Simplifying Diagnosis of Bile Acid Diarrhea with Clinical and Biochemical Measurements on Blood and Single Stool Sample.

Abstract

Background: Diagnosis of bile acid (BA) diarrhea (BAD) has been based on 48-hour fecal BA excretion; serum 7αC4 (C4) has been used to screen for BAD. Optimal diagnostic cut-offs for C4 and biochemical measurements in a single stool sample are unknown.

Aims: To examine the relationship between total BA concentration (TBAc) and percent primary BA (%PBA) in a single stool sample and serum C4 in patients with and without BAD; and explore performance characteristics of stool consistency and biochemical (serum C4 and single stool BA) parameters for diagnosis of BAD compared to gold standard 48-hour fecal BA.

Methods: Based on data from patients with BAD, IBS-D, and healthy controls, we assessed correlations among stool and serum measurements. Machine learning models (based on data from 30 with BAD, 8 IBS-D, and 26 healthy) were trained on 25 bootstrapped random samples, the superior model identified, and optimal cut-offs of biological measurements to diagnose BAD were summarized.

Results: There were correlations between serum C4 and %PBA (R=0.284, P<0.001), and between %PBA and TBAc (R=0.49, P<0.001). Using PBA of 1.05% (25^th percentile in BAD), the %PBA distinguished BAD from IBS-D (OR 3.06 [95% CI: 1.35-7.46], P=0.01). The multivariate logistic regression (LR) model had superior balance of variance and bias. Optimal cut-offs for predicting BAD using LR were 4.5% PBA (P=0.023) and 1.88μmol/g TBAc (P=0.016). Serum C4 >24ng/mL and PBA>4.6% individually had 57% and 75.8% PPV, respectively, but together 90.1% PPV. Stool consistency was less informative.

Conclusions: New diagnostic cut-offs based on serum C4 and single stool TBAc and % PBA provide potential alternatives for diagnosing BAD. Further validation is warranted.