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Not yet recruiting 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

Observational COPD

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: A non-invasive cardio-respiratory sensor will be applied on the subjects to measure parameters to identify exacerbations.
Who it may be relevant to
Registry conditions: COPD. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Center list to be confirmed — check the primary protocol.
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

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

Overview

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.

Interventions

  • Device A non-invasive cardio-respiratory sensor will be applied on the subjects to measure parameters to identify exacerbations
    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: 1. 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. 2. To validate level of compliance, drop-out rate and if additional measu

Primary outcome measures

  • Identifying readmissions using respiratory biomarkers [Time frame: 60-days]
Secondary outcome measures (1)
  • Validate compliance and usability [Time frame: 60-days]

Eligibility criteria

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.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Case-only

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT06798688 · 2025-001

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗