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Remote sampling of biomarkers of inflammation with linked patient generated health data in patients with rheumatic and musculoskeletal diseases: an Ecological Momentary Assessment feasibility study.
Druce, Katie L; Gibson, David S; McEleney, Kevin; Yimer, Belay B; Meleck, Stephanie; James, Ben; Hellman, Bruce; Dixon, William G; McBeth, John.
Affiliation
  • Druce KL; Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK.
  • Gibson DS; Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
  • McEleney K; Northern Ireland Centre for Stratified Medicine, School of Biomedical Sciences, Biomedical Sciences Research Institute, Ulster University, Londonderry, UK.
  • Yimer BB; Northern Ireland Centre for Stratified Medicine, School of Biomedical Sciences, Biomedical Sciences Research Institute, Ulster University, Londonderry, UK.
  • Meleck S; Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK.
  • James B; Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
  • Hellman B; uMotif, London, UK.
  • Dixon WG; uMotif, London, UK.
  • McBeth J; uMotif, London, UK.
BMC Musculoskelet Disord ; 23(1): 770, 2022 Aug 13.
Article in En | MEDLINE | ID: mdl-35964066
ABSTRACT

BACKGROUND:

People with rheumatic diseases experience troublesome fluctuations in fatigue. Debated causes include pain, mood and inflammation. To determine the relationships between these potential causes, serial assessments are required but are methodologically challenging. This mobile health (mHealth) study explored the viability of using a smartphone app to collect patient-reported symptoms with contemporaneous Dried Blood Spot Sampling (DBSS) for inflammation.

METHODS:

Over 30 days, thirty-eight participants (12 RA, 13 OA, and 13 FM) used uMotif, a smartphone app, to report fatigue, pain and mood, on 5-point ordinal scales, twice daily. Daily DBSS, from which C-reactive Protein (CRP) values were extracted, were completed on days 1-7, 14 and 30. Participant engagement was determined based on frequency of data entry and ability to calculate within- and between-day symptom changes. DBSS feasibility and engagement was determined based on the proportion of samples returned and usable for extraction, and the number of days between which between-day changes in CRP which could be calculated (days 1-7).

RESULTS:

Fatigue was reported at least once on 1085/1140 days (95.2%). Approximately 65% of within- and between-day fatigue changes could be calculated. Rates were similar for pain and mood. A total of 287/342 (83.9%) DBSS, were returned, and all samples were viable for CRP extraction. Fatigue, pain and mood varied considerably, but clinically meaningful (≥ 5 mg/L) CRP changes were uncommon.

CONCLUSIONS:

Embedding DBSS in mHealth studies will enable researchers to obtain serial symptom assessments with matched biological samples. This provides exciting opportunities to address hitherto unanswerable questions, such as elucidating the mechanisms of fatigue fluctuations.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Rheumatic Diseases / Patient Generated Health Data Type of study: Diagnostic_studies / Etiology_studies Limits: Humans Language: En Journal: BMC Musculoskelet Disord Journal subject: FISIOLOGIA / ORTOPEDIA Year: 2022 Type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Rheumatic Diseases / Patient Generated Health Data Type of study: Diagnostic_studies / Etiology_studies Limits: Humans Language: En Journal: BMC Musculoskelet Disord Journal subject: FISIOLOGIA / ORTOPEDIA Year: 2022 Type: Article Affiliation country: United kingdom