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Actimetry Protocol in COPD Patients

NCT05918003 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 104

Last updated 2023-06-26

No results posted yet for this study

Summary

Recently, the principal investigator published an EI predictive Machine Learning algorithm based solely on clinical data, without any physical activity measures, collected from 1 409 patients. The GOLD standard of EI was defined on the basis of interrogation criteria. Patients considered as EI reported walking less than 10 minutes per day on average, and the pulmonologist judged that the patient had mainly "domestic activities".

Despite the subjective nature of the GOLD standard, the algorithm validated on a test sample had an error rate of only 13.7% (AUROC: 0.84, CI95% \[0.75-0.92\]). In the total study population (n=1409), 34% of patients were ultimately classified as EIs by the algorithm, in agreement with the results of studies using actimetry as the GOLD standard.

The principal investigator now wish to verify and improve the validity of the MLA on a new smaller population of 104 patients, using a physiological GOLD standard such as three-dimensional actimetry.

Conditions

  • COPD
  • Inactivity, Physical

Sponsors & Collaborators

  • Icadom

    collaborator INDUSTRY

  • Association pour la Complementarite des Connaissances et des Pratiques de la Pneumologie

    lead OTHER

Principal Investigators

  • Bernard Aguilaniu, M.D. PhD · Association pour la Complementarite des Connaissances et des Pratiques de la Pneumologie

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-01-01
Primary Completion
2023-09-30
Completion
2023-12-31

Countries

  • France

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05918003 on ClinicalTrials.gov