Skip to main content
SpringerLink
Log in

Disease Activity Patterns Recorded Using a Mobile Monitoring System Are Associated with Clinical Outcomes of Patients with Crohn’s Disease

  • Original Article
  • Published:
Digestive Diseases and Sciences Aims and scope Submit manuscript

Abstract

Background

Usefulness of a mobile monitoring system for Crohn’s disease (CD) has not been evaluated. We aimed to determine whether disease activity patterns depicted using a web-based symptom diary for CD could indicate disease clinical outcomes.

Methods

Patients with CD from tertiary hospitals were prospectively invited to record their symptoms using a smartphone at least once a week. Disease activity patterns for at least 2 months were statistically classified into good and poor groups based on two factors in two consecutive time frames; the degree of score variation (maximum–minimum) in each frame and the trend (upward, stationary, or downward) of patterns indicated by the difference in the mean activity scores between two time frames.

Results

Overall, 220 (82.7%) and 46 (17.3%) patients were included in good and poor groups, respectively. Poor group was significantly more associated with disease-related hospitalization (p = 0.004), unscheduled hospital visits (p = 0.005), and bowel surgery (p < 0.001) during the follow-up period than good group. In the multivariate analysis, poor patterns [odds ratio (OR) 2.62, p = 0.006], stricturing (OR 4.19, p < 0.001) or penetrating behavior (OR 2.27, p = 0.012), and young age at diagnosis (OR 1.06, p = 0.019) were independently associated with disease-related hospitalization. Poor patterns (OR 4.06, p = 0.006) and an ileal location (OR 5.79, p = 0.032) remained independent risk factors for unscheduled visits. Poor patterns (OR 15.2, p < 0.001) and stricturing behavior (OR 9.77, p = 0.004) were independent risk factors for bowel surgery.

Conclusion

The disease activity patterns depicted using a web-based symptom diary were useful indicators of poor clinical outcomes in patients with CD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Veloso FT, Ferreira JT, Barros L, Almeida S. Clinical outcome of Crohn’s disease: analysis according to the vienna classification and clinical activity. Inflamm Bowel Dis. 2001;7:306–313.

    Article  PubMed  CAS  Google Scholar 

  2. Thia KT, Sandborn WJ, Harmsen WS, Zinsmeister AR, Loftus EV Jr. Risk factors associated with progression to intestinal complications of Crohn’s disease in a population-based cohort. Gastroenterology. 2010;139:1147–1155.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Sandborn WJ, Feagan BG, Hanauer SB, et al. A review of activity indices and efficacy endpoints for clinical trials of medical therapy in adults with Crohn’s disease. Gastroenterology. 2002;122:512–530.

    Article  PubMed  Google Scholar 

  4. Harvey RF, Bradshaw JM. A simple index of Crohn’s-disease activity. Lancet. 1980;1:514.

    Article  PubMed  CAS  Google Scholar 

  5. Pariente B, Cosnes J, Danese S, et al. Development of the Crohn’s disease digestive damage score, the Lemann score. Inflamm Bowel Dis. 2011;17:1415–1422.

    Article  PubMed  Google Scholar 

  6. Maiolo C, Mohamed EI, Fiorani CM, De Lorenzo A. Home telemonitoring for patients with severe respiratory illness: the Italian experience. J Telemed Telecare. 2003;9:67–71.

    Article  PubMed  Google Scholar 

  7. Gomez EJ, Hernando ME, Garcia A, et al. Telemedicine as a tool for intensive management of diabetes: the DIABTel experience. Comput Methods Progr Biomed. 2002;69:163–177.

    Article  CAS  Google Scholar 

  8. Evangelista LS, Stromberg A, Westlake C, Ter-Galstanyan A, Anderson N, Dracup K. Developing a Web-based education and counseling program for heart failure patients. Prog Cardiovasc Nurs. 2006;21:196–201.

    Article  PubMed  Google Scholar 

  9. Ajay VS, Jindal D, Roy A, et al. Development of a smartphone-enabled hypertension and diabetes mellitus management package to facilitate evidence-based care delivery in primary healthcare facilities in India: The mPower Heart Project. J Am Heart Assoc. 2016;5:e004343.

    Article  PubMed  PubMed Central  Google Scholar 

  10. McConnell MV, Shcherbina A, Pavlovic A, et al. Feasibility of obtaining measures of lifestyle from a smartphone app: the MyHeart counts cardiovascular health study. JAMA Cardiol. 2017;2:67–76.

    Article  PubMed  Google Scholar 

  11. Chan NY, Choy CC. Screening for atrial fibrillation in 13 122 Hong Kong citizens with smartphone electrocardiogram. Heart. 2017;103:24–31.

    Article  PubMed  Google Scholar 

  12. Capecci M, Pepa L, Verdini F, Ceravolo MG. A smartphone-based architecture to detect and quantify freezing of gait in Parkinson’s disease. Gait Posture. 2016;50:28–33.

    Article  PubMed  Google Scholar 

  13. Van Deen WK, van der Meulen-de Jong AE, Parekh NK, et al. Development and validation of an inflammatory bowel diseases monitoring index for use with mobile health technologies. Clin Gastroenterol Hepatol. 2016;14:1742–1750e7.

    Article  PubMed  Google Scholar 

  14. Kim ES, Park KS, Cho KB, et al. Development of a web-based, self-reporting symptom diary for Crohn’s disease, and its correlation with the Crohn’s disease activity index: web-based, self-reporting symptom diary for Crohn’s disease. J Crohns Colitis. 2017;11:1449–1455.

    Article  PubMed  Google Scholar 

  15. Solberg IC, Vatn MH, Hoie O, et al. Clinical course in Crohn’s disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol. 2007;5:1430–1438.

    Article  PubMed  Google Scholar 

  16. Bernstein CN, Loftus EV Jr, Ng SC, et al. Hospitalisations and surgery in Crohn’s disease. Gut. 2012;61:622–629.

    Article  PubMed  Google Scholar 

  17. Ramos-Rivers C, Regueiro M, Vargas EJ, et al. Association between telephone activity and features of patients with inflammatory bowel disease. Clin Gastroenterol Hepatol. 2014;12:986–994.

    Article  PubMed  Google Scholar 

  18. Sulz MC, Siebert U, Arvandi M, et al. Predictors for hospitalization and outpatient visits in patients with inflammatory bowel disease: results from the Swiss Inflammatory Bowel Disease Cohort Study. Eur J Gastroenterol Hepatol. 2013;25:790–797.

    Article  PubMed  CAS  Google Scholar 

  19. Romberg-Camps MJ, Dagnelie PC, Kester AD, et al. Influence of phenotype at diagnosis and of other potential prognostic factors on the course of inflammatory bowel disease. Am J Gastroenterol. 2009;104:371–383.

    Article  PubMed  CAS  Google Scholar 

  20. Moran GW, Dubeau MF, Kaplan GG, et al. Phenotypic features of Crohn’s disease associated with failure of medical treatment. Clin Gastroenterol Hepatol. 2014;12:434–442.

    Article  PubMed  CAS  Google Scholar 

  21. Beaugerie L, Seksik P, Nion-Larmurier I, Gendre JP, Cosnes J. Predictors of Crohn’s disease. Gastroenterology. 2006;130:650–656.

    Article  PubMed  Google Scholar 

  22. Lunney PC, Kariyawasam VC, Wang RR, et al. Smoking prevalence and its influence on disease course and surgery in Crohn’s disease and ulcerative colitis. Aliment Pharmacol Ther. 2015;42:61–70.

    Article  PubMed  CAS  Google Scholar 

  23. Ng WK, Wong SH, Ng SC. Changing epidemiological trends of inflammatory bowel disease in Asia. Intest Res. 2016;14:111–119.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Hwang SW, Seo H, Kim GU, et al. Underestimation of smoking rates in an East Asian population with Crohn’s disease. Gut Liver. 2017;11:73–78.

    Article  PubMed  Google Scholar 

  25. Ma J, Zhu J, Li N, et al. Severe and differential underestimation of self-reported smoking prevalence in Chinese adolescents. Int J Behav Med. 2014;21:662–666.

    Article  PubMed  Google Scholar 

  26. Williet N, Sandborn WJ, Peyrin-Biroulet L. Patient-reported outcomes as primary end points in clinical trials of inflammatory bowel disease. Clin Gastroenterol Hepatol. 2014;12:1246–1256.

    Article  PubMed  Google Scholar 

Download references

Funding

This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2015R1D1A1A02062168) and by the research promoting grant from the Keimyung University Dongsan Medical Center in 2011.

Author information

Authors and Affiliations

  1. Division of Gastroenterology, Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Korea

    Eun Soo Kim, Sung Kook Kim & Hyun Seok Lee

  2. Division of Gastroenterology and Hepatology, Department of Internal Medicine, Yeungnam University College of Medicine, 317-1 Daemyung 5 Dong, Daegu, 705-703, Korea

    Byung Ik Jang & Kyeong Ok Kim

  3. Division of Gastroenterology, Department of Internal Medicine, Catholic University of Daegu School of Medicine, Daegu, Korea

    Eun Young Kim

  4. Division of Gastroenterology, Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea

    Eun Soo Kim & Yoo Jin Lee

  5. Department of Medical Statistics, Catholic University of Daegu School of Medicine, Daegu, Korea

    Sang Gyu Kwak

Authors
  1. Eun Soo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sung Kook Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Byung Ik Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kyeong Ok Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Eun Young Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yoo Jin Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hyun Seok Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sang Gyu Kwak
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

the Crohn’s and Colitis Association in Daegu-Gyeongbuk (CCAiD)

Corresponding author

Correspondence to Byung Ik Jang.

Ethics declarations

Conflict of interest

All the authors declare that they have no conflicts of interest.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, E.S., Kim, S.K., Jang, B.I. et al. Disease Activity Patterns Recorded Using a Mobile Monitoring System Are Associated with Clinical Outcomes of Patients with Crohn’s Disease. Dig Dis Sci 63, 2220–2230 (2018). https://doi.org/10.1007/s10620-018-5110-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10620-018-5110-8

Keywords

Search

Navigation