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Differential Diagnosis of Persistent COVID-19 by Artificial Intelligence (DICOPERIA)

Primary Purpose

COVID-19, Fatigue, Distress Respiratory Syndrome

Status
Not yet recruiting
Phase
Not Applicable
Locations
Spain
Study Type
Interventional
Intervention
Experimental tests
Sponsored by
Fundacin Biomedica Galicia Sur
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional treatment trial for COVID-19 focused on measuring Machine learning, Stress test, Cardiac variability, Voice recording, Skin conductance

Eligibility Criteria

18 Years - 70 Years (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Persistent COVID group: Inclusion Criteria: 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. Symptoms may fluctuate or remit over time. Patients have capacity to consent and agree to participate in the study. Exclusion Criteria: 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 Inclusion Criteria: 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. Exclusion Criteria: 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.

Sites / Locations

  • Complexo Hospitalario Universitario de Ourense
  • Health Center Novoa Santos
  • Health Center Valle Inclán
  • S.S. Computer Engineering (University of Vigo)
  • Health Center A Cuña
  • Galicia Sur Health Research Institute (IISGS) - Hospital Álvaro Cunqueiro
  • School of Telecommunication Engineering (University of Vigo)

Arms of the Study

Arm 1

Arm 2

Arm Type

Experimental

Experimental

Arm Label

Persistent COVID group

Recovered COVID group

Arm Description

Patients with persistent COVID will be recruited by the physicians of the Post COVID-19 Multidisciplinary Clinic of the Complexo Hospitalario Universitario de Ourense.

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.

Outcomes

Primary Outcome Measures

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.

Secondary Outcome Measures

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.
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).
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.
6MWT
metres/min. The patient will walk the maximum distance they can in 6 minutes.
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..
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.

Full Information

First Posted
November 18, 2022
Last Updated
November 28, 2022
Sponsor
Fundacin Biomedica Galicia Sur
Collaborators
University of Vigo, Galician South Health Research Institute
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1. Study Identification

Unique Protocol Identification Number
NCT05629793
Brief Title
Differential Diagnosis of Persistent COVID-19 by Artificial Intelligence
Acronym
DICOPERIA
Official Title
Differential Diagnosis of Persistent COVID-19 by Artificial Intelligence
Study Type
Interventional

2. Study Status

Record Verification Date
November 2022
Overall Recruitment Status
Not yet recruiting
Study Start Date
December 14, 2022 (Anticipated)
Primary Completion Date
November 2023 (Anticipated)
Study Completion Date
November 2023 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Fundacin Biomedica Galicia Sur
Collaborators
University of Vigo, Galician South Health Research Institute

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

Brief 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. 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
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

7. Study Design

Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Model Description
Persistent COVID group vs. Recovered COVID group
Masking
Investigator
Masking Description
The investigators performing the tests will be blinded to the diagnostic group.
Allocation
Non-Randomized
Enrollment
136 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
Persistent COVID group
Arm Type
Experimental
Arm Description
Patients with persistent COVID will be recruited by the physicians of the Post COVID-19 Multidisciplinary Clinic of the Complexo Hospitalario Universitario de Ourense.
Arm Title
Recovered COVID group
Arm Type
Experimental
Arm Description
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.
Intervention Type
Other
Intervention Name(s)
Experimental tests
Intervention Description
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.
Primary Outcome Measure Information:
Title
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.
Description
Through an algorithm model created by Machine Learning that will be trained using cardic variability (HRV), skin conductance and acoustic analysis data.
Time Frame
8 weeks
Secondary Outcome Measure Information:
Title
Cardiac variability
Description
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.
Time Frame
8 weeks
Title
Voice recording
Description
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).
Time Frame
8 weeks
Title
Skin conductance
Description
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.
Time Frame
8 weeks
Title
6MWT
Description
metres/min. The patient will walk the maximum distance they can in 6 minutes.
Time Frame
8 weeks
Title
1minSTST
Description
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..
Time Frame
8 weeks
Title
Cold Pressor test
Description
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.
Time Frame
8 weeks
Other Pre-specified Outcome Measures:
Title
Age
Description
Years
Time Frame
8 weeks
Title
Sex
Description
Male, Female
Time Frame
8 weeks
Title
Current treatment
Description
Treatment taken by the patient at the time of the study.
Time Frame
8 weeks
Title
Date of PCR + SARS-CoV-2
Description
DD-MMM-YYYY
Time Frame
8 weeks
Title
Epidemic wave
Description
Of the 7 waves of COVID-19 that have occurred in Spain, a description will be given of the wave to which the infection of each patient included belonged. First, second, third, fourth, fifth, sixth, seventh, eighth, ninth or tenth wave.
Time Frame
8 weeks
Title
Vaccination status at the time of infection
Description
Number of vaccines doses at the time of infection
Time Frame
8 weeks
Title
FVC
Description
Is the maximum volume of air exhaled, with the maximum possible effort, starting from a maximum inspiration in ml.
Time Frame
8 weeks
Title
FEV1
Description
The volume of air expelled during the first second of forced expiration in ml.
Time Frame
8 weeks
Title
FEV1/ FVC
Description
Expressed as a percentage (%), it indicates the proportion of the FVC that is expelled during the first second of the forced expiratory maneuver.
Time Frame
8 weeks
Title
CO diffusion test
Description
To evaluate the transfer of oxygen from the alveolar space to the hemoglobin of the erythrocytes contained in the pulmonary capillaries. Effective alveolar-capillary area available for gas transfer in the lung. (%)
Time Frame
8 weeks

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
70 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Persistent COVID group: Inclusion Criteria: 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. Symptoms may fluctuate or remit over time. Patients have capacity to consent and agree to participate in the study. Exclusion Criteria: 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 Inclusion Criteria: 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. Exclusion Criteria: 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.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Alejandro García Caballero, MD
Phone
988 38 55 00
Email
alejandro.alberto.garcia.caballero@sergas.es
Facility Information:
Facility Name
Complexo Hospitalario Universitario de Ourense
City
Ourense
ZIP/Postal Code
32002
Country
Spain
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Alejandro García Caballero, MD
Email
alejandro.alberto.garcia.caballero@sergas.es
First Name & Middle Initial & Last Name & Degree
Alejandro García Caballero, MD
First Name & Middle Initial & Last Name & Degree
María Bustillo Casado, MD
First Name & Middle Initial & Last Name & Degree
María Dolores Díaz López, MD
First Name & Middle Initial & Last Name & Degree
Pablo López Mato, MD
First Name & Middle Initial & Last Name & Degree
Luis Docasar Bertolo, MD
First Name & Middle Initial & Last Name & Degree
Beatriz Gómez Gómez, MD
Facility Name
Health Center Novoa Santos
City
Ourense
ZIP/Postal Code
32003
Country
Spain
Facility Name
Health Center Valle Inclán
City
Ourense
ZIP/Postal Code
32004
Country
Spain
Facility Name
S.S. Computer Engineering (University of Vigo)
City
Ourense
ZIP/Postal Code
32004
Country
Spain
Facility Name
Health Center A Cuña
City
Ourense
ZIP/Postal Code
32005
Country
Spain
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Carlos Menéndez Villalva
Facility Name
Galicia Sur Health Research Institute (IISGS) - Hospital Álvaro Cunqueiro
City
Vigo
ZIP/Postal Code
36213
Country
Spain
Facility Name
School of Telecommunication Engineering (University of Vigo)
City
Vigo
ZIP/Postal Code
36310
Country
Spain

12. IPD Sharing Statement

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Differential Diagnosis of Persistent COVID-19 by Artificial Intelligence

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