Matthias Christian Reichert

Background: Elevated levels of the C-3 epimer (3-epi-25(OH)D) of 25-hydroxyvitamin D (25(OH)D) have been identified in premature infants as compared to most adults, and an immature liver has been suggested as a possible cause. We hypothesised that patients with cirrhosis might present with elevated C-3 epimerisation due to impaired liver function. The aim was to assess whether 3-epi-25(OH)D levels differ in patients with chronic liver disease with cirrhosis vs. those without cirrhosis. Methods: A total of 309 patients were included (254 patients with cirrhosis vs. 55 without cirrhosis). Serum 25(OH)D and 3-epi-25(OH)D levels were determined using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Results: Patients with cirrhosis had significantly higher median relative 3-epi-25(OH)D concentrations, as compared to patients without cirrhosis (7.4% (5.5–10.4) vs. 4.8% (2.4–5.7), respectively; p < 0.001). They also had similar absolute 3-epi-25(OH)D levels (despite having lower 25(OH)D serum concentrations) than patients without cirrhosis. A progressive increase in relative 3-epi-25(OH)D levels was observed with more advanced cirrhosis (p < 0.001). An analysis of the ROC area under the curve determined 6% as the optimal cut-off for relative 3-epi-25(OH)D. All patients with Child–Pugh stage C and 88.6% with stage B were above the 6% cut-off and had significantly higher absolute serum 3-epi-25(OH)D concentrations (0.9 ng/mL vs. 0.6 ng/mL; p < 0.05) and lower serum 25(OH)D levels (9.3 vs. 14.1 ng/mL; p < 0.001) than patients <6% cut-off. Conclusions: These results reflect the marked increases in relative 3-epi-25(OH)D levels that occur with cirrhosis. The specific hepatic metabolic alterations still need to be unravelled, including whether cirrhosis might lead to reduced epimer clearance.

Background/Aims: Patients with diverticular disease (DD) frequently have abnormal bowel movements. However, it is unknown whether the entity of these alterations is associated with the severity of DD. We aimed to assess bowel habits and their relationship with the severity of DD according to Diverticular Inflammation and Complication Assessment (DICA) classification, Combined Overview on Diverticular Assessment (CODA) score, and fecal calprotectin (FC). Methods: An international, multicenter, prospective cohort study was conducted in 43 centers. A 10-point visual analog scale (VAS) was used to assess the severity of constipation and diarrhea. The association of constipation and diarrhea with DICA classification, CODA score, and basal FC was tested using non-parametric tests. Survival methods for censored observations were applied to test the association of constipation and diarrhea with the incidence of acute diverticulitis over a 3-year follow-up. Results: Of 871 patients with DD were included in the study. Of these, 208 (23.9%) and 199 (22.9%) reported a VAS score for constipation and diarrhea at least 3 at baseline, respectively. Higher constipation and diarrhea scores were associated with increasing DICA classification, CODA score and basal FC (P< 0.001). Constipation and diarrhea scores were independently associated with an increased hazard of developing acute diverticulitis (hazard ratio [HR]constipation = 1.15 per 1-VAS point increase, 95% confidence interval [CI], 1.04–1.27; P=0.004; and HRdiarrhea =1.14; 95% CI, 1.03–1.26; P=0.014, respectively). Conclusions: In newly diagnosed patients with DD, higher endoscopic and combined scores of DD severity were associated with higher scores of constipation and diarrhea at baseline. Both constipation and diarrhea were independent prognostic factors of acute diverticulitis.

Background and AimsThe Diverticular Inflammation and Complication Assessment (DICA) classification and the Combined Overview on Diverticular Assessment (CODA) were found to be effective in predicting the outcomes of Diverticular Disease (DD). We ascertain whether fecal calprotectin (FC) can further aid in improving risk stratification. MethodsA three-year international, multicentre, prospective cohort study was conducted involving 43 Gastroenterology and Endoscopy centres. Survival methods for censored observations were used to estimate the risk of acute diverticulitis (AD) in newly diagnosed DD patients according to basal FC, DICA, and CODA. The net benefit of management strategies based on DICA, CODA and FC in addition to CODA was assessed with decision curve analysis, which incorporates the harms and benefits of using a prognostic model for clinical decisions. ResultsAt the first diagnosis of diverticulosis/DD, 871 participants underwent FC measurement. FC was associated with the risk of AD at 3 years (HR per each base 10 logarithm increase: 3.29; 95% confidence interval, 2.13-5.10) and showed moderate discrimination (c-statistic: 0.685; 0.614-0.756). DICA and CODA were more accurate predictors of AD than FC. However, FC showed high discrimination capacity to predict AD at 3 months, which was not maintained at longer follow-up times. The decision curve analysis comparing the combination of FC and CODA with CODA alone did not clearly indicate a larger net benefit of one strategy over the other. ConclusionsFC measurement could be used as a complementary tool to assess the immediate risk of AD. In all other cases, treatment strategies based on the CODA score alone should be recommended.

Background __and objective_: The Diverticular Inflammation and Complication Assessment (DICA) classification and the Combined Overview on Diverticular Assessment (CODA) score are valuable prognostic tools for diverticulitis, providing new risk stratification tools useful for everyday clinical...

Background: Whereas Artificial Intelligence (AI) based tools have recently been introduced in the field of gastroenterology, application in inflammatory bowel disease (IBD) is in its infancies. We established AI‐based algorithms to distinguish IBD from infectious and ischemic colitis using endoscopic images and clinical data.Methods: First, we trained and tested a Convolutional Neural Network (CNN) using 1796 real‐world images from 494 patients, presenting with three diseases (IBD [n = 212], ischemic colitis [n = 157], and infectious colitis [n = 125]). Moreover, we evaluated a Gradient Boosted Decision Trees (GBDT) algorithm using five clinical parameters as well as a hybrid approach (CNN + GBDT). Patients and images were randomly split into two completely independent datasets. The proposed approaches were benchmarked against each other and three expert endoscopists on the test set.Results: For the image‐based CNN, the GBDT algorithm and the hybrid approach global accuracies were .709, .792, and .766, respectively. Positive predictive values were .602, .702, and .657. Global areas under the receiver operating characteristics (ROC) and precision recall (PR) curves were .727/.585, .888/.823, and .838/.733, respectively. Global accuracy did not differ between CNN and endoscopists (.721), but the clinical parameter‐based GBDT algorithm outperformed CNN and expert image classification.Conclusions: Decision support systems exclusively based on endoscopic image analysis for the differential diagnosis of colitis, representing a complex clinical challenge, seem not yet to be ready for primetime and more diverse image datasets may be necessary to improve performance in future development. The clinical value of the proposed clinical parameters algorithm should be evaluated in prospective cohorts.

High-quality DNA extraction is a crucial step in metagenomic studies. Bias by different isolation kits impairs the comparison across datasets. A trending topic is, however, the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases. We thus collected bile, stool, saliva, plaque, sputum, and conjunctival swab samples and performed DNA extraction with three commercial kits. For each combination of the specimen type and DNA extraction kit, 20-gigabase (Gb) metagenomic data were generated using short-read sequencing. While profiles of the specimen types showed close proximity to each other, we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits. No kit outperformed all selected kits on every specimen. We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit. Depending on the specimen, our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution, but DNA-based identification is superior to identification by mass spectrometry. Finally, long-read nanopore sequencing confirmed the results (correlation coefficient > 0.98). Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients.