Background and study aims The Bethesda ERCP Skill Assessment Tool (BESAT) is a video-based assessment tool of technical endoscopic retrograde cholangiopancreatography (ERCP) skill with previously established validity evidence. We aimed to assess the discriminative validity of the BESAT in differentiating ERCP skill levels. Methods Twelve experienced ERCP practitioners from tertiary academic centers were asked to blindly rate 43 ERCP videos using the BESAT. ERCP videos consisted of native biliary cannulation and sphincterotomy and were recorded from 10 unique endoscopists of various ERCP experience (from advanced endoscopy fellow to > 10 years of ERCP experience). Inter-rater reliability, discriminative validity, and internal structure validity were subsequently assessed. Results The BESAT was found to reliably differentiate between endoscopists of varying levels of ERCP experience with experienced ERCPists scoring higher than novice ERCPists in 11 of 13 (85%) instrument items. Inter-rater reliability for BESAT items ranged from good to excellent (intraclass correlation range: 0.86 to 0.93). Internal structure validity was assessed with item-total correlations ranging from 0.53 to 0.83. Conclusions Study findings demonstrate that the BESAT, a video-based ERCP skill assessment tool, has high inter-rater reliability and has discriminative validity in differentiating novice from expert ERCP skill. Further investigations are needed to determine the role of video-based assessment in improving trainee learning curves and patient outcomes.

Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling. We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions. Voxel values within MRF-derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor-reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images. MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities.

Cardiomyopathy in chronic kidney disease (CKD) is a complex condition with multiple triggers and poor prognosis. This review provides an overview of recent advances in CKD-associated cardiomyopathy, with a focus on pathophysiology, newly discovered biomarkers and potential therapeutic targets. CKD is associated with a specific pattern of myocardial hypertrophy and fibrosis, resulting in diastolic and systolic dysfunction, and often triggered by nonatherosclerotic processes. Novel biomarkers, including amino-terminal type III procollagen peptide (PIIINP), carboxy-terminal type I procollagen peptide (PICP), FGF23, marinobufagenin, and several miRNAs, show promise for early detection and risk stratification. Treatment options for CKD-associated cardiomyopathy are limited. Sodium glucose cotransporter-2 inhibitors have been shown to reduce left ventricle hypertrophy and improve ejection fraction in individuals with diabetes and mild CKD, and are currently under investigation for more advanced stages of CKD. In hemodialysis patients calcimimetic etelcalcetide resulted in a significant reduction in left ventricular mass. CKD-associated cardiomyopathy is a common and severe complication in CKD. The identification of novel biomarkers may lead to future therapeutic targets. Randomized clinical trials in individuals with more advanced CKD would be well posed to expand treatment options for this debilitating condition.

Abstract Ambulatory impairment in Parkinson’s disease (PD) is common and complex, and poorly understood from the perspectives of those with PD. Gaining insights to the anticipated perceived trajectories and their drivers, will further facilitate patient-centered care. Latent class growth analysis, a person-centered mixture modelling approach, was applied to 16,863 people with PD stratified by early (N = 8612; <3 years), mid (N = 6181; 3–10 years) and later (N = 2070; >10 years) disease to discern clusters with similar longitudinal patterns of self-reported walking difficulty, measured by EuroQoL 5D-5L that is validated for use in PD. There were four clusters in early and mid-disease strata, with a fifth identified in later disease. Trajectories ranged from none to moderate mobility problems, with small clusters with severe problems. The percentage of subjects with moderate (early = 17.5%, mid = 26.4%, later = 32.5%) and severe (early = 3.8%, mid = 7.4%, later = 15.4%) mobility problems at baseline increased across disease duration groups. The trajectories tended to be stable with variability in moderate and severe groups. Across strata, clusters with moderate to severe problems were associated with more severe impairment, depression, anxiety, arthritis, higher BMI, lower income, and lower education, but no consistent race or gender differences. The findings reveal distinct longitudinal ambulatory patterns in PD based on a person-centered approach.

We investigated the impact of the COVID-19 pandemic on cancer detection, using data from the Surveillance, Epidemiology, and End Results Program, which recently released data through the first year of the pandemic (2020). Across all cancer sites, cancer incidence fell by 8.7percent. The most common cancers that experienced the largest disruptions were lung and bronchus, melanoma of the skin, and thyroid cancer.

Our objective was to evaluate if botox alters the urinary microbiome of patients with overactive bladder and whether this alteration is predictive of treatment response. This multicenter prospective cohort study included 18-89-year-old patients undergoing treatment for overactive bladder with 100 units of botox. Urine samples were collected by straight catheterization on the day of the procedure (S1) and again 4 weeks later (S2). Participants completed the Patient Global Impression of Improvement form at their second visit for dichotomization into responders and nonresponders. The microbiome was sequenced using 16s rRNA sequencing. Wilcoxon signed rank and Wilcoxon rank sum were used to compare the microbiome, whereas chi-square, Wilcoxon rank sum, and the independent t-test were utilized for clinical data. Sixty-eight participants were included in the analysis. The mean relative abundance and prevalence of Beauveria bassiana, Xerocomus chrysenteron, Crinipellis zonata, and Micrococcus luteus were all found to increase between S1 and S2 in responders; whereas in nonresponders the mean relative abundance and prevalence of Pseudomonas fragi were found to decrease. The MRA and prevalence of Weissella cibaria, Acinetobacter johnsonii, and Acinetobacter schindleri were found to be greater in responders than nonresponders at the time of S1. Significant UM differences in the S1 of patients who did (n = 5) and did not go on to develop a post-treatment UTI were noted. Longitudinal urobiome differences may exist between patients who do and do not respond to botox.