COVID-19DICOPERIANCT05629793
Differential Diagnosis of Persistent COVID-19 by Artificial Intelligence
A study testing Experimental tests in people with COVID-19 and Fatigue, run by Fundacin Biomedica Galicia Sur at 7 sites in Spain.
Trial summary
The pandemic caused by SARS-CoV-2 infection has resulted, in addition to the well-known acute symptoms, in the emergence of persistent, diffuse and heterogeneous symptoms referred to as persistent COVID. Read more about this study
- Who is it for?
- Ages 18 to 70 years
- Conditions the study is for
- COVID-19, Fatigue, Distress Respiratory Syndrome
- What is being tested?
- Experimental tests
- Type of treatment
- Vaccines
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 136 participants
- Where
- 7 sitesSpain
- Study dates
- 14 Dec 2022to Nov 2023
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 70 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age ≥18 and ≤70 years of age
- Confirmed infection (PCR) with SARS- CoV-2 until 03/28/2022 and thereafter date.
- Symptoms include: fatigue, respiratory distress or cognitive dysfunction, among others.
- Symptoms persist or appear more than 3 months after onset of infection.
- Symptoms last longer than 2 months and are not better explained by another diagnosis.
- Symptoms appeared after initial recovery or persisted since disease debut.
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- Symptoms may fluctuate or remit over time.
- Patients have capacity to consent and agree to participate in the study.
- Age ≥18 and ≤70 years of age
- Confirmed infection (PCR) with SARS- CoV-2 until 03/28/2022 and thereafter date.
- Full functional recovery.
- Follow-up by Primary Care.
- They have not presented three months after the onset of the disease: fatigue, respiratory distress or cognitive dysfunction, among others.
- Patients have capacity to consent and agree to participate in the study.
Who cannot join
- Active COVID-19 infection.
- Cardiac arrhythmia, pacemaker carrier.
- Other pathologies with dysautonomia.
- Raynaud's phenomenon.
- Other diseases that may affect exercise capacity or be aggravated by exercise shall also be excluded, such as: Uncontrolled heart failure, severe or symptomatic aortic stenosis, pulmonary edema, acute respiratory failure, recent pulmonary thromboembolism, lower limb thrombosis, infections, thyrotoxicosis, or orthopedic inability to walk.
- Recovery COVID group
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- Active COVID-19 infection.
- Cardiac arrhythmia, pacemaker carrier.
- Other pathologies with dysautonomia.
- Raynaud's phenomenon.
- Other diseases that may affect exercise capacity or be aggravated by exercise such as: uncontrolled heart failure, severe or symptomatic aortic stenosis, pulmonary edema, acute respiratory failure, recent pulmonary thromboembolism, lower limb thrombosis, infections, thyrotoxicosis, or orthopedic inability to walk shall also be excluded.
Trial locations and contacts
7 sites in 1 country.
7 sites in 1 country
Spain7 sites
Complexo Hospitalario Universitario de Ourense
Ourense, 32002
Alejandro García Caballero, MD, alejandro.alberto.garcia.caballero@sergas.es
Alejandro García Caballero, MD
Health Center Novoa Santos
Ourense, 32003
Health Center Valle Inclán
Ourense, 32004
S.S. Computer Engineering (University of Vigo)
Ourense, 32004
Health Center A Cuña
Ourense, 32005
Carlos Menéndez Villalva
Galicia Sur Health Research Institute (IISGS) - Hospital Álvaro Cunqueiro
Vigo, 36213
School of Telecommunication Engineering (University of Vigo)
Vigo, 36310
About this study
The pandemic caused by SARS-CoV-2 infection has resulted, in addition to the well-known acute symptoms, in the emergence of persistent, diffuse and heterogeneous symptoms referred to as persistent COVID.
Common symptoms include fatigue, shortness of breath, and cognitive dysfunction, among others, and result in an impact on daily functioning. Symptoms may be new onset, appear after initial recovery from an acute episode of COVID-19, or persist after the initial illness. Cardiac variability (HRV) was initially used in COVID-19 to predict mortality in the acute setting. Dysautonomia which partly evaluates HRV is frequent in patients with persistent COVID. Several groups have used voice or other respiratory noise analysis for the diagnosis of acute COVID.
Patients in the persistent COVID cohort will be able to be differentiated from an age, sex and vaccination status matched cohort of recovered COVID patients without sequelae by means of a model created by Machine Learning that will be trained using cardiac variability (HRV), skin conductance and acoustic analysis data. The primary objetive will be to obtain a classification algorithm by Machine Learning to differentiate the group of patients with persistent COVID diagnosis from the paired group of recovered COVID patients without sequelae.
Read the detailed description
This is a validation study of a Machine Learning algorithm for the diagnosis of persistent COVID using clinical diagnosis as the "gold standard". The sample will be composed of post-COVID patients, one group of which developed persistent COVID and another paired with the previous one with cured COVID without sequelae.
- Conditions
- COVID-19, Fatigue, Distress Respiratory Syndrome, Cognitive Dysfunction, COVID-19 Recurrent, SARS CoV 2 Infection
- Being tested
- Experimental tests
- Keywords
- Machine learning, Stress test, Cardiac variability, Voice recording, Skin conductance
- Medical subject headings
- COVID-19, Fatigue, Pulmonary Atelectasis, Cognitive Dysfunction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Experimental testsOther
Walking for 6 minutes, sitting down and getting up from a chair for 1 minute and finally the cold test (Cold pressor) where the hand is introduced for 1 minute in water at 4ºC. The patient will be monitored by means of a Polar H10 chest strap, as used in sports, continuously and 02 saturation, TA and voice (exhalation while saying /a/ and dry cough) will be collected before and after the tests. Finally, skin conductance will be monitored by performing baseline tracing and then control while performing the cold test.
| Study group | Role | What they receive |
|---|---|---|
| Persistent COVID group | Experimental | Patients with persistent COVID will be recruited by the physicians of the Post COVID-19 Multidisciplinary Clinic of the Complexo Hospitalario Universitario de Ourense. Receives: Other: Experimental tests |
| Recovered COVID group | Experimental | The controls will be recruited in a matched manner with the clinical sample in age, sex, epidemic wave and vaccination status, from among previously COVID-positive patients cured without sequelae and attended in Primary Care in the Health Centers of A Cuña, Valle Inclán and Novoa Santos in Ourense. Receives: Other: Experimental tests |
What is being measured
The primary outcome is the main question the study is designed to answer.
Differences of the group of patients with a persistent diagnosis of COVID from the age-matched group, sex and vaccination status of patients recovered from COVID without sequelae.
Through an algorithm model created by Machine Learning that will be trained using cardic variability (HRV), skin conductance and acoustic analysis data.
Measured: 8 weeks
Secondary outcomes (6)
Cardiac variability
Number of times a contraction of the heart occurs in one minute, expressed in beats per minute, by means of a Polar chest strap, model H10. A baseline recording of 5 minutes duration will be taken, with the patient in a seated position. At the end of each test, recording is continued for 2 minutes to demonstrate the speed and degree of recovery after stress.
Measured: 8 weeks
Voice recording
Sounds produced by the patient at rest and after having performed the stress tests. The patient will be asked to take a deep breath and then pronounce the vowel /a/ in a sustained manner, in a comfortable tone and volume (3 times).
Measured: 8 weeks
Skin conductance
micro Siemens [µS]. By means of the Bitalino electrodermal activity recording system. It will be recorded at rest, during the Cold Pressor test and once it is finished, for at least two minutes, to assess the normalization of the conductivity curve.
Measured: 8 weeks
6MWT
metres/min. The patient will walk the maximum distance they can in 6 minutes.
Measured: 8 weeks
1minSTST
Number of repetitions performed after sitting down and getting up from a chair without supporting the hands as many times as possible for 1 minute..
Measured: 8 weeks
Cold Pressor test
One hand is inserted into a container with water at 4-5ºC for 1 minute. Before and after the test, HRV, BP, and thermal conductance are recorded for 5 and 2 minutes -respectively- while lying supine.
Measured: 8 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Nov 2022
- Study start14 Dec 2022 (estimated)
- Primary completionNov 2023 (estimated)
- Study completionNov 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for COVID-19Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Model description
- Persistent COVID group vs. Recovered COVID group
- Masking
- Single blind
- Who is masked
- Investigator
- Enrolment
- 136 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Fundacin Biomedica Galicia Sur
- Sponsor type
- University, hospital or other
- Collaborators
- University of Vigo, Galician South Health Research Institute
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05629793
- Sponsor's protocol ID
- DICOPERIA
- Acronym
- DICOPERIA
- Status last verified
- Nov 2022
- First submitted
- 18 Nov 2022
- Last updated
- 29 Nov 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Differential Diagnosis of Persistent COVID-19 by Artificial Intelligence
- ClinicalTrials.gov ID
- NCT05629793
- Acronym / sponsor ID
- DICOPERIA / DICOPERIA
- Conditions
- COVID-19, Fatigue, Distress Respiratory Syndrome, Cognitive Dysfunction, COVID-19 Recurrent, SARS CoV 2 Infection
- Keywords
- Machine learning, Stress test, Cardiac variability, Voice recording, Skin conductance
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 136 participants (estimated)
- Lead sponsor
- Fundacin Biomedica Galicia SurUniversity, hospital or other
- Collaborators
- University of Vigo, Galician South Health Research Institute
- Study start
- 14 Dec 2022 (estimated)
- Primary completion
- Nov 2023 (estimated)
- Study completion
- Nov 2023 (estimated)
- First posted
- 29 Nov 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The pandemic caused by SARS-CoV-2 infection has resulted, in addition to the well-known acute symptoms, in the emergence of persistent, diffuse and heterogeneous symptoms referred to as persistent COVID.
Common symptoms include fatigue, shortness of breath, and cognitive dysfunction, among others, and result in an impact on daily functioning. Symptoms may be new onset, appear after initial recovery from an acute episode of COVID-19, or persist after the initial illness. Cardiac variability (HRV) was initially used in COVID-19 to predict mortality in the acute setting. Dysautonomia which partly evaluates HRV is frequent in patients with persistent COVID. Several groups have used voice or other respiratory noise analysis for the diagnosis of acute COVID.
Patients in the persistent COVID cohort will be able to be differentiated from an age, sex and vaccination status matched cohort of recovered COVID patients without sequelae by means of a model created by Machine Learning that will be trained using cardiac variability (HRV), skin conductance and acoustic analysis data. The primary objetive will be to obtain a classification algorithm by Machine Learning to differentiate the group of patients with persistent COVID diagnosis from the paired group of recovered COVID patients without sequelae.
Detailed description
This is a validation study of a Machine Learning algorithm for the diagnosis of persistent COVID using clinical diagnosis as the "gold standard". The sample will be composed of post-COVID patients, one group of which developed persistent COVID and another paired with the previous one with cured COVID without sequelae.
Study design
- Primary purpose
- Treatment
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (investigator)
- Number of arms
- 2
- Model description
- Persistent COVID group vs. Recovered COVID group
| Arm | Type | Receives |
|---|---|---|
| Persistent COVID group | Experimental | Other: Experimental testsPatients with persistent COVID will be recruited by the physicians of the Post COVID-19 Multidisciplinary Clinic of the Complexo Hospitalario Universitario de Ourense. |
| Recovered COVID group | Experimental | Other: Experimental testsThe controls will be recruited in a matched manner with the clinical sample in age, sex, epidemic wave and vaccination status, from among previously COVID-positive patients cured without sequelae and attended in Primary Care in the Health Centers of A Cuña, Valle Inclán and Novoa Santos in Ourense. |
Who may qualify
- Ages
- 18 to 70 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (14 listed)
- Age ≥18 and ≤70 years of age
- Confirmed infection (PCR) with SARS- CoV-2 until 03/28/2022 and thereafter date.
- Symptoms include: fatigue, respiratory distress or cognitive dysfunction, among others.
- Symptoms persist or appear more than 3 months after onset of infection.
- Symptoms last longer than 2 months and are not better explained by another diagnosis.
Key exclusion criteria (11 listed)
- Active COVID-19 infection.
- Cardiac arrhythmia, pacemaker carrier.
- Other pathologies with dysautonomia.
- Raynaud's phenomenon.
- Other diseases that may affect exercise capacity or be aggravated by exercise shall also be excluded, such as: Uncontrolled heart failure, severe or symptomatic aortic stenosis, pulmonary edema, acute respiratory failure, recent pulmonary thromboembolism, lower limb thrombosis, infections, thyrotoxicosis, or orthopedic inability to walk.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Experimental testsWalking for 6 minutes, sitting down and getting up from a chair for 1 minute and finally the cold test (Cold pressor) where the hand is introduced for 1 minute in water at 4ºC. The patient will be monitored by means of a Polar H10 chest strap, as used in sports, continuously and 02 saturation, TA and voice (exhalation while saying /a/ and dry cough) will be collected before and after the tests. Finally, skin conductance will be monitored by performing baseline tracing and then control while performing the cold test. | Other | Persistent COVID group, Recovered COVID group |
Primary outcome
Differences of the group of patients with a persistent diagnosis of COVID from the age-matched group, sex and vaccination status of patients recovered from COVID without sequelae.
Time frame: 8 weeks
Through an algorithm model created by Machine Learning that will be trained using cardic variability (HRV), skin conductance and acoustic analysis data.
6 secondary outcomes
Cardiac variability
Time frame: 8 weeks
Voice recording
Time frame: 8 weeks
Skin conductance
Time frame: 8 weeks
6MWT
Time frame: 8 weeks
1minSTST
Time frame: 8 weeks
Cold Pressor test
Time frame: 8 weeks
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Nov 2022.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
7 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Experimental tests in people with COVID-19 and Fatigue, run by Fundacin Biomedica Galicia Sur at 7 sites in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 14 inclusion and 11 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 29 Nov 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 7 sites in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Alejandro García Caballero, MD (988 38 55 00, alejandro.alberto.garcia.caballero@sergas.es), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Differences of the group of patients with a persistent diagnosis of COVID from the age-matched group, sex and vaccination status of patients recovered from COVID without sequelae. (time frame: 8 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Nov 2022.