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Differential Diagnosis of Persistent COVID-19 by Artificial Intelligence

NCT05629793 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 136

Last updated 2022-11-29

No results posted yet for this study

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.

Conditions

  • COVID-19
  • Fatigue
  • Distress Respiratory Syndrome
  • Cognitive Dysfunction
  • COVID-19 Recurrent
  • SARS CoV 2 Infection

Interventions

OTHER

Experimental tests

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.

Sponsors & Collaborators

  • University of Vigo

    collaborator OTHER

  • Galician South Health Research Institute

    collaborator NETWORK

  • Fundacin Biomedica Galicia Sur

    lead OTHER

Study Design

Allocation
NON_RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-12-14
Primary Completion
2023-11-30
Completion
2023-11-30

Countries

  • Spain

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05629793 on ClinicalTrials.gov