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

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.

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Key information

Conditions

Post-Acute COVID-19 Syndrome Behavior COVID-19 Chronic Disease Coronaviridae Infections Coronavirus Infections Disease Attributes Infections Lung Diseases Nidovirales Infections Pathologic Processes Pathological Conditions, Signs and Symptoms Personal Satisfaction Pneumonia Pneumonia, Viral Post-Infectious Disorders Psychological Well-Being RNA Virus Infections Respiratory Tract Diseases Respiratory Tract Infections Virus Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Virgen Macarena University Hospital

Seville, 41009, Spain

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Review of available clinical data sources related to use cases

Other

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

Primary outcomes

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.

Sponsors and collaborators

Lead sponsor

Adhera Health, Inc.

Industry

Collaborators

Hospital Universitario Virgen Macarena

Registry information

Official study title

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

Acronym: SENSING-AI

Important dates

Study start: 2022
Primary completion: 2022
Study completion: 2022
First posted: Feb 7, 2024
Registry last updated: Feb 18, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed