{
  "abstract": "Introduction Exacerbations, impaired health-related quality of life (HRQoL) and reduced exercise capacity increase the risk of hospitalisations and death in chronic obstructive pulmonary disease (COPD). However, their monitoring relies on in-person assessments, potentially delaying early care. While smart sensing technologies can enable remote monitoring, their use in predicting disease worsening remains limited. The TOLIFE Clinical Study A (CSA) aims to develop an artificial intelligence (AI) model integrating clinical data with smart sensing devices data to predict exacerbation onset and changes in HRQoL, dyspnoea and exercise capacity in people with COPD.Methods and analyses TOLIFE CSA is a longitudinal observational study that will recruit 150 clinically stable people with COPD from three clinical sites in Spain, Italy and Germany. Over 1 year, participants will attend quarterly in-person visits to collect clinical data, while being continuously monitored using six unobtrusive smart sensing devices collecting daily metrics calculated from triaxial acceleration, angular velocity, photoplethysmogram, sound intensity, changes in latitude and longitude, ambient light intensity, biomechanical pressure and respiratory airflow parameters. Clinical outcomes are exacerbation onset through medical records; 3-month changes in HRQoL through the COPD Assessment Test and the Clinical COPD Questionnaire; 3-month changes in dyspnoea severity through the modified Medical Research Council Dyspnoea Scale; and 6-month changes in functional exercise capacity through the 6-minute walk test. We will train, internally validate and test AI-based models (Random Forests, XGBoost, multilayer perceptrons, cumulative link model and standard classification model) to predict clinical outcomes.Ethics and dissemination Ethical approval was issued for all sites by the Ethical Commission (EC) of the Medical Association of Schleswig-Holstein (Bad Segeberg; vote 074/23 ff), EC of the Tuscany Region–North West Area (Pisa; vote CET10/2023) and EC of Parc de Salut Mar (Barcelona; vote 2023/11230). All participants will sign a written informed consent.Trial registration number NCT06172712.",
  "authors": [
    {
      "affiliations": [
        "Barcelona Institute for Global Health, Barcelona, Spain",
        "Universitat Pompeu Fabra, Barcelona, Spain"
      ],
      "name": "Roger Vásquez-Andrade"
    },
    {
      "affiliations": [
        "Barcelona Institute for Global Health, Barcelona, Spain",
        "Universitat Pompeu Fabra, Barcelona, Spain"
      ],
      "name": "Victoria Alcaraz-Serrano"
    },
    {
      "affiliations": [
        "Barcelona Institute for Global Health, Barcelona, Spain",
        "Universitat Pompeu Fabra, Barcelona, Spain"
      ],
      "name": "Joren Buekers"
    },
    {
      "affiliations": [
        "Institute of Clinical Physiology, National Research Council, Pisa, Italy"
      ],
      "name": "Pasquale Bufano"
    },
    {
      "affiliations": [
        "Institute of Clinical Physiology, National Research Council, Pisa, Italy"
      ],
      "name": "Marco Laurino"
    },
    {
      "affiliations": [
        "Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Pisa, Italy"
      ],
      "name": "Alessandro Celi"
    },
    {
      "affiliations": [
        "Velocity Clinical Research Germany, Ahrensburg, Germany",
        "Airway Research Center North (ARCN), German Center for Lung Research (DZL), University of Lübeck, Lübeck, Germany"
      ],
      "name": "Henrik Watz"
    },
    {
      "affiliations": [
        "Servei de Pneumologia, Hospital del Mar, Hospital del Mar Research Institute, Barcelona, Spain",
        "MELIS Department, Universitat Pompeu Fabra, Barcelona, Spain"
      ],
      "name": "Joaquim Gea"
    },
    {
      "affiliations": [
        "Department of Information Engineering, University of Pisa, Pisa, Italy"
      ],
      "name": "Nicola Carbonaro"
    },
    {
      "affiliations": [
        "Department of Information Engineering, University of Pisa, Pisa, Italy"
      ],
      "name": "Alessandro Tognetti"
    },
    {
      "affiliations": [
        "Barcelona Institute for Global Health, Barcelona, Spain",
        "Universitat Pompeu Fabra, Barcelona, Spain"
      ],
      "name": "Judith Garcia-Aymerich"
    }
  ],
  "title": "Development of an artificial intelligence prediction model for moderate-to-severe COPD exacerbations using continuous multiple unobtrusive sensors: protocol of a multicentre prospective observational study",
  "uid": "8bc0d0bd-ce73-56eb-905a-bf9c7fc39abd"
}