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

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

Based on data from patients with BAD, irritable bowel syndrome with diarrhea (IBS-D), and healthy control subjects, we assessed correlations among stool and serum measurements. Machine learning models (based on data from 30 patients with BAD, 8 patients with IBS-D, and 26 healthy control subjects) were trained on 25 bootstrapped random samples, the superior model was identified, and optimal cutoffs of biological measurements to diagnose BAD were summarized.

There were correlations between serum C4 and %PBA (R = 0.284, P < .001), and between %PBA and TBAc (R = 0.49, P < .001). Using a %PBA of 1.05% (25th percentile in BAD), the %PBA distinguished BAD from IBS-D (odds ratio, 3.06; 95% confidence interval, 1.35-7.46; P = .01). The multivariate logistic regression model had superior balance of variance and bias. Optimal cutoffs for predicting BAD using logistic regression were 4.5% PBA (P = .023) and 1.88 μmol/g TBAc (P = .016). Serum C4 >24 ng/mL and PBA >4.6% individually had 57% and 75.8% positive predictive value, respectively, but together had a 90.1% positive predictive value. Stool consistency was less informative.

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