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Background Forty distinct primary sclerosing cholangitis (PSC) genomic loci have been identified through multiancestry meta-analyses. The polygenic risk score (PRS) could serve as a promising tool to discover unique disease behaviour, like PSC, underlying inflammatory bowel disease (IBD). Aim To test whether PRS indicates PSC risk in patients with IBD. Materials and methods Mayo Clinic and Washington University at St Louis IBD cohorts were used to test our hypothesis. PRS was modelled through the published PSC loci and weighted with their corresponding effect size. Logistic regression was applied to predict the PSC risk. Results In total, 63 (5.6%) among 1130 patients with IBD of European ancestry had PSC. Among 381 ulcerative colitis (UC), 12% had PSC; in contrast to 1.4% in 761 Crohn disease (CD). Compared with IBD alone, IBD-PSC had significantly higher PRS (PSC risk: 3.0% at the lowest PRS quartile vs 7.2% at the highest PRS quartile, Ptrend =.03). In IBD subphenotypes subgroup analysis, multivariate analysis shows that UC-PSC is associated with more extensive UC disease (OR, 5.60; p=0.002) and younger age at diagnosis (p=0.02). In CD, multivariate analysis suggests that CD-PSC is associated with colorectal cancer (OR, 50; p=0.005). Conclusions We found evidence that patients with IBD with PSC presented with a clinical course difference from that of patients with IBD alone. PRS can influence PSC risk in patients with IBD. Once validated in an independent cohort, this may help identify patients with the highest likelihood of developing PSC.

INTRODUCTION: Patients with ulcerative colitis (UC) who are likely to have primary sclerosing cholangitis (PSC) should be identified because PSC can influence UC clinical behavior and outcomes.The aim of this study was to establish a model incorporating clinical and genetic risk predictors that identifies patients with UC at risk of developing PSC. METHODS: We conducted a retrospective case-control study. Inflammatory bowel disease cohorts from multiple institutions were used as discovery and replicate datasets. Quality control criteria, including minor allele frequency, call rates, Hardy-Weinberg equilibrium, cryptic relatedness, and population stratification (through principal components), were used. Discriminative accuracy was evaluated with area under the receiver operating characteristic curve. RESULTS: Fifty-seven of 581 patients (9.8%) with UC had PSC. Multivariate analysis showed that patients with UC-PSC had more extensive disease (odds ratio [OR], 5.42; P = 1.57E-04), younger diagnosis age (younger than 20 years; OR, 2.22; P = 0.02), and less smoking (OR, 0.42; P = 0.02) than those with UC. After linkage disequilibrium pruning and multivariate analyses, 3 SNPs (rs3131621 at 6p21.33; rs9275596 and rs11244 at 6p21.32) at the HLA region were found associated with a 2- to 3-fold increased risk of PSC. Our model demonstrated good discriminatory power (area under the receiver operating characteristic curve, 88%). DISCUSSION: Three variants in HLA (6p21.3) region significantly distinguished patients with UC-PSC from patients with UC alone. Once further validated in an independent large cohort, our model could be used to identify patients with UC at risk of PSC, and it could also help guide disease management.

Abstract Background Carbapenemase-producing (CP) Escherichia coli (CP-Ec) are a global public health threat. We aimed to describe the clinical and molecular epidemiology and outcomes of patients from several countries with CP-Ec isolates obtained from a prospective cohort. Methods Patients with CP-Ec were enrolled from 26 hospitals in 6 countries. Clinical data were collected, and isolates underwent whole-genome sequencing. Clinical and molecular features and outcomes associated with isolates with or without metallo-β-lactamases (MBLs) were compared. The primary outcome was desirability of outcome ranking (DOOR) at 30 days after the index culture. Results Of the 114 CP-Ec isolates in Consortium on resistance against carbapenems in Klebsiella and other Enterobacterales-2 (CRACKLE-2), 49 harbored an MBL, most commonly blaNDM-5 (38/49, 78%). Strong regional variations were noted with MBL-Ec predominantly found among patients in China (23/49). Clinically, MBL-Ec were more often from urine sources (49% vs 29%), less often met criteria for infection (39% vs 58%, P = .04), and had lower acuity of illness when compared with non–MBL-Ec. Among patients with infection, the probability of a better DOOR outcome for a randomly selected patient with MBL-Ec as compared with non–MBL-Ec was 62% (95% CI: 48.2–74.3%). Among infected patients, non–MBL-Ec had increased 30-day (26% vs 0%; P = .02) and 90-day (39% vs 0%; P = .001) mortality compared with MBL-Ec. Conclusions Emergence of CP-Ec was observed with important geographic variations. Bacterial characteristics, clinical presentations, and outcomes differed between MBL-Ec and non–MBL-Ec. Mortality was higher among non-MBL isolates, which were more frequently isolated from blood, but these findings may be confounded by regional variations.

Objectives: Deaths from an unknown cause are difficult to adjudicate and oncologic studies of comparative effectiveness often demonstrate inconsistencies in incorporating these deaths and competing events (eg, heart disease and stroke) in their analyses. In this study, we identify cancer patients most at risk for death of an unknown cause. Methods: This retrospective, population-based study used cancer registry data from the Surveillance, Epidemiology, and End Results database (1992-2015). The absolute rate of unknown causes of death (COD) cases stratified by sex, marital status, race, treatment, and cancer site were calculated and a multivariable logistic regression model was applied to obtain adjusted odds ratios with 95% CIs. Results: Out of 7,154,779 cancer patients across 22 cancer subtypes extracted from Surveillance, Epidemiology, and End Results, 3,448,927 died during follow-up and 276,068 (7.4%) of these deaths were from unknown causes. Patients with an unknown COD had a shorter mean survival time compared with patients with known COD (36.3 vs 65.7 mo, P < 0.001). The contribution of unknown COD to total mortality was highest in patients with more indolent cancers (eg, prostate [12.7%], thyroid [12.3%], breast [10.7%]) and longer follow-up (eg, >5 to 10 y). One, 3, and 5-year cancer-specific survival (CSS) calculations including unknown COD were significantly decreased compared with CSS estimates excluding cancer patients with unknown COD. Conclusion: Of the patients, 7.4% died of unknown causes during follow-up and the proportion of death was higher with longer follow-up and among more indolent cancers. The attribution of high percentages of unknown COD to cancer or non-cancer causes could impact population-based cancer registry studies or clinical trial outcomes with respect to measures involving CSS and mortality.

Abstract Acute pancreatitis (AP) is a disease characterized by an acute inflammatory phase followed by a convalescent phase. Diabetes mellitus (DM) was historically felt to be a transient phenomenon related to acute inflammation; however, it is increasingly recognized as an important late and chronic complication. There are several challenges that have prevented precisely determining the incidence rate of DM after AP and understanding the underlying mechanisms. The DREAM (Diabetes RElated to Acute Pancreatitis and its Mechanisms) Study is a prospective cohort study designed to address these and other knowledge gaps to provide the evidence needed to screen for, prevent, and treat DM after AP. In the following article, we summarize literature regarding the epidemiology of DM after AP and provide the rationale and an overview of the DREAM study.

Abstract Purpose: The use of postoperative prophylactic antibiotics in pediatric upper urinary tract reconstruction remains controversial. In this study, we elected to examine if low dose antibiotics (Abx) post pediatric dismember pyeloplasty reduce the incidence of urinary tract infections (UTIs) in our institution. As a secondary outcome, in patients who present with post op febrile UTIs, additional analysis was performed to better quantify which patient population benefits the most from low dose Abx. Methods: Institutional review board approval (IRB) was obtained. A retrospective study was performed in patients who underwent dismember pyeloplasty (2011-2017) at our institution. Patients with prior history of urologic interventions or other abnormalities of the genitourinary tract were excluded. Demographics (age, gender, ethnicity, insurance status), prior history of culture proven UTIs, surgical details (administration of perioperative antibiotics), and postoperative outcomes, including any readmission 30 days post repair, any urine samples, and culture results were collected. Results: 209 patients (149 boys, 60 girls) met our inclusion criteria. The average age was 6 years (range: 2 months-18 years). 160 patients (77%) underwent robotic-assisted pyeloplasty. Thirty-one patients underwent open repair (15%). 176 (84%) had an indwelling ureteral stent. Eleven patients (5%) had a culture-proven febrile UTI within 30-days postoperatively. No significant differences were seen in postoperative complications or incidence of UTIs when comparing surgical approaches, ureteral stent, or the use of prophylactic post-operative Abx. Secondary review of patients with post-operative febrile UTIs noted younger age (2.8 v. 6.2 years, p = 0.02) and positive intraoperative urine culture (p = 0.01) as significant risk factors. Conclusion: The incidence of postoperative UTIs in our cohort is relatively low. There is a higher incidence of febrile UTIs in patients less than 3 years old and those with positive intraoperative urine culture. The use of prophylactic Abx in patients post dismember pyeloplasty did not appear to affect the incidence of febrile culture proven UTIs, however, might be important in younger patients pre-potty training.

In 1995, a committee of the International Headache Society developed and published the first edition of the Guidelines for Controlled Trials of Drugs in Cluster Headache. These have not been revised. With the emergence of new medications, neuromodulation devices and trial designs, an updated version of the International Headache Society Guidelines for Controlled Clinical Trials in Cluster Headache is warranted. Given the scarcity of evidence-based data for cluster headache therapies, the update is largely consensus-based, but takes into account lessons learned from recent trials and demands by patients. It is intended to apply to both drug and neuromodulation treatments, with specific proposals for the latter when needed. The primary objective is to propose a template for designing high quality, state-of-the-art, controlled clinical trials of acute and preventive treatments in episodic and chronic cluster headache. The recommendations should not be regarded as dogma and alternative solutions to particular methodological problems should be explored in the future and scientifically validated.

Heart disease has a higher fatality rate than any other disease. Increased Atrial fat on the left atrium has been discovered to cause Atrial Fibrillation (AF) in most patients. AF can put one’s life at risk and eventually lead to death. AF might worsen over time; therefore, it is crucial to have an early diagnosis and treatment. To evaluate the left atrium fat tissue pattern using Radon descriptor-based machine learning. This study developed a bridge between the Radon transform framework and machine learning to distinguish two distinct patterns. Motivated by a Radon descriptor-based machine learning approach, the patches of eight patients from CT images of the heart were used and categorized into “epicardial fat tissue” and “nonfat tissue” groups. The 10 feature vectors are extracted from each big patch using Radon descriptors and then fed into a traditional machine learning model. The results show that the proposed methodology discriminates between fat tissues and nonfat tissues clearly. KNN has shown the best performance with 96.77% specificity, 98.28% sensitivity, and 97.50% accuracy. To our knowledge, this study is the first attempt to provide a Radon transform-based machine learning method to distinguish between fat tissue and nonfat tissue on the left atrium. Our proposed research method could be potentially used in advanced interventions.