SENSING-AI Cohort for Long COVID Patients

NCT05204615 | Completed

• 1 other identifier: SEN-0221
• Study Type: observational
• Target: 10
• Locations: 1 country
• Sites: 2

Brief Summary

The prospective study will focus on the collection of biometric and psychometric data from a limited population for 1 month with the aim of complementing the SENSING-AI retrospective cohort.

Conditions

Post-acute COVID-19 Syndrome

Keywords

COVID-19 syndrome; Prospective study; Artificial Intelligence; Mental Health

Outcome Measures

Primary Outcomes (22)

• Physical Activity Distances

  Through the Withings Scanwatch the following physical activity data are gathered: Daily distance travelled in metres; List of distance travelled/ 4-5 minutes approx.; Daily number of floors climbed in metres; List of distance travelled/ approx. 4-5 minutes.

  1 month

• Physical Activity in Steps

  Through the Withings Scanwatch the following physical activity data are gathered: Daily number of steps; List of steps/ 4-5 minutes approximately.

  1 month

• Physical Activity Duration

  Through the Withings Scanwatch the following physical activity data are gathered: Daily duration of light, moderate and intense intensity activities in seconds; Daily sum of moderate and intense activities in seconds.

  1 month

• Physical Activity Kcal

  Through the Withings Scanwatch the following physical activity data are gathered: Daily active calories burned in Kcal; Total daily calories burned in Kcal; List of calories burned/ approx. 4-5 minutes.

  1 month

• Physical Activity Bpm

  Through the Withings Scanwatch the following physical activity data are gathered: Daily minimum/average/maximum heart rate in bpm.

  1 month

• Physical Activity Heart Rate

  Through the Withings Scanwatch the following physical activity data are gathered: Daily duration in seconds of heart rate; List of heart rate measurements/10 minutes/average rate.

  1 month

• Physical Activity Oxygen Saturation

  Through the Withings Scanwatch the following physical activity data are gathered: Manual Oxygen Saturation (SpO2) measurements.

  1 month

• Workouts Kcal

  Through the Withings Scanwatch the following workouts data are gathered: Calories / workout events in Kcal.

  1 month

• Workouts distances

  Through the Withings Scanwatch the following workouts data are gathered: Distance of the workouts in meters; Steps climbed in metres; Step run in meters.

  1 month

• Workouts Bpm

  Through the Withings Scanwatch the following workouts data are gathered: Heart rate/minimum/average/maximum intensity in bpm.

  1 month

• Workouts Heart Rate

  Through the Withings Scanwatch the following workouts data are gathered: Duration in the minimum/moderate/intense heart rate zone in seconds; Duration of maximum heart rate in seconds.

  1 month

• Sleep quality Number of Times Awake

  Through the Withings Scanwatch the following sleep quality data are gathered: Number of times the user woke up; Number of times the user got out of bed during the night.

  1 month

• Sleep quality duration

  Through the Withings Scanwatch the following sleep quality data are gathered: Total time spent in bed in seconds; Total time asleep in seconds; Time spent in bed before falling asleep in seconds; Time spent in bed after waking up in seconds; Time spent awake in bed after falling asleep for the first time during the night in seconds; Duration in light resting state in seconds; Duration in deep sleep state in seconds; Ratio of total sleep time/time spent in bed.

  1 month

• Sleep quality Rapid Eye Movement

  Through the Withings Scanwatch the following sleep quality data are gathered: Rapid Eye Movement (REM) sleep phase count.

  1 month

• Sleep quality Bpm

  Through the Withings Scanwatch the following sleep quality data are gathered: Average heart rate in bpm; Average minimum bpm rate.

  1 month

• Sleep quality Breathing

  Through the Withings Scanwatch the following sleep quality data are gathered: Intensity of breathing disturbances.

  1 month

• Fatigue Assessment Scale

  The Fatigue Assessment Scale is a unidimensional scale, consisting of 10-items measured on 5-point rating scale varies from 1 never to 5 always. Scores range from 10 to 50 with higher scores indicating greater fatigue.

  Weekly up to 1 month

• Dyspnoea Index

  Dyspnoea Index is a unidimensional scale, consisting of 10-items evaluated on a 0-4 Likert Scale (0= never; 1= almost never; 2= sometimes; 3= almost always; 4= always). Scores range from 0 to 40 and higher scores indicate greater dyspnea.

  Weekly up to 1 month

• Generalized Anxiety Disorder 7-Item Scale

  Generalized Anxiety Disorder 7-Item Scale consists of 7 items measured on 4-point rating scale varies from 0 (not at all) to 3 (nearly every day). Scores range from 0 to 21 with higher scores indicating higher anxiety levels.

  Weekly up to 1 month

• Perceived Stress Scale

  Perceived Stress Scale consists of 10 items measures on 4-point rating scale varies from 0 (never) to 4 (nearly every day). Scores range from 0 to 40 with higher scores indicating higher perceived stress.

  Weekly up to 1 month

• Patient Health Questionnaire-9

  Patient Health Questionnaire-9 consists of 9 items measures on 4-point rating scale varies from 0 (never) to 3 (nearly every day). Scores range from 0 to 27 and higher scores indicate higher depression levels.

  Weekly up to 1 month

• Oviedo Sleep Questionnaire

  Oviedo Sleep Questionnaire consists of 15 items, 13 form the scale itself and two are descriptive items to provide the clinician with information on parasomnias and on the type and frequency of use of any type of sleep aid. The 13 items are grouped in 3 subscales: a) Subjective satisfaction with sleep: 1 item. Likert scale of satisfaction with 7 values ranging from 1 (very dissatisfied) to 7 (very satisfied); b) Insomnia: made up of 9 items to assess the nature of insomnia (difficulties in reconciling sleep, maintenance, early awakening, non-restorative sleep) and its repercussions on wakefulness (worry/tiredness/decreased functioning. Scored on a 5-value Likert scale (from 1 to 5) where the higher the score, the greater the severity; c) Hypersomnia: consisting of 3 items that assess daytime sleepiness and concern/decreased functioning for this reason. Scored on a 5-value Likert scale (from 1 to 5) where the higher the score, the greater the severity.

  Weekly up to 1 month

Study Arms (1)

Prospective Long COVID cases

The target population will be 10 patients diagnosed during 2021 with long COVID, who will then be followed-up for one month.

Other: Collection of clinical, psychometric and biometric data

Interventions

Collection of clinical, psychometric and biometric data OTHER

Wearable devices and a mobile app will be used to collect real-time data for 4 weeks to detect physiological and psychological complications based on biometric and psychometric (patient-reported outcomes) information.

Prospective Long COVID cases

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Sample will be recruited from patients attending Primary Care Aljarafe-Sevilla Norte centers and Jordi Gol Primary Care Research Institute.

You may qualify if:

• Legal adults
• With a long COVID-19 diagnose in the last year
• Reporting any of these symptoms:
• Fatigue
• Dyspnea
• Shortness of breath
• Anxiety
• Stress
• Depression
• Conduct disorder
• Sleep disorder

You may not qualify if:

• Hospital admission during follow-up due to pathology not related to COVID-19
• Patients without digital literacy or who cannot use the mobile application.
• Known severe psychiatric illness or cognitive impairment
• Being pregnant (or suspected to be pregnant)
• Discharged after hospital admission due to COVID-19

Sponsors & Collaborators

• Adhera Health, Inc.: lead
• Fundación Pública Andaluza para la gestión de la Investigación en Sevilla: collaborator
• Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina: collaborator

Study Sites (2)

IDIAP Jordi Gol

Barcelona, 08007, Spain

Location

Primary Care Aljarafe-Sevilla Norte

Seville, 41927, Spain

Location

Related Publications (8)

• Michielsen HJ, De Vries J, Van Heck GL. Psychometric qualities of a brief self-rated fatigue measure: The Fatigue Assessment Scale. J Psychosom Res. 2003 Apr;54(4):345-52. doi: 10.1016/s0022-3999(02)00392-6.

  PMID: 12670612 BACKGROUND

• Gartner-Schmidt JL, Shembel AC, Zullo TG, Rosen CA. Development and validation of the Dyspnea Index (DI): a severity index for upper airway-related dyspnea. J Voice. 2014 Nov;28(6):775-82. doi: 10.1016/j.jvoice.2013.12.017. Epub 2014 Oct 12.

  PMID: 25311596 BACKGROUND

• Remor E. Psychometric properties of a European Spanish version of the Perceived Stress Scale (PSS). Span J Psychol. 2006 May;9(1):86-93. doi: 10.1017/s1138741600006004.

  PMID: 16673626 BACKGROUND

• Campo-Arias A, Pedrozo-Pupo JC, Cogollo-Milanes Z. [PHQ-9 in screening of major depressive episode among COVID-19 survivors]. Rev Colomb Psiquiatr (Engl Ed). 2021 Jul 2. doi: 10.1016/j.rcp.2021.06.004. Online ahead of print. No abstract available. Spanish.

  PMID: 34230698 BACKGROUND

• Johnson SU, Ulvenes PG, Oktedalen T, Hoffart A. Psychometric Properties of the General Anxiety Disorder 7-Item (GAD-7) Scale in a Heterogeneous Psychiatric Sample. Front Psychol. 2019 Aug 6;10:1713. doi: 10.3389/fpsyg.2019.01713. eCollection 2019.

  PMID: 31447721 BACKGROUND

• Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606-13. doi: 10.1046/j.1525-1497.2001.016009606.x.

  PMID: 11556941 BACKGROUND

• Paz Garcia-Portilla M, Saiz PA, Diaz-Mesa EM, Fonseca E, Arrojo M, Sierra P, Sarramea F, Sanchez E, Goikole JM, Balanza V, Benabarre A, Bobes J. Psychometric performance of the Oviedo Sleep Questionnaire in patients with severe mental disorder. Rev Psiquiatr Salud Ment. 2009 Oct;2(4):169-77. doi: 10.1016/S1888-9891(09)73235-5. Epub 2010 Jan 25. English, Spanish.

  PMID: 23034346 BACKGROUND

• Fuster-Casanovas A, Fernandez-Luque L, Nunez-Benjumea FJ, Moreno Conde A, Luque-Romero LG, Bilionis I, Rubio Escudero C, Chicchi Giglioli IA, Vidal-Alaball J. An Artificial Intelligence-Driven Digital Health Solution to Support Clinical Management of Patients With Long COVID-19: Protocol for a Prospective Multicenter Observational Study. JMIR Res Protoc. 2022 Oct 14;11(10):e37704. doi: 10.2196/37704.

  PMID: 36166648 DERIVED

Related Links

• Withings Scanwatch

MeSH Terms

Conditions

Post-Acute COVID-19 Syndrome; Psychological Well-Being

Interventions

Psychometrics

Condition Hierarchy (Ancestors)

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

Intervention Hierarchy (Ancestors)

Psychological Tests; Behavioral Disciplines and Activities

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 10, 2022
• First Posted: January 24, 2022
• Study Start: January 18, 2022
• Primary Completion: February 12, 2022
• Study Completion: April 28, 2022
• Last Updated: January 5, 2023

Record last verified: 2022-01

Data Sharing

• IPD Sharing: Will not share

Locations

ES (2)