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CompletedNCT05204615SENSING-AIUpdated Jan 5, 2023

SENSING-AI Cohort for Long COVID Patients

An observational study in Post-acute COVID-19 Syndrome, sponsored by Adhera Health, Inc.. Completed at 2 sites in Spain. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2023-01-05.

Sponsored by Adhera Health, Inc. · Observational

Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
10
Ages
18 Years and older
Sex
All
01

Study 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.

Read the detailed description

The stratification of the risk of complications related to persistent COVID symptoms 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 of this study is to complement the SENSING-AI cohort with biometric and psychometric data prospectively gathered from patients diagnosed with long COVID in the last year to drive the generation of AI-based risk prediction and stratification models.

02

Conditions studied

  • Post-acute COVID-19 Syndrome

Keywords

  • COVID-19 syndrome
  • Prospective study
  • Artificial Intelligence
  • Mental Health
03

In context

Post-Acute COVID-19 Syndrome

536 studies on the registry are indexed under Post-Acute COVID-19 Syndrome; 187 are open to participants now.

This study's enrollment of 10 is below the median of 160 across 149 observational studies indexed under Post-Acute COVID-19 Syndrome.

Browse Post-Acute COVID-19 Syndrome studies →

Lead sponsor

Adhera Health, Inc. is the lead sponsor of 11 studies on the registry; 1 is open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
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.

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • 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

Exclusion criteria

Exclusion Criteria:

  • 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
05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
10 participants (actual)
Patient registry
No

Groups and cohorts

  • 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

  • OtherCollection of clinical, psychometric and biometric data

    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.

06

What researchers measure

Primary outcomes

  1. 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.

    Time frame: 1 month

  2. 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.

    Time frame: 1 month

  3. 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.

    Time frame: 1 month

  4. 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.

    Time frame: 1 month

  5. Physical Activity Bpm

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

    Time frame: 1 month

  6. 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.

    Time frame: 1 month

  7. Physical Activity Oxygen Saturation

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

    Time frame: 1 month

  8. Workouts Kcal

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

    Time frame: 1 month

  9. 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.

    Time frame: 1 month

  10. Workouts Bpm

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

    Time frame: 1 month

  11. 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.

    Time frame: 1 month

  12. 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.

    Time frame: 1 month

  13. 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.

    Time frame: 1 month

  14. Sleep quality Rapid Eye Movement

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

    Time frame: 1 month

  15. Sleep quality Bpm

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

    Time frame: 1 month

  16. Sleep quality Breathing

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

    Time frame: 1 month

  17. 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.

    Time frame: Weekly up to 1 month

  18. 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.

    Time frame: Weekly up to 1 month

  19. 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.

    Time frame: Weekly up to 1 month

  20. 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.

    Time frame: Weekly up to 1 month

  21. 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.

    Time frame: Weekly up to 1 month

  22. 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.

    Time frame: Weekly up to 1 month

07

Study locations

2 sites
  • IDIAP Jordi Gol
    Barcelona, 08007, Spain
  • Primary Care Aljarafe-Sevilla Norte
    Seville, 41927, Spain
08

References and documents

Publications

  • 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. PubMed 12670612 ↗
  • 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. PubMed 25311596 ↗
  • 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. PubMed 16673626 ↗
  • 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. PubMed 34230698 ↗
  • 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. PubMed 31447721 ↗
  • 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. PubMed 11556941 ↗
  • 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. PubMed 23034346 ↗
  • 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. PubMed 36166648 ↗

Individual participant data

Plan to share: No

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jan 5, 2023, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT05204615
Lead sponsor
Adhera Health, Inc.
Responsible party
Sponsor
First posted
Jan 24, 2022
Start date
Jan 18, 2022
Primary completion
Feb 12, 2022
Completion
Apr 28, 2022
Last update
Jan 5, 2023

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Jan 2022. You cannot join it, but the record below documents what was studied.

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