SENSING-AI in Patients with Long COVID (SENSING-AI) (SENSING-AI)

February 14, 2025 updated by: Adhera Health, Inc.

Retrospective Data Collection for SENSING-AI: a Wearable Platform for the Early Diagnosis of Emotional Disorders and Exacerbations in Patients with Long COVID Through the Use of Artificial Intelligence

The retrospective study will be used to develop an artificial intelligence model of risk stratification of physiological and psychological complications arising from the information available in the electronic medical record and first consultation report to support patients and healthcare professionals in better managing the healthcare process for patients diagnosed with long COVID.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

The stratification of the risk of complications related to persistent COVID both physiological and psychological in a personalized way would optimize the cost-effectiveness model for the management of these patients. Similarly, the early detection of complications associated with persistent COVID in patients belonging to vulnerable groups would improve care times and, therefore, the patient's prognosis.

The primary objective for this study is to gather anonymized retrospective data of patients suffering from long COVID in order to contribute to the generation of the SENSING-AI cohort.

Study Type

Observational

Enrollment (Actual)

103

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Spain
      • Seville, Spain, 41009
        • Virgen Macarena University Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

The sample size for the retrospective study enough to generate a first version of the risk stratification models will be around 100 cases. The target population will be as balanced as possible between subjects who needed specialized care due to long COVID-19 complications (either specialized care consultations or any non-planned hospital admission) at 1 month, 3 months, 6 months and 1 year from the long COVID-19 diagnose and those who did not require such specialized care.

Description

Inclusion Criteria:

  • Legal adult
  • Diagnosed of long COVID-19 in the last year
  • With the presence of any of these symptoms:
  • Asthenia (Tiredness)
  • Dyspnea
  • Shortness of breath
  • Anxiety
  • Stress
  • Depression
  • Sleep disorder

Exclusion Criteria:

  • Attended to specialized care consultation
  • Was admitted in hospital in the last year due to a problem not related to the COVID complications

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Retrospective Long COVID cases
The target population will be as balanced as possible between subjects who needed specialized care due to long COVID-19 complications (either specialized care consultations or any non-planned hospital admission) at 1 month, 3 months, 6 months and 1 year from the long COVID-19 diagnose and those who did not require such specialized care.
Other: Review of available clinical data sources related to use cases
There will be a review of available clinical data sources related to use cases. In addition, this information will be complemented by a cohort of anonymized retrospective data of 100 cases obtained from the clinical information resulting from the assistance to COVID-19 patients managed by the Primary Care Health District of Sevilla Norte and the Infectious Diseases Department of the Virgen Macarena University Hospital

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Retrospective SENSING-AI cohort
Time Frame: 1 month
The retrospective SENSING-AI cohort will be fed from clinical information of 100 cases of patients with long COVID-19.
1 month

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Adhera Health, Inc.

Collaborators

Hospital Universitario Virgen Macarena

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 18, 2022

Primary Completion (Actual)

February 25, 2022

Study Completion (Actual)

February 25, 2022

Study Registration Dates

First Submitted

January 31, 2024

First Submitted That Met QC Criteria

January 31, 2024

First Posted (Actual)

February 7, 2024

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

February 14, 2025

Last Verified

February 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • SEN-0121

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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