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Resting anal pressure, not outlet obstruction or transit, predicts healthcare utilization in chronic constipation: a
K Staller1, K Barshop2, B Kuo1
1Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Background:
Chronic constipation is common and exerts a considerable burden on health-related quality of life and healthcare resource utilization. Anorectal manometry (ARM) and colonic transit testing have allowed classification of subtypes of constipation, raising promise of targeted treatments. There has been limited study of the correlation between physiological parameters and healthcare utilization.
Methods:
All patients undergoing ARM and colonic transit testing for chronic constipation at two tertiary care centers from 2000 to 2014 were included in this retrospective study. Our primary outcomes included number of constipation-related and gastroenterology visits per year. Multivariate linear regression adjusting for confounders defined independent effect of measures of colonic and anorectal function on healthcare utilization.
Key Results:
Our study included 612 patients with chronic constipation. More than 50% (n = 333) of patients had outlet obstruction by means of balloon expulsion testing and 43.5% (n = 266) had slow colonic transit. On unadjusted analysis, outlet obstruction (1.98 vs 1.68), slow transit (2.40 vs 2.07) and high resting anal pressure (2.16 vs 1.76) were all associated with greater constipation-related visits/year compared to patients without each of those parameters (p < 0.05 for all). Outlet obstruction and high resting anal pressure were also associated with greater number of gastroenterology visits/year. After multivariate adjustment, high resting anal pressure was the only independent predictor of increased constipation-related visits/year (p = 0.02) and gastroenterology visits/year (p = 0.04).
Conclusions & Inferences:
Among patients with chronic constipation, high resting anal pressure, rather than outlet obstruction or slow transit, predicts healthcare resource utilization.
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