World Scientific
  • Search
  •   
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×
Our website is made possible by displaying certain online content using javascript.
In order to view the full content, please disable your ad blocker or whitelist our website www.worldscientific.com.

System Upgrade on Tue, Oct 25th, 2022 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.

MOTILITY OF THE UNPREPARED INTESTINAL TRACT IN HEALTHY HUMANS AND PATIENTS WITH SLOW TRANSIT CONSTIPATION REVEALED BY USING MICRO-ELECTRONIC CAPSULE

    https://doi.org/10.4015/S1016237221500538Cited by:1 (Source: Crossref)

    Slow transit constipation (STC) is usually accompanied by intestinal motility abnormalities. Although conventional anorectal manometry could record the pressure in the colon, most patients need preparation of intestinal tract. The intervention of catheter for monitoring the intestinal pressure also affects the clinical measurement. The pressure data collected by the conventional anorectal manometry cannot fully characterize the dynamic characteristics of the intestine. Thus, we aimed to obtain colonic pressure data under normal physiological conditions. Utilizing these data, we analyze the difference of colonic motility parameters between healthy control and patients with STC. A micro-electronic capsule made by ourselves was used to gather the subjects’ intestinal pressure in their daily life. Several intestinal motility parameters were calculated from the pressure profile. The average energy of colonic pressure data in the STC group is higher than the healthy control group (HC: 259.95 vs. STC: 821.28). But the STC group has a lower average complexity of colonic motility (HC: 0.80 vs. STC: 0.64). About 81.25% of the colonic data from patients with STC could be identified by using slow transit constipation (SVM) classifier. Compared with health control, most colonic parameters of patients with STC are higher under the normal physiological conditions, but the complexity of colonic motility is lower in the STC group. The correct rate of colonic pressure recognition in the STC group is more than 80% by using SVM classifier.

    References

    • 1. Zhao YF, Ma XQ, Wang R, Yan XY, Li ZS, Zou DW, He J , Epidemiology of functional constipation and comparison with constipation-predominant irritable bowel syndrome: The Systematic Investigation of Gastrointestinal Diseases in China (SILC), Aliment Pharmacol Ther 34 :1020, 2011. Crossref, ISIGoogle Scholar
    • 2. Peppas G, Alexiou VG, Mourtzoukou E, Falagas ME , Epidemiology of constipation in Europe and Oceania: A systematic review, BMC Gastroenterol 8 :1–7, 2008. Crossref, ISIGoogle Scholar
    • 3. Stewart WF, Liberman JN, Sandler RS, Woods MS, Stemhagen A, Chee E, Lipton RB, Farup CE , Epidemiology of constipation (EPOC) study in the United States: Relation of clinical subtypes to sociodemographic features, Am J Gastroenterol 94 :3530, 1999. Crossref, ISIGoogle Scholar
    • 4. Gallagher P, O’Mahony D , Constipation in old age, Best Pract Res Clin Gastroenterol 23 :875, 2009. Crossref, ISIGoogle Scholar
    • 5. Andy UU, Vaughan CP, Burgio KL, Alli FM, Goode PS, Markland AD , Shared risk factors for constipation, fecal incontinence, and combined symptoms in older US adults, J Am Geriatr Soc 64 :e183, 2016. Crossref, ISIGoogle Scholar
    • 6. Basilisco G, Coletta M , Chronic constipation: A critical review, Dig Liver Dis 45 :886, 2013. CrossrefGoogle Scholar
    • 7. Seo M, Joo S, Jung K, Lee J, Lee H, Soh J, Yoon IJ, Koo HS, Seo SY, Kim D , A high-resolution anorectal manometry parameter based on integrated pressurized volume: A study based on 204 male patients with constipation and 26 controls, J Neurogastroenterol Motil 30 :e13376, 2018. Crossref, ISIGoogle Scholar
    • 8. Dinning P, Wiklendt L, Maslen L, Patton V, Lewis H, Arkwright J, Wattchow DA, Lubowski DZ, Costa M, Bampton PA , Colonic motor abnormalities in slow transit constipation defined by high resolution, fibre-optic manometry, Neurogastroenterol Motil 27 :379, 2015. Crossref, ISIGoogle Scholar
    • 9. Ratuapli SK, Bharucha AE, Noelting J, Harvey DM, Zinsmeister AR , Phenotypic identification and classification of functional defecatory disorders using high-resolution anorectal manometry, Gastroenterology 144 :314, 2013. Crossref, ISIGoogle Scholar
    • 10. Rao SS, Singh S , Clinical utility of colonic and anorectal manometry in chronic constipation, J Clin Nutr Gastroenterol 44 :597, 2010. Crossref, ISIGoogle Scholar
    • 11. Prichard DO, Lee T, Parthasarathy G, Fletcher JG, Zinsmeister AR, Bharucha AE , High-resolution anorectal manometry for identifying defecatory disorders and rectal structural abnormalities in women, Clin Gastroenterol Hepatol 15 :412, 2017. Crossref, ISIGoogle Scholar
    • 12. Siah KT, Wong RK, Whitehead WE , Chronic constipation and constipation-predominant IBS: Separate and distinct disorders or a spectrum of disease? Gastroenterol Hepatol 12 :171, 2016. Google Scholar
    • 13. Prior A, Maxton D, Whorwell P , Anorectal manometry in irritable bowel syndrome: Differences between diarrhoea and constipation predominant subjects, Gut 31 :458, 1990. Crossref, ISIGoogle Scholar
    • 14. Dinning P, Wiklendt L, Maslen L, Gibbins I, Patton V, Arkwright J, Lubowski DZ, O’Grady G, Bampton PA, Brookes SJ , Quantification of in vivo colonic motor patterns in healthy humans before and after a meal revealed by high-resolution fiber-optic manometry, Neurogastroenterol Motil 26 :1443, 2014. Crossref, ISIGoogle Scholar
    • 15. Grossi U, Carrington EV, Bharucha AE, Horrocks EJ, Scott SM, Knowles CH , Diagnostic accuracy study of anorectal manometry for diagnosis of dyssynergic defecation, Gut 65 :447, 2016. Crossref, ISIGoogle Scholar
    • 16. Zhao K, Yan G, Lu L, Xu F , Low-power wireless electronic capsule for long-term gastrointestinal monitoring, J Med Syst 39 :1, 2015. Crossref, ISIGoogle Scholar
    • 17. Bhate PA, Patel JA, Parikh P, Ingle MA, Phadke A, Sawant PD , Total and segmental colon transit time study in functional constipation: Comparison with healthy subjects, Gastroenterol Res 8 :157, 2015. CrossrefGoogle Scholar
    • 18. Lee YY, Askin Erdogan SY, Dewitt A, Rao SS , Anorectal manometry in defecatory disorders: A comparative analysis of high-resolution pressure topography and waveform manometry, J Neurogastroenterol Motil 24 :460, 2018. Crossref, ISIGoogle Scholar
    • 19. Xu F, Yan G, Zhao K, Lu L, Gao J, Liu G , A wireless capsule system with ASIC for monitoring the physiological signals of the human gastrointestinal tract, IEEE Trans Biomed Circuits Syst 8 :871, 2014; 8(6) :871–80. Crossref, ISIGoogle Scholar
    • 20. Zhao K, Yan G, Lu L, Xu F , Colonic peristalsis signal extraction and energy analysis based on wavelet analysis, 2014 7th International Conference on Biomedical Engineering and Informatics, Dalian, China, pp. 740–744, 2014. CrossrefGoogle Scholar
    • 21. Zhang C, Wang H, Fu R , Automated detection of driver fatigue based on entropy and complexity measures, IEEE Transactions on Intelligent Transportation Systems 15 :168, 2013. Crossref, ISIGoogle Scholar
    • 22. Abásolo D, Hornero R, Gómez C, García M, López M , Analysis of EEG background activity in Alzheimer’s disease patients with Lempel-Ziv complexity and central tendency measure, Med. Eng. Phys. 28 :315, 2006. Crossref, ISIGoogle Scholar
    • 23. Naseer N, Noori FM, Qureshi NK, Hong Keum-Shik , Determining Optimal Feature-Combination for LDA Classification of Functional Near-Infrared Spectroscopy Signals in Brain-Computer Interface Application, Frontiers in Human Neuroscience 10 :315, 2016. Crossref, ISIGoogle Scholar
    • 24. Soltani M, Omid M , Detection of poultry egg freshness by dielectric spectroscopy and machine learning techniques, LWT-Food Science and Technology 62 :1034, 2015. Crossref, ISIGoogle Scholar
    • 25. Monika S, Matjaž G, Ana M , Non-invasive blood pressure estimation from ECG using machine learning techniques, Sensors 18 :1160, 2018. Crossref, ISIGoogle Scholar
    • 26. Tran K, Brun R, Kuo B , Evaluation of regional and whole gut motility using the wireless motility capsule: Relevance in clinical practice, Therapeutic Advances in Gastroenterology 5 :249, 2012. Crossref, ISIGoogle Scholar
    Remember to check out the Most Cited Articles!

    Notable Biomedical Titles
    Authors from Harvard, Rutgers University, University College London and more!