New algorithm aims to catch COPD before It's too late
NCT ID NCT07223749
First seen Jun 25, 2026 · Last updated Aug 28, 2026 · Updated 2 times
Summary
This study is testing a computer algorithm that uses health records to predict whether a person has COPD. Many people with COPD are not diagnosed until the disease is advanced, while others are wrongly told they have it. The goal is to see if the algorithm can correctly identify who truly has COPD, so patients can get the right care sooner.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- What this could lead to
- If successful, this could lead to a reliable way to diagnose COPD earlier and reduce misdiagnosis, helping patients get the right treatment sooner.
- What could go wrong
- This is an observational study testing an algorithm, not a treatment. The tool may not prove accurate enough in real-world settings, and results may not apply to all patient groups.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Study facts
What this study's own registry entry says, in plain language.
- Participants
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425 people
The number who actually took part.
- Started
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Aug 2025
- Finished
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May 2026
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Data from the Wake Forest Baptist Medical Center in Winston Salem, NC and Lexington Medical Center in Lexington, NC were extracted from a common electronic health record system. Algorithm development included 15,065 patients who underwent pulmonary function testing in 2016-2022.
- Ages
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40 years and older
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: * greater thank or equal to 40 years of age * 2 or more encounters in the health system * Previous Pulmonary Function Test (PFT) recorded in our Electronic Health Records (EHR) in the previous 5 years Exclusion Criteria: * cystic fibrosis * Alpha-1 Antitrypsin Deficiency (AAD)currently pregnant * History of a lung transplant or partial removal of the lung * significant chest wall deformity * neuromuscular disease that currently impacts the respiratory muscles * surgery requiring general anesthesia or an overnight stay in the hospital within the past 30 days
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
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Wake Forest University Health Sciences
Winston-Salem, North Carolina, 27157, United States
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