > 0.05). Consequently, the EG recorded greater performance improvements than the CG in most cognitive tasks tested ( < 0.0001) after the intervention session.
DISCUSSION
These findings demonstrate that, irrespective to sex, a single aerobic exercise session on an ergocycle can improve cognitive function in patients with moderate AD. The results suggest that acute aerobic exercise enhances cognitive function similarly in both female and male patients, indicating promising directions for inclusive therapeutic strategies.
PubMed: 38903391
DOI: 10.3389/fspor.2024.1383119 -
Annals of Medicine Dec 2024Atrioventricular block (AVB) is rare in hyperthyroidism (HTH). Little is known about the true prevalence, clinical course, optimal management, and outcomes of different...
BACKGROUND
Atrioventricular block (AVB) is rare in hyperthyroidism (HTH). Little is known about the true prevalence, clinical course, optimal management, and outcomes of different types of AVBs in patients with HTH. To address these uncertainties, we aimed to conduct a systematic review by combining the available literature to provide more meaningful data regarding AVBs in HTH.
METHODS
We systematically searched PubMed, Scopus, Embase, and Google Scholar for articles reporting patients who developed AVB in the context of HTH. Data were analysed in STATA 16. The main outcomes included types of AVB, frequency of pacemaker insertion, and resolution of AVB. The systematic review is registered with the International Prospective Register of Systematic Reviews (PROSPERO) with the identification number CRD42022335598.
RESULTS
A total of 56 studies (39 case reports, 12 case series, 3 conference abstracts, 1 retrospective study, and 1 prospective observational study) with 87 patients were included in the analysis, with a mean age of 39.1 ± 17.6 years. Females constituted 65.7% ( = 48) of the cohort. Complete heart block (CHB) was the most commonly reported AVB ( = 45, 51.7%), followed by first-degree AVB (16.1%) and second-degree AVB (14.9%). Overall, 21 patients underwent pacing. A permanent pacemaker was inserted in one patient with second-degree AVB and six patients with CHB. Mortality was reported in one patient with CHB. The clinical course and management of HTH and AVBs did not differ in patients with CHB or lower-degree blocks. Apart from lower rates of goitre and more use of carbimazole in those who underwent pacing, no differences were found when compared to the patients managed without pacing.
CONCLUSION
Current data suggest that CHB is the most common type of AVB in patients with HTH. Most patients can be managed with anti-thyroid management alone. Additionally, whether pacemaker insertion alters the clinical outcomes needs further exploration.
Topics: Humans; Hyperthyroidism; Atrioventricular Block; Female; Pacemaker, Artificial; Male; Adult; Middle Aged
PubMed: 38902995
DOI: 10.1080/07853890.2024.2365405