Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH): Protocol for a Prospective Observational Study

Yatharth Ranjan, Malik Althobiani, Joseph Jacob, Michele Orini, Richard Jb Dobson, Joanna Porter, John Hurst, Amos A Folarin, Yatharth Ranjan, Malik Althobiani, Joseph Jacob, Michele Orini, Richard Jb Dobson, Joanna Porter, John Hurst, Amos A Folarin

Abstract

Background: Chronic lung disorders like chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are characterized by exacerbations. They are unpleasant for patients and sometimes severe enough to cause hospital admission and death. Moreover, due to the COVID-19 pandemic, vulnerable populations with these disorders are at high risk, and their routine care cannot be done properly. Remote monitoring offers a low cost and safe solution for gaining visibility into the health of people in their daily lives, making it useful for vulnerable populations.

Objective: The primary objective is to assess the feasibility and acceptability of remote monitoring using wearables and mobile phones in patients with pulmonary diseases. The secondary objective is to provide power calculations for future studies centered around understanding the number of exacerbations according to sample size and duration.

Methods: Twenty participants will be recruited in each of three cohorts (COPD, IPF, and posthospitalization COVID). Data collection will be done remotely using the RADAR-Base (Remote Assessment of Disease And Relapse) mobile health (mHealth) platform for different devices, including Garmin wearable devices and smart spirometers, mobile app questionnaires, surveys, and finger pulse oximeters. Passive data include wearable-derived continuous heart rate, oxygen saturation, respiration rate, activity, and sleep. Active data include disease-specific patient-reported outcome measures, mental health questionnaires, and symptom tracking to track disease trajectory. Analyses will assess the feasibility of lung disorder remote monitoring (including data quality, data completeness, system usability, and system acceptability). We will attempt to explore disease trajectory, patient stratification, and identification of acute clinical events such as exacerbations. A key aspect is understanding the potential of real-time data collection. We will simulate an intervention to acquire responses at the time of the event to assess model performance for exacerbation identification.

Results: The Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH) study provides a unique opportunity to assess the use of remote monitoring in the evaluation of lung disorders. The study started in the middle of June 2021. The data collection apparatus, questionnaires, and wearable integrations were setup and tested by the clinical teams prior to the start of recruitment. While recruitment is ongoing, real-time exacerbation identification models are currently being constructed. The models will be pretrained daily on data of previous days, but the inference will be run in real time.

Conclusions: The RALPMH study will provide a reference infrastructure for remote monitoring of lung diseases. It specifically involves information regarding the feasibility and acceptability of remote monitoring and the potential of real-time data collection and analysis in the context of chronic lung disorders. It will help plan and inform decisions in future studies in the area of respiratory health.

Trial registration: ISRCTN Registry ISRCTN16275601; https://www.isrctn.com/ISRCTN16275601.

International registered report identifier (irrid): PRR1-10.2196/28873.

Keywords: COVID-19; cardiopulmonary diseases; internet of things; lung diseases; mHealth; mental health; mobile health; remote monitoring; respiratory health; wearables.

Conflict of interest statement

Conflicts of Interest: JJ has received consultancy fees from Boehringer Ingelheim, Roche, GSK, and NHSX unrelated to the submitted work. YR, RJBD and AAF were actively involved in the development of RADAR-Base platform and applications. There were no financial interests for this work and contributions were made to open-source software. The other authors have no conflicts to declare.

©Yatharth Ranjan, Malik Althobiani, Joseph Jacob, Michele Orini, Richard JB Dobson, Joanna Porter, John Hurst, Amos A Folarin. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 07.10.2021.

Figures

Figure 1
Figure 1
Time course of symptoms and oximetry variables at exacerbation [11]. PEF: peak airflow.
Figure 2
Figure 2
The Active Remote Monitoring Technology (aRMT) app used to collect phone-delivered questionnaires. Top: app screens and example questionnaire. Bottom left: Example notification to complete the questionnaire. Bottom right: Speech task.
Figure 3
Figure 3
Study flow diagram. CAT: COPD assessment test; CCLTE: CDC COVID-19 long-term effects; COPD: chronic obstructive pulmonary disease; EoP: experience of participation; ERS: Exacerbation Rating Scale; FSS: Fatigue Severity Scale; GAD-7: Generalized Anxiety Disorder scale; ILD: interstitial lung disease; IPF: idiopathic pulmonary fibrosis; l-IPF: living with idiopathic pulmonary fibrosis; KBILD: The King's Brief Interstitial Lung Disease; MRC: Medical Research Council; PCFS: post-COVID function status; PHQ-8: Patient Health Questionnaire depression scale; PROM: patient-reported outcome measure; PSQI: Pittsburgh Sleep Quality Index; RADAR: Remote Assessment of Disease and Relapse; SGRQ: St. George's Respiratory Questionnaire; TAMF: Technology Acceptance Model Fast Form; VAS: visual analog scale; WCS: World Health Organization COVID-19 symptoms.
Figure 4
Figure 4
Study timeline. aRMT: Active Remote Monitoring Technology; eCRF: electronic case report form; RADAR: Remote Assessment of Disease and Relapse.

References

    1. Drake TM, Docherty AB, Harrison EM, Quint JK, Adamali H, Agnew S, Babu S, Barber CM, Barratt S, Bendstrup E, Bianchi S, Villegas DC, Chaudhuri N, Chua F, Coker R, Chang W, Crawshaw A, Crowley LE, Dosanjh D, Fiddler CA, Forrest IA, George PM, Gibbons MA, Groom K, Haney S, Hart SP, Heiden E, Henry M, Ho L, Hoyles RK, Hutchinson J, Hurley K, Jones M, Jones S, Kokosi M, Kreuter M, MacKay LS, Mahendran S, Margaritopoulos G, Molina-Molina M, Molyneaux PL, O'Brien A, O'Reilly K, Packham A, Parfrey H, Poletti V, Porter JC, Renzoni E, Rivera-Ortega P, Russell A, Saini G, Spencer LG, Stella GM, Stone H, Sturney S, Thickett D, Thillai M, Wallis T, Ward K, Wells AU, West A, Wickremasinghe M, Woodhead F, Hearson G, Howard L, Baillie JK, Openshaw PJM, Semple MG, Stewart I, Jenkins RG, ISARIC4C Investigators Outcome of Hospitalization for COVID-19 in Patients with Interstitial Lung Disease. An International Multicenter Study. Am J Respir Crit Care Med. 2020 Dec 15;202(12):1656–1665. doi: 10.1164/rccm.202007-2794OC.
    1. Ranjan Y, Rashid Z, Stewart C, Conde P, Begale M, Verbeeck D, Boettcher S, Hyve. Dobson R, Folarin A, RADAR-CNS Consortium RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices. JMIR Mhealth Uhealth. 2019 Aug 01;7(8):e11734. doi: 10.2196/11734. v7i8e11734
    1. RADAR-base. [2021-05-22].
    1. Apache Avro. Wikipedia. [2021-11-06]. .
    1. King TE, Tooze JA, Schwarz MI, Brown KR, Cherniack RM. Predicting survival in idiopathic pulmonary fibrosis: scoring system and survival model. Am J Respir Crit Care Med. 2001 Oct 01;164(7):1171–81. doi: 10.1164/ajrccm.164.7.2003140.
    1. Lung disease in the UK. British Lung Foundation. [2020-12-16]. .
    1. Collard HR, Ryerson CJ, Corte TJ, Jenkins G, Kondoh Y, Lederer DJ, Lee JS, Maher TM, Wells AU, Antoniou KM, Behr J, Brown KK, Cottin V, Flaherty KR, Fukuoka J, Hansell DM, Johkoh T, Kaminski N, Kim DS, Kolb M, Lynch DA, Myers JL, Raghu G, Richeldi L, Taniguchi H, Martinez FJ. Acute Exacerbation of Idiopathic Pulmonary Fibrosis. An International Working Group Report. Am J Respir Crit Care Med. 2016 Aug 01;194(3):265–75. doi: 10.1164/rccm.201604-0801CI.
    1. Richeldi L, du Bois RM, Raghu G, Azuma A, Brown KK, Costabel U, Cottin V, Flaherty KR, Hansell DM, Inoue Y, Kim DS, Kolb M, Nicholson AG, Noble PW, Selman M, Taniguchi H, Brun M, Le Maulf F, Girard M, Stowasser S, Schlenker-Herceg R, Disse B, Collard HR, INPULSIS Trial Investigators Efficacy and safety of nintedanib in idiopathic pulmonary fibrosis. N Engl J Med. 2014 May 29;370(22):2071–82. doi: 10.1056/NEJMoa1402584. 10.1186/s12890-019-1030-4
    1. Mikolasch TA, Garthwaite HS, Porter JC. Update in diagnosis and management of interstitial lung disease . Clin Med (Lond) 2017 May;17(2):146–153. doi: 10.7861/clinmedicine.17-2-146. 17/2/146
    1. Management and Prevention of COPD. Global Initiative for Chronic Obstructive Lung Disease (GOLD) [2020-12-16].
    1. Hurst JR, Vestbo J, Anzueto A, Locantore N, Müllerova H, Tal-Singer R, Miller B, Lomas DA, Agusti A, Macnee W, Calverley P, Rennard S, Wouters EFM, Wedzicha JA, Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med. 2010 Oct 16;363(12):1128–38. doi: 10.1056/NEJMoa0909883.
    1. Hurst JR, Donaldson GC, Quint JK, Goldring JJP, Patel ARC, Wedzicha JA. Domiciliary pulse-oximetry at exacerbation of chronic obstructive pulmonary disease: prospective pilot study. BMC Pulm Med. 2010 Oct 20;10:52. doi: 10.1186/1471-2466-10-52. 1471-2466-10-52
    1. Al Rajeh AM, Aldabayan YS, Aldhahir A, Pickett E, Quaderi S, Alqahtani JS, Mandal S, Lipman MC, Hurst JR. Once Daily Versus Overnight and Symptom Versus Physiological Monitoring to Detect Exacerbations of Chronic Obstructive Pulmonary Disease: Pilot Randomized Controlled Trial. JMIR Mhealth Uhealth. 2020 Nov 13;8(11):e17597. doi: 10.2196/17597. v8i11e17597
    1. The Post-hospitalisation COVID-19 study (PHOSP-COVID) PHOSP. [2020-10-12]. .
    1. COVID-19. Centers for Disease Control and Prevention. [2020-11-12]. .
    1. Varatharaj A, Thomas N, Ellul MA, Davies NWS, Pollak TA, Tenorio EL, Sultan M, Easton A, Breen G, Zandi M, Coles JP, Manji H, Al-Shahi Salman R, Menon DK, Nicholson TR, Benjamin LA, Carson A, Smith C, Turner MR, Solomon T, Kneen R, Pett SL, Galea I, Thomas RH, Michael BD, Allen C, Archibald N, Arkell J, Arthur-Farraj P, Baker M, Ball H, Bradley-Barker V, Brown Z, Bruno S, Carey L, Carswell C, Chakrabarti A, Choulerton J, Daher M, Davies R, Di Marco Barros R, Dima S, Dunley R, Dutta D, Ellis R, Everitt A, Fady J, Fearon P, Fisniku L, Gbinigie I, Gemski A, Gillies E, Gkrania-Klotsas E, Grigg J, Hamdalla H, Hubbett J, Hunter N, Huys A, Ihmoda I, Ispoglou S, Jha A, Joussi R, Kalladka D, Khalifeh H, Kooij S, Kumar G, Kyaw S, Li L, Littleton E, Macleod M, Macleod Mj, Madigan B, Mahadasa V, Manoharan M, Marigold R, Marks I, Matthews P, Mccormick M, Mcinnes C, Metastasio A, Milburn-McNulty P, Mitchell C, Mitchell D, Morgans C, Morris H, Morrow J, Mubarak Mohamed A, Mulvenna P, Murphy L, Namushi R, Newman E, Phillips W, Pinto A, Price Da, Proschel H, Quinn T, Ramsey D, Roffe C, Ross Russell A, Samarasekera N, Sawcer S, Sayed W, Sekaran L, Serra-Mestres J, Snowdon V, Strike G, Sun J, Tang C, Vrana M, Wade R, Wharton C, Wiblin L, Boubriak I, Herman K, Plant G. Neurological and neuropsychiatric complications of COVID-19 in 153 patients: a UK-wide surveillance study. The Lancet Psychiatry. 2020 Oct;7(10):875–882. doi: 10.1016/S2215-0366(20)30287-X. S2215-0366(20)30287-X
    1. COVID Collab. [2020-11-16].
    1. RADAR-CNS. [2019-05-22].
    1. Matcham F, Barattieri di San Pietro C, Bulgari V, de Girolamo G, Dobson R, Eriksson H, Folarin AA, Haro JM, Kerz M, Lamers F, Li Q, Manyakov NV, Mohr DC, Myin-Germeys I, Narayan V, Bwjh P, Ranjan Y, Rashid Z, Rintala A, Siddi S, Simblett SK, Wykes T, Hotopf M, RADAR-CNS consortium Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol. BMC Psychiatry. 2019 Feb 18;19(1):72. doi: 10.1186/s12888-019-2049-z. 10.1186/s12888-019-2049-z
    1. Shah SA, Velardo C, Farmer A, Tarassenko L. Exacerbations in Chronic Obstructive Pulmonary Disease: Identification and Prediction Using a Digital Health System. J Med Internet Res. 2017 Mar 07;19(3):e69. doi: 10.2196/jmir.7207. v19i3e69
    1. Ismail A, Musa A, Zim M, Fadzil M, Razali N. Resting heart rate and exacerbations in COPD patients. European Respiratory Journal. 2016. [2020-07-23]. .
    1. Han MK, McLaughlin VV, Criner GJ, Martinez FJ. Pulmonary diseases and the heart. Circulation. 2007 Dec 18;116(25):2992–3005. doi: 10.1161/CIRCULATIONAHA.106.685206.116/25/2992
    1. Yu C, Wong RS, Wu EB, Kong S, Wong J, Yip GW, Soo YOY, Chiu MLS, Chan Y, Hui D, Lee N, Wu A, Leung C, Sung JJ. Cardiovascular complications of severe acute respiratory syndrome. Postgrad Med J. 2006 Mar;82(964):140–4. doi: 10.1136/pgmj.2005.037515. 82/964/140
    1. Chatterjee S, Rahman M, Nemati E, Nathan V, Vatanparvar K, Kuang J. mLung++: automated characterization of abnormal lung sounds in pulmonary patients using multimodal mobile sensors. Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers; UbiComp/ISWC '19 Adjunct; September 9-13, 2019; London, United Kingdom. 2019. pp. 474–481.
    1. Wang X, Huang R, Mao S. SonarBeat: Sonar Phase for Breathing Beat Monitoring with Smartphones. 26th International Conference on Computer Communication and Networks (ICCCN); July 31-August 3, 2017; Vancouver, BC, Canada. 2017. pp. 1–8.
    1. Jones SR, Carley S, Harrison M. An introduction to power and sample size estimation. Emerg Med J. 2003 Oct;20(5):453–8. doi: 10.1136/emj.20.5.453.
    1. Activity Tracking Feature Explained. Garmin. [2020-11-24]. .
    1. What is Advanced Sleep Monitoring in Garmin Connect? Garmin. [2020-11-24]. .
    1. Fatigue Severity Scale. Shirley Ryan AbilityLab. [2020-11-24]. .
    1. Approach S62 - Body Battery. Garmin. [2020-11-24]. .
    1. An Alternative Reference Index to Monitor Fatigue | Heart Rate Variability (HRV) Garmin. [2020-09-15].
    1. Activity Tracking and Fitness Metric Accuracy. Garmin. [2020-11-24].
    1. What is Heart-Rate Variability (HRV)? Garmin. [2020-11-24]. .
    1. What Is the Respiration Rate Feature on My Garmin Device? Garmin. [2020-11-24]. .
    1. Top FAQs for the Pulse Ox Feature on Garmin Watches. Garmin. [2020-11-24]. .
    1. Klok F, Boon GA, Barco S, Endres M, Geelhoed JJ, Knauss S, Rezek SA, Spruit MA, Vehreschild J, Siegerink B. The Post-COVID-19 Functional Status scale: a tool to measure functional status over time after COVID-19. Eur Respir J. 2020 Jul;56(1):a. doi: 10.1183/13993003.01494-2020. 13993003.01494-2020
    1. Coronavirus. World Health Organization. [2020-11-24]. .
    1. Jones PW, Harding G, Berry P, Wiklund I, Chen W, Kline Leidy N. Development and first validation of the COPD Assessment Test. Eur Respir J. 2009 Oct;34(3):648–54. doi: 10.1183/09031936.00102509. 34/3/648
    1. Jones P, Harding G, Wiklund I, Berry P, Leidy N. Improving the process and outcome of care in COPD: development of a standardised assessment tool. Prim Care Respir J. 2009 Oct;18(3):208–15. doi: 10.4104/pcrj.2009.00053. doi: 10.4104/pcrj.2009.00053.pcrj-2009-03-0028
    1. Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006 May 22;166(10):1092–7. doi: 10.1001/archinte.166.10.1092.166/10/1092
    1. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Oct;16(9):606–13. doi: 10.1046/j.1525-1497.2001.016009606.x. jgi01114
    1. Bartfield JM, Ushkow BS, Rosen JM, Dylong K. Single Breath Counting in the Assessment of Pulmonary Function. Annals of Emergency Medicine. 1994 Aug;24(2):256–259. doi: 10.1016/s0196-0644(94)70138-5.S0196064494001496
    1. Dejonckere PH, Bradley P, Clemente P, Cornut G, Crevier-Buchman L, Friedrich G, Van De Heyning P, Remacle M, Woisard V, Committee on Phoniatrics of the European Laryngological Society (ELS) A basic protocol for functional assessment of voice pathology, especially for investigating the efficacy of (phonosurgical) treatments and evaluating new assessment techniques. Guideline elaborated by the Committee on Phoniatrics of the European Laryngological Society (ELS) Eur Arch Otorhinolaryngol. 2001 Mar;258(2):77–82. doi: 10.1007/s004050000299.
    1. Scholkmann F, Wolf U. The Pulse-Respiration Quotient: A Powerful but Untapped Parameter for Modern Studies About Human Physiology and Pathophysiology. Front Physiol. 2019;10:371. doi: 10.3389/fphys.2019.00371. doi: 10.3389/fphys.2019.00371.
    1. Fighting pulmonary fibrosis and infection. Breathing Matters. [2021-05-24].
    1. Synapse. [2021-05-24].
    1. Precision Health Informatics Data Lab. [2021-05-24].

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