Atrial Fibrillation (AF) is the most common arrhythmia worldwide affecting an estimated 5% of people over the age of 65 and is a leading cause of stroke and heart failure. Identification of patients at risk allows preventative measures and treatment before these complications occur. Conventional risk prediction models are static, do not have flexibility to incorporate dynamic risk factors and possess only modest predictive value. Artificial intelligence and machine learning-powered health virtual twin technology offer transformative methods for risk prediction and guiding clinical decisions.

In this prospective observational study, 1200 patients will be recruited in two tertiary centres. Patients hospitalised with acute illnesses (sepsis, heart failure, respiratory failure, stroke or critical illness) and patients having undergone high-risk surgery (major vascular surgery, upper gastrointestinal surgery and emergency surgery) will be monitored with a patch-based remote wireless monitoring system for up to 14 days. Clinical and electrocardiographic data will be used for modelling the risk of new-onset AF. The primary outcome is episodes of AF >30 s and will be described as ratio of episodes/patient and as percentage of patients having episodes of AF. Secondary outcomes include 30-day and 90-day readmission rates and complications of AF.

The aim of this study is to generate data for the development and validation of health virtual twins predicting onset of AF in an at-risk population. The intelligent monitoring to predict atrial fibrillation (NOTE-AF) study is part of the TARGET project, a Horizon Europe funded programme which includes risk prediction, diagnosis and management of AF-related stroke (https://target-horizon.eu/).

The study has received approval by the Health Research Authority and the National Research Ethics Service (REC reference 24/NW/0170, IRAS project ID: 342528) in the UK and has been registered on clinicaltrials.gov (NCT06600620). Results will be disseminated as outlined in the TARGET protocol to communicate project ideas, activities and results to diverse audiences.

NCT06600620.

Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate secondary prevention but remains challenging due to its often asymptomatic or paroxysmal occurrence. Artificial intelligence (AI) offers new possibilities by integrating biomarkers, clinical phenotypes, established risk factors and imaging features to define a personalised ‘digital twin’ model. The TAILOR study aims to (1) examine prospective detection of AF using monitoring devices, (2) investigate novel prognostic MRI markers in patients with an AF-related stroke (AFRS) and (3) validate AI-based models for outcome prediction in AFRS.

This prospective multicentre observational cohort study includes patients aged 40 years and above, with neuroimaging-confirmed diagnosis of ischaemic stroke, recruited from two sites: Hospital del Mar Barcelona (Spain) and Radboud University Medical Centre (The Netherlands). For the first sub-study (n=300), patients will undergo clinical assessment at baseline, 3 months and 12 months, and patch-based or Holter cardiac monitoring. The second sub-study (n=200) involves repeated brain MRI and cognitive examination after AFRS. Finally, AI-driven ‘digital twin’ models developed on retrospective TARGET datasets will be prospectively evaluated in TAILOR using temporal and centre-stratified analyses for advanced predictive tools for AF and AFRS outcomes.

The TAILOR study was approved by local ethics boards in Barcelona (CPMP/ICH/135/95) and Medical Research Ethics Committee Oost-Nederland (NL86346.091.24). Patients will be included after providing informed consent. Study results will be presented in peer-reviewed journals and at global conferences.

Phasix mesh is a fully resorbable synthetic mesh for use in clean and contaminated ventral incisional hernia repairs. Long-term absorbable Phasix mesh appears to be a safe and promising device in incisional hernia repair, with low recurrence rates; however, data on long-term complications after surgery, particularly after the resorption period of the mesh, are scarce.

This protocol describes a study of several European registries on the use of a Phasix mesh in incisional hernia repair. The primary endpoint of the study is long-term complications at 2–5 year follow-up after mesh implantation, with secondary endpoints including hernia recurrence and complications during short-term follow-up.

Ethical approval was not required for this protocol as the study is based on anonymised registry data collected with prior patient consent in each registry. Each participating registry has its own ethical approval process, and this study will adhere to those regulations. The results will be disseminated through peer-reviewed publications and conference presentations.

Knee osteoarthritis (OA) is a leading cause of disability in older adults, with health and economic impacts. Despite pharmacological advances, exercise continues to be a fundamental pillar in the management of OA, with lower limb strength training showing significant benefits. Virtual reality (VR)-based interventions have emerged as innovative tools, providing immersive environments to facilitate functional movement exercises. VR offers pain relief, improved functionality and reduced fall risks, although its efficacy in OA management requires further exploration. The main aim of the study is to assess whether a VR-based intervention provides superior improvements in pain, stiffness, physical function and movement biomechanics compared with conventional therapeutic exercise in adults aged 60 years and older with knee OA.

This is a protocol for a randomised controlled trial comparing the effects of immersive VR interventions with conventional therapeutic exercises in individuals aged 60 years and older with knee OA. Participants are allocated 1:1 to experimental (VR) and control groups. The VR intervention involves 18 supervised sessions over 8 weeks, using Meta Quest 3 goggles to perform functional movements in virtual environments. The control group follows standard therapeutic exercise protocols per Osteoarthritis Research Society International guidelines. Outcomes include OA-related symptoms, kinematic performance, pain intensity, kinesiophobia and fall risk. Secondary measures assess cybersickness, depressive symptoms, medication use and comorbidities. Assessments occur at baseline, ninth week, sixth and ^12th months. Data analysis employs intention-to-treat principles, leveraging descriptive statistics, t-tests and multiple imputations for missing data.

This study was approved by the A Coruña-Ferrol Research Ethics Committee (reference: 2023/557), under the Galician Health Service. All participants will be required to provide written informed consent prior to their inclusion in the study. Participant data will be pseudonymised and securely stored. Additionally, anonymised datasets will be deposited in open-access repositories (Zenodo).

NCT06362785.

Pelvic organ prolapse (POP) is the descent of one or more pelvic organs through the vaginal canal, including the vagina, uterus, rectum, bladder, cervix, posthysterectomy vaginal cuff, and small or large bowel, which compromises a woman’s physical, mental and social well-being.

This study aimed to explore how women with POP experience their living and its impact on their quality of life (QoL).

This was a qualitative study using interpretive phenomenological analysis, following in-depth structured interviews. Analysis was undertaken to identify superordinate themes relating to how women are living with POP.

3 public hospitals and 3 woredas in Gurage zone, Central Regional State, Ethiopia.

A purposive sample of 12 women who were diagnosed with POP was recruited.

Five core themes with subthemes were identified; general health judgement, POP symptom, life situation related to POP, feeling about POP and limitation in daily life/activity. The majority of respondents expressed concern that the prolapse had negatively impacted their general health and voiced hope that pelvic floor reconstruction would improve their general well-being. The majority of the informants stated that disclosing to others might significantly lower their QoL and that having the condition was extremely embarrassing. The women were most affected by the actual physical symptoms of prolapse (bulge, back pain, heaviness, bowel problems, urinary incontinence) as well as by the impact prolapse has on their sexual function.

Women with POP should be offered psychosocial support, early care and counselling because they have physical, personal, emotional, social and sleep/energy problems. Healthcare providers should take the initiative in educating women regarding prolapse and to make them aware that it is a treatable condition which can improve their QoL.

It is unclear how mis- and disinformation regarding healthcare policy changes propagate throughout Latino communities via social media. This may lead to chilling effects that dissuade eligible individuals from enrolling in critical safety net programmes such as Medicaid. This study will examine pathways and mechanisms by which sentiment in response to mis- and disinformation regarding healthcare policies on social media differentially impact health disparity populations, thus supporting the design of tailored social media interventions to mitigate this.

We will search social media from X/Twitter, Facebook/Instagram and Reddit for keywords relating to health benefit programmes. Demographic, geographical location and other characteristics of users will be used to stratify social media data. Posts will be classified as fake-news-related or fact-related based on curated lists of fake-news-related websites. The number, temporal dissemination and positive or negative sentiment in reacting to posts and threads will be examined using the Python-based Valence Aware Dictionary and sEntiment Reasoner (VADER). Using a crowd-sourcing methodology, a novel Spanish-language VADER (S-VADER) will be created to rate sentiment to social media among Spanish-speaking Latinos. With the proposed approach, we will explore reactions to the dissemination of fake-news- or fact-related social media tweets and posts and their sources. Analyses of social media posts in response to healthcare-related policies will provide insights into fears faced by Latinos and Spanish speakers, as well as positive or negative perceptions relating to the policy over time among social media users.

Our study protocol was approved by the University of California, Los Angeles IRB (IRB#23–0 01 123). Results from this study will be disseminated in peer-reviewed journals and conference presentations, and S-VADER will be disseminated to public repositories such as GitHub.