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.

A successful extubation process is critical for the future health outcomes of paediatric patients, as it tests the functioning of the respiratory system without the support of mechanical ventilation. However, extubation can cause stress, pain, anxiety or discomfort in patients, which may sometimes lead to an increased likelihood of reintubation. Music-based interventions and therapies have been shown to be effective in reducing anxiety and stress levels in ventilated patients in the paediatric intensive care unit (PICU), but studies evaluating the effect of music therapy during the extubation process in the PICU are scarce.

This is a pragmatic multicentre randomised clinical trial with two parallel arms. The intervention group will receive standard care + music therapy during the extubation process, and the control group will receive standard care alone. The main outcome measure is heart rate, which will be measured every minute for 5 min pre-extubation, during the extubation process and up to 10 min postextubation. Secondary outcome measures are: oxygen saturation, respiratory rate, blood pressure and heart rate variability. A total of 82 patients will be randomised.

This study was approved by the Research Ethics Committee of the Fundación Universitaria Sanitas (CEIFUS 1356-24, date of approval: 3 May 2024). All parents or legal guardians of patients will sign a written informed consent, and if applicable, assent from participants will be sought. The results will be disseminated through publications in peer-reviewed journals, conferences and presentations at the hospitals’ clinical committees.

Version 1.0, 18 December 2024.

NCT06591533, trial registration date: 10 September 2024.