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

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

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06247332

Acronym

SENSING-AI

Enrollment

103

Registered

2024-02-07

Start date

2022-01-18

Completion date

2022-02-25

Last updated

2025-02-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Post-acute COVID-19 Syndrome

Keywords

Long COVID-19, Retrospective study, Artificial Intelligence, Mental Health

Brief summary

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.

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.

Interventions

OTHERReview 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

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

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

Design outcomes

Primary

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

Countries

Spain

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026