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NCT Number: NCT06798688

In This Study, the Sponsor Would Like to Collaborate with Institution and Investigator to Aggregate Participants Data and to Pilot Its Software Algorithm Using Machine Learning and Threshold Based Methods for Predicting Exacerbations and Deterioration Within a 60 Days Period Post-discharge

In this study, the sponsor would like to collaborate with Institution and Investigator to aggregate participants data and to pilot its software algorithm using machine learning and threshold based methods for predicting exacerbations and deterioration within a 60 days period post-discharge.

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Key information

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Subject age 18 or older
  • Receives all primary and specialty care at Institution
  • Participants will be enrolled at discharge (and not designate hospital or ED)
  • A history of one of the following diagnoses:

a. c. Chronic obstructive pulmonary disease

  • At least two documented exacerbations of the above disease in the past 12 months as defined by the following corresponding criteria:

a. Chronic obstructive pulmonary disease exacerbation: all three of (1) increase in frequency and severity or severity of cough, (2) increase in volume and/or change of character of sputum production, and (3) increase in dyspnea, and requiring treatment with short-acting bronchodilators, antibiotics, and oral or intravenous glucocorticoids.

  • Participants able to provide informed consent.
  • Participants will be enrolled at discharge (and not designate hospital or ED)

Exclusion criteria

  • Participants with neuromuscular diseases and seizures
  • Participants enrolled in hospice care or life expectancy less than three months.
  • Participants living more than 60 miles away from Institution and Investigator
  • Participants with expected out of state travel within a 30-day period or travel to a location with no internet access.

Treatment and study plan

A non-invasive cardio-respiratory sensor will be applied on the subjects to measure parameters to identify exacerbations

Device

This Study aims to pilot software algorithms based on respiratory features and hemodynamics for predicting exacerbations on a total of 20 participants with COPD. The end-points of this Study includes the following:

  • To validate respiratory-based biomarkers in models to predict exacerbations - benchmarking to be done versus physician assess exacerbations, emergency department visits, hospitalizations and any other visit.
  • To validate level of compliance, drop-out rate and if additional measures are required to get participants to follow-on

Primary outcomes

  1. Identifying readmissions using respiratory biomarkers

    Time frame: 60-days

    To validate respiratory-based biomarkers in models to predict exacerbations - benchmarking to be done versus physician assess exacerbations, emergency department visits, hospitalizations and any other visit.

Secondary outcomes

  1. Validate compliance and usability

    Time frame: 60-days

    To validate level of usability using self-assessed questionnaires required to get participants to follow-on

Study contacts

Contact information is provided by the study sponsor or research team.

Gurpreet Singh Singh

CONTACT

[email protected]

6590617570

Sponsors and collaborators

Lead sponsor

Respiree Pte Ltd

Industry

Registry information

Official study title

Software Algorithm Using Machine Learning and Threshold Based Methods for Predicting Exacerbations and Deterioration

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
Jan 29, 2025
Registry last updated
Jan 29, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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