copd exacerbation modelling using unobtrusive sensors - the tolife clinical study a

Conditions: Chronic Obstructive Pulmonary Disease (COPD)

Summary: this work is a multicentric prospective cohort study designed to improve chronic obstructive pulmonary disease (copd) treatment and management. the study involves 150 patients diagnosed with copd who are at risk of exacerbations. these patients are recruited from three tertiary hospitals in spain, germany, and italy. the study will last 18 months, with a 12-month follow-up duration for each patient. the primary objective of this study is to develop and test artificial intelligence (ai)-based models that can predict moderate-to-severe copd exacerbations early on. this will be done by analyzing daily-life data collected from unobtrusive sensors that monitor patients' psycho-physiological and environmental signals. by accurately predicting exacerbations, the study aims to support clinicians in providing more precise, optimized, and personalized treatment to copd patients. a secondary objective is to train and test ai-based models to estimate the 12-month dynamics of health-related quality of life (hrqol) in copd patients. this will involve analyzing data related to the patients' functional exercise capacity, dyspnea (difficulty breathing), and health-related quality of life, as measured by the clinical copd questionnaire (ccq) score and the copd assessment test (cat) score.


Eligibility criteria:
inclusion criteria: * diagnosis of copd (fev1/fvc \< 0.7) for at least a year. * participants with moderate-to-very severe copd (fev1 ≤ 80% predicted) * documented history of ≥ 1 moderate (treated with sabds and oral corticosteroids ± antibiotics) or severe copd exacerbation\* within 12 months before enrolment. * adults aged 40 or over. * able to walk 4 meters independently with or without walking aids. * anticipated availability for repeated study visits over 12 months. * willingness to use smart sensors. * able to read and write in the first language in the respective location. * capable of giving signed informed consent, which includes compliance with the requirements and restrictions listed in the informed consent form (icf) and the study protocol. exclusion criteria: * occurrence of any of the following within three months before informed consent: myocardial infarction, hospitalization for unstable angina, stroke, coronary artery bypass graft (cabg), percutaneous coronary intervention (pci), implantation of a cardiac resynchronization therapy device (crtd). * uncontrolled congestive heart disease (nyha class \>3). * having undergone major lung surgery (e.g., lung transplant) * primary respiratory diseases other than copd. * participant who has experienced a major respiratory infection or exacerbation within 2 weeks before screening * lung volume reduction within six months before screening. * active treatment for cancer or other malignant diseases that in the opinion of the investigator, have an impact on the patient's quality of life such as to prevent adherence to the study. * acute psychosis or major psychiatric disorders or continued substance abuse. * severe disease that limits survival to 1 year. * patients with severe cognitive impairment (mmse \< 18). * substantial limitations in mobility due to factors other than copd. * inability to follow the study procedures (e.g., due to language problems, psychological disorders) or unable to read, understand and fill in a questionnaire.

Keywords: chronic obstructive pulmonary disease (copd) exacerbation remote patient monitoring predictive modeling