Tailored Hydration for the Prevention of Contrast-Induced Acute Kidney Injury After Coronary Angiogram or PCI: A Systematic Review and Meta-Analysis.

Background: Contrast-induced acute kidney injury (CI-AKI) is a frequent complication of coronary interventions associated with an increased risk of mortality and morbidity. The optimal intravenous hydration strategy to prevent CI-AKI is not well-established. The primary objective is to determine if a tailored hydration strategy reduces the risk of CI-AKI and of major adverse cardiovascular events (MACE) in patients undergoing coronary angiography compared with a non-tailored hydration strategy.

Consecutive Microsurgical Cases Performed by Single Surgeon at a Canadian Tertiary Care Center: A Retrospective Review.

The practice of a microsurgeon evolves over time with experience, changes in clinical interest, and practice setting. Previous reports suggest that complication rates may be influenced by years of practice. The aim of this study was to analyze consecutive microsurgical cases performed by a single surgeon during the first half of their career in a broad microsurgical practice at a Canadian academic tertiary care center.

Ethical Considerations Regarding Financial Incentives in Plastic Surgery-Related Health Research.

To recruit enough patients to achieve adequate statistical power in clinical research, investigators often rely on financial incentives. The use of these incentives, however, remains controversial as they may cause patients to overlook risks associated with research participation. This concern is amplified in the context of plastic surgery where aesthetic procedures are often more desirable and are not typically covered by public or private insurance plans.

Automated Assessment of Right Atrial Pressure From Ultrasound Videos Using Machine Learning.

Background: Early recognition of volume overload is essential for heart failure patients. Volume overload can often be easily treated if caught early but causes significant morbidity if unrecognized and allowed to progress. Intravascular volume status can be assessed by ultrasound-based estimation of right atrial pressure (RAP), but the availability of this diagnostic modality is limited by the need for experienced physicians to accurately interpret these scans.

Impact of Treatment with Direct Antivirals on Coagulation Parameters in Patients with Hepatitis C Virus-Related Liver Cirrhosis and Sustained Virological Response.

: Sustained virologic responses (SVRs) lead to a decrease in portal hypertension, the regression of fibrosis, and the improvement in the hepatic synthesis of procoagulant and anticoagulant factors. We aimed to assess the influence of SVR on coagulation parameters in cirrhotic patients with HCV treated with DAAs. : We performed a prospective study in the Institute of Gastroenterology and Hepatology Iasi, Romania, between January 2022 and February 2024.

Prediction of incident atrial fibrillation using deep learning, clinical models, and polygenic scores.

Background And Aims: Deep learning applied to electrocardiograms (ECG-AI) is an emerging approach for predicting atrial fibrillation or flutter (AF). This study introduces an ECG-AI model developed and tested at a tertiary cardiac centre, comparing its performance with clinical models and AF polygenic score (PGS).

Methods: Electrocardiograms in sinus rhythm from the Montreal Heart Institute were analysed, excluding those from patients with pre-existing AF.

Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?

Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devices capable of detecting short episodes of arrhythmia are now widely available. Although it has recently been suggested that some high-risk patients with AF detected on implantable devices may benefit from anticoagulation, long-term management remains challenging in lower-risk patients and in those with AF detected on monitors or wearable devices as the development of clinically meaningful arrhythmia burden in this group remains unknown.

A Responsible Framework for Applying Artificial Intelligence on Medical Images and Signals at the Point of Care: The PACS-AI Platform.

The potential of artificial intelligence (AI) in medicine lies in its ability to enhance clinicians' capacity to analyse medical images, thereby improving diagnostic precision and accuracy and thus enhancing current tests. However, the integration of AI within health care is fraught with difficulties. Heterogeneity among health care system applications, reliance on proprietary closed-source software, and rising cybersecurity threats pose significant challenges.

Evaluation of stenoses using AI video models applied to coronary angiography.

The coronary angiogram is the gold standard for evaluating the severity of coronary artery disease stenoses. Presently, the assessment is conducted visually by cardiologists, a method that lacks standardization. This study introduces DeepCoro, a ground-breaking AI-driven pipeline that integrates advanced vessel tracking and a video-based Swin3D model that was trained and validated on a dataset comprised of 182,418 coronary angiography videos spanning 5 years.

Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.

Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in our understanding of these syndromes have improved patient diagnosis and care, yet certain clinical gaps remain, particularly within case ascertainment, access to genetic testing, and risk stratification. Artificial intelligence (AI), specifically machine learning and its subset deep learning, present promising solutions to these challenges.

Deep Learning-Augmented ECG Analysis for Screening and Genotype Prediction of Congenital Long QT Syndrome.

Importance: Congenital long QT syndrome (LQTS) is associated with syncope, ventricular arrhythmias, and sudden death. Half of patients with LQTS have a normal or borderline-normal QT interval despite LQTS often being detected by QT prolongation on resting electrocardiography (ECG).

Objective: To develop a deep learning-based neural network for identification of LQTS and differentiation of genotypes (LQTS1 and LQTS2) using 12-lead ECG.

Continuous Atrial Fibrillation Monitoring From Photoplethysmography: Comparison Between Supervised Deep Learning and Heuristic Signal Processing.

Background: Continuous monitoring for atrial fibrillation (AF) using photoplethysmography (PPG) from smartwatches or other wearables is challenging due to periods of poor signal quality during motion or suboptimal wearing. As a result, many consumer wearables sample infrequently and only analyze when the user is at rest, which limits the ability to perform continuous monitoring or to quantify AF.

Objectives: This study aimed to compare 2 methods of continuous monitoring for AF in free-living patients: a well-validated signal processing (SP) heuristic and a convolutional deep neural network (DNN) trained on raw signal.

Co-surgeon versus Single-surgeon Outcomes in Free Tissue Breast Reconstruction: A Meta-analysis.

Background:  Autologous breast reconstruction offers superior long-term patient reported outcomes compared with implant-based reconstruction. Universal adoption of free tissue transfer has been hindered by procedural complexity and long operative time with microsurgery. In many specialties, co-surgeon (CS) approaches are reported to decrease operative time while improving surgical outcomes.

Eosinophilic enteritis: the great mimic.

Eosinophilic enteritis (EoN), a subtype of eosinophilic gastrointestinal disease, is a rare and complicated inflammatory condition affecting the small intestine. This case report discusses a 42-year-old patient who presented with acute gastrointestinal symptoms including diarrhea, nausea, and vomiting. Initial laboratory investigations revealed leukocytosis, peripheral eosinophilia, and distinctive imaging findings, prompting further evaluation.

Authorship Correction: Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial.

[This corrects the article DOI: 10.2196/41209.].