Biomarker-based prediction of sinus rhythm in atrial fibrillation patients: the EAST-AFNET 4 biomolecule study.

Background And Aims: In patients with atrial fibrillation (AF), recurrent AF and sinus rhythm during follow-up are determined by interactions between cardiovascular disease processes and rhythm control therapy. Predictors of attaining sinus rhythm at follow-up are not well known.

Methods: To quantify the interaction between cardiovascular disease processes and rhythm outcomes, 14 biomarkers reflecting AF-related cardiovascular disease processes in 1586 patients in the EAST-AFNET 4 biomolecule study (71 years old, 45% women) were quantified at baseline.

PITX2 deficiency leads to atrial mitochondrial dysfunction.

Aims: Reduced left atrial PITX2 is associated with atrial cardiomyopathy and atrial fibrillation (AF). PITX2 is restricted to left atrial cardiomyocytes (aCMs) in the adult heart. The links between PITX2 deficiency, atrial cardiomyopathy, and AF are not fully understood.

Global 30-day morbidity and mortality of surgery for perforated peptic ulcer: GRACE study.

Background: There is little international data on morbidity and mortality of surgery for perforated peptic ulcer (PPU). This study aimed to understand the global 30-day morbidity and mortality of patients undergoing surgery for PPU and to identify variables associated with these.

Method: We performed an international study of adults (≥ 18 years) who underwent surgery for PPU from 1st January 2022 to 30th June 2022.

Global 30-Day Morbidity and Mortality of Primary Bariatric Surgery Combined with Another Procedure: The BLEND Study.

Background: No robust data are available on the safety of primary bariatric and metabolic surgery (BMS) alone compared to primary BMS combined with other procedures.

Objectives: The objective of this study is to collect a 30-day mortality and morbidity of primary BMS combined with cholecystectomy, ventral hernia repair, or hiatal hernia repair.

Setting: This is as an international, multicenter, prospective, and observational audit of patients undergoing primary BMS combined with one or more additional procedures.

30-day Morbidity and Mortality after Cholecystectomy for Benign Gallbladder Disease (AMBROSE): A Prospective, International Collaborative Cohort Study.

Objective: This study aimed to assess 30-day morbidity and mortality rates following cholecystectomy for benign gallbladder disease and identify the factors associated with complications.

Summary Background Data: Although cholecystectomy is common for benign gallbladder disease, there is a gap in the knowledge of the current practice and variations on a global level.

Methods: A prospective, international, observational collaborative cohort study of consecutive patients undergoing cholecystectomy for benign gallbladder disease from participating hospitals in 57 countries between January 1 and June 30, 2022, was performed.

Single-center retrospective assessment of robotic-assisted simultaneous pancreas-kidney transplants: Exploring clinical utility.

The diabetic population is witnessing a rise in obesity rates, creating specific hurdles for individuals seeking pancreas transplantation because they are frequently disqualified due to their elevated body weight. Introducing a robotic-assisted approach to transplantation has been proven to yield improved outcomes, particularly in patients with obesity. A retrospective analysis was conducted between January 2015 and September 2023.

Safety outcomes of bariatric surgery in patients with advanced organ disease: the ONWARD study: a prospective cohort study.

Introduction: Increasing numbers of patients with advanced organ disease are being considered for bariatric and metabolic surgery (BMS). There is no prospective study on the safety of BMS in these patients. This study aimed to capture outcomes for patients with advanced cardiac, renal, or liver disease undergoing BMS.

Correction: Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models.

[This corrects the article DOI: 10.1371/journal.pone.

Outcomes of Early Rhythm Control Therapy in Patients With Atrial Fibrillation and a High Comorbidity Burden in Large Real-World Cohorts.

Background: A recent subanalysis of the EAST-AFNET 4 (Early Treatment of Atrial Fibrillation for Stroke Prevention Trial) suggests a stronger benefit of early rhythm control (ERC) in patients with atrial fibrillation and a high comorbidity burden when compared to patients with a lower comorbidity burden.

Methods: We identified 109 739 patients with newly diagnosed atrial fibrillation in a large United States deidentified administrative claims database (OptumLabs) and 11 625 patients in the population-based UKB (UK Biobank). ERC was defined as atrial fibrillation ablation or antiarrhythmic drug therapy within the first year after atrial fibrillation diagnosis.

Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcare.

Artificial intelligence (AI) is increasingly being utilized in healthcare. This article provides clinicians and researchers with a step-wise foundation for high-value AI that can be applied to a variety of different data modalities. The aim is to improve the transparency and application of AI methods, with the potential to benefit patients in routine cardiovascular care.

Early onset of immune-mediated diseases in minority ethnic groups in the UK.

Background: The prevalence of some immune-mediated diseases (IMDs) shows distinct differences between populations of different ethnicities. The aim of this study was to determine if the age at diagnosis of common IMDs also differed between different ethnic groups in the UK, suggestive of distinct influences of ethnicity on disease pathogenesis.

Methods: This was a population-based retrospective primary care study.

Single-centre review of the management of intra-thoracic oesophageal perforation in a tertiary oesophageal unit: paradigm shift, short- and long-term outcomes over 15 years.

Background: Oesophageal perforation is an uncommon surgical emergency associated with high morbidity and mortality. The timing and type of intervention is crucial and there has been a major paradigm shift towards minimal invasive management over the last 15 years. Herein, we review our management of spontaneous and iatrogenic oesophageal perforations and assess the short- and long-term outcomes.

Implementation of patient-reported outcome measures in real-world evidence studies: Analysis of ClinicalTrials.gov records (1999-2021).

Background: Real-world evidence (RWE) plays an increasingly important role within global regulatory and reimbursement processes. RWE generation can be enhanced by collecting and using patient-reported outcomes (PROs), which can provide valuable information on the effectiveness, safety, and tolerability of health interventions from the patient perspective. This analysis aims to examine and summarise the utilisation of patient-reported outcomes measures (PROMs) in real-world studies.

Eligibility for early rhythm control in patients with atrial fibrillation in the UK Biobank.

Objective: The Early Treatment of Atrial Fibrillation for Stroke Prevention (EAST-AFNET4) trial showed a clinical benefit of early rhythm-control therapy in patients with recently diagnosed atrial fibrillation (AF). The generalisability of the results in the general population is not known.

Methods: Participants in the population-based UK Biobank were assessed for eligibility based on the EAST-AFNET4 inclusion/exclusion criteria.

Smartphone detection of atrial fibrillation using photoplethysmography: a systematic review and meta-analysis.

Objectives: Timely diagnosis of atrial fibrillation (AF) is essential to reduce complications from this increasingly common condition. We sought to assess the diagnostic accuracy of smartphone camera photoplethysmography (PPG) compared with conventional electrocardiogram (ECG) for AF detection.

Methods: This is a systematic review of MEDLINE, EMBASE and Cochrane (1980-December 2020), including any study or abstract, where smartphone PPG was compared with a reference ECG (1, 3 or 12-lead).

Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models.

Background: Numerous approaches have been proposed for the detection of epistatic interactions within GWAS datasets in order to better understand the drivers of disease and genetics.

Methods: A selection of state-of-the-art approaches were assessed. These included the statistical tests, fast-epistasis, BOOST, logistic regression and wtest; swarm intelligence methods, namely AntEpiSeeker, epiACO and CINOEDV; and data mining approaches, including MDR, GSS, SNPRuler and MPI3SNP.

30-day morbidity and mortality of sleeve gastrectomy, Roux-en-Y gastric bypass and one anastomosis gastric bypass: a propensity score-matched analysis of the GENEVA data.

Background: There is a paucity of data comparing 30-day morbidity and mortality of sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), and one anastomosis gastric bypass (OAGB). This study aimed to compare the 30-day safety of SG, RYGB, and OAGB in propensity score-matched cohorts.

Materials And Methods: This analysis utilised data collected from the GENEVA study which was a multicentre observational cohort study of bariatric and metabolic surgery (BMS) in 185 centres across 42 countries between 01/05/2022 and 31/10/2020 during the Coronavirus Disease-2019 (COVID-19) pandemic.

Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis.

Background: Mortality remains unacceptably high in patients with heart failure and reduced left ventricular ejection fraction (LVEF) despite advances in therapeutics. We hypothesised that a novel artificial intelligence approach could better assess multiple and higher-dimension interactions of comorbidities, and define clusters of β-blocker efficacy in patients with sinus rhythm and atrial fibrillation.

Methods: Neural network-based variational autoencoders and hierarchical clustering were applied to pooled individual patient data from nine double-blind, randomised, placebo-controlled trials of β blockers.

Multimorbidity prediction using link prediction.

Multimorbidity, frequently associated with aging, can be operationally defined as the presence of two or more chronic conditions. Predicting the likelihood of a patient with multimorbidity to develop a further particular disease in the future is one of the key challenges in multimorbidity research. In this paper we are using a network-based approach to analyze multimorbidity data and develop methods for predicting diseases that a patient is likely to develop.

A Causal Web between Chronotype and Metabolic Health Traits.

Observational and experimental evidence has linked chronotype to both psychological and cardiometabolic traits. Recent Mendelian randomization (MR) studies have investigated direct links between chronotype and several of these traits, often in isolation of outside potential mediating or moderating traits. We mined the EpiGraphDB MR database for calculated chronotype-trait associations (-value < 5 × 10).

Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study.

Background: The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification.

Methods: Training cohorts comprised 1276 patients admitted to King's College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020.

A random forest based biomarker discovery and power analysis framework for diagnostics research.

Background: Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale -omics data are increasingly being accumulated and can provide vital means for the identification of biomarkers for the early diagnosis of complex disease and/or for advanced patient/diseases stratification. These tasks are clearly interlinked, and it is essential that an unbiased and stable methodology is applied in order to address them.

Ensemble learning for poor prognosis predictions: A case study on SARS-CoV-2.

Objective: Risk prediction models are widely used to inform evidence-based clinical decision making. However, few models developed from single cohorts can perform consistently well at population level where diverse prognoses exist (such as the SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2] pandemic). This study aims at tackling this challenge by synergizing prediction models from the literature using ensemble learning.