eQTL in diseased colon tissue identifies novel target genes associated with IBD.

Genome-wide association studies (GWAS) have identified over 300 loci associated with the inflammatory bowel diseases (IBD), but putative causal genes for most are unknown. We conducted the largest disease-focused expression quantitative trait loci (eQTL) analysis using colon tissue from 252 IBD patients to determine genetic effects on gene expression and potential contribution to IBD. Combined with two non-IBD colon eQTL studies, we identified 194 potential target genes for 108 GWAS loci.

Long-term Outcomes Following Colectomy and Liver Transplantation for Inflammatory Bowel Disease with Primary Sclerosing Cholangitis.

Objective: To investigate the long-term outcomes of patients with combined primary sclerosing cholangitis/inflammatory bowel disease (PSC-IBD) undergoing both liver transplantation (LT) and total abdominal colectomy (TAC).

Summary Background Data: The fraction of patients with PSC-IBD that require both LT and TAC is small, thereby limiting significant conclusions regarding long-term outcomes.

Methods: Adult and pediatric patients from nine centers from the US IBD Surgery Collaborative who underwent staged LT and TAC for PSC-IBD were included.

Disparities in Outcomes following Resection of Locally Advanced Rectal Cancer.

Surgical margins following rectal cancer resection impact oncologic outcomes. We examined the relationship between margin status and race, ethnicity, region of care, and facility type. Patients undergoing resection of a stage II-III locally advanced rectal cancer (LARC) between 2004 and 2018 were identified through the National Cancer Database.

Linking gene expression to clinical outcomes in pediatric Crohn's disease using machine learning.

Pediatric Crohn's disease (CD) is characterized by a severe disease course with frequent complications. We sought to apply machine learning-based models to predict risk of developing future complications in pediatric CD using ileal and colonic gene expression. Gene expression data was generated from 101 formalin-fixed, paraffin-embedded (FFPE) ileal and colonic biopsies obtained from treatment-naïve CD patients and controls.

Factors Associated With Performing IPAA After Total Colectomy for Ulcerative Colitis.

Background: IPAA is considered the procedure of choice for restorative surgery after total colectomy for ulcerative colitis. Previous studies have examined the rate of IPAA within individual states but not at the national level in the United States.

Objective: This study aimed to assess the rate of IPAA after total colectomy for ulcerative colitis in a national population and identify factors associated with IPAA.

The value of national accreditation program for rectal cancer: A survey of accredited programs and programs seeking accreditation.

Background: Significant variation in rectal cancer care has been demonstrated in the United States. The National Accreditation Program for Rectal Cancer was established in 2017 to improve the quality of rectal cancer care through standardization and emphasis on a multidisciplinary approach. The aim of this study was to understand the perceived value and barriers to achieving the National Accreditation Program for Rectal Cancer accreditation.

Financial Relationships in General Surgery Education: Recent Trends in Industry Payments to General Surgery Residency Leadership.

Introduction: Residency programs and their directors frequently receive funding from industry payers. Both general surgery residency program directors (PDs) and assistant program directors (APDs) receive industry funding for various reasons, including educational advancement. This study investigates recent trends in industry payments to both PDs and APDs to better understand the financial relationships among leaders in residency education.

Perspectives on Referring for Rectal Cancer Surgery: a Survey Study of Gastroenterologist and General Surgeons in Iowa.

Purpose: To understand referral practices for rectal cancer surgical care and to secondarily determine differences in referral practices by two main hypothesized drivers of referral: the rurality of the community endoscopists' practice and their affiliation with a colorectal surgeon.

Methods: Community gastroenterologists and general surgeons in Iowa completed a mailed questionnaire on practice demographics, volume, and referral practices for rectal cancer patients. Rurality was operationalized with RUCA codes.

Long-term Outcomes of the Kono-S Anastomosis: A Multicenter Study.

Background: Postoperative recurrence remains a significant problem in Crohn's disease, and the mesentery is implicated in the pathophysiology. The Kono-S anastomosis was designed to exclude the mesentery from a wide anastomotic lumen, limit luminal distortion and fecal stasis, and preserve innervation and vascularization.

Objective: To review postoperative complications and long-term outcomes of the Kono-S anastomosis in a large series of consecutive unselected patients with Crohn's disease.

How to say "I don't know": development and evaluation of workshops for medical students and surgical residents on communicating uncertainty using the ADAPT framework.

Purpose: Uncertainty, or the conscious awareness of having doubts, is pervasive in medicine, from differential diagnoses and the sensitivity of diagnostic tests, to the absence of a single known recovery path. While openness about uncertainty is necessary for shared decision-making and is a pillar of patient-centered care, it is a challenge to do so while preserving patient confidence. The authors' aim was to develop, pilot, and evaluate an uncertainty communication curriculum to prepare medical students and residents to confidently navigate such conversations.

Prediction of Pathologic Complete Response for Rectal Cancer Based on Pretreatment Factors Using Machine Learning.

Background: Pathologic complete response after neoadjuvant therapy is an important prognostic indicator for locally advanced rectal cancer and may give insights into which patients might be treated nonoperatively in the future. Existing models for predicting pathologic complete response in the pretreatment setting are limited by small data sets and low accuracy.

Objective: We sought to use machine learning to develop a more generalizable predictive model for pathologic complete response for locally advanced rectal cancer.

Analysis of Specimen Mammography with Artificial Intelligence to Predict Margin Status.

Background: Intraoperative specimen mammography is a valuable tool in breast cancer surgery, providing immediate assessment of margins for a resected tumor. However, the accuracy of specimen mammography in detecting microscopic margin positivity is low. We sought to develop an artificial intelligence model to predict the pathologic margin status of resected breast tumors using specimen mammography.

Program Website Evaluation Regarding Dedicated Research Years Offered in General Surgery Residency Programs in the United States.

Introduction: Research is a vital component in the advancements of surgical sciences due to the reliance of treatment options on innovations and outcomes of patient care. This study aimed to identify research pathways, opportunities, and academic productivities of different general surgery residency programs in the United States.

Materials And Methods: A web-based review was conducted concerning accredited US general surgery residency programs.

Estimating Risk of Locoregional Failure and Overall Survival in Anal Cancer Following Chemoradiation: A Machine Learning Approach.

Background: Optimal treatment of anal squamous cell carcinoma (ASCC) is definitive chemoradiation. Patients with persistent or recurrent disease require abdominoperineal resection (APR). Current models for predicting need for APR and overall survival are limited by low accuracy or small datasets.

Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.

Background: Postoperative gastrointestinal bleeding (GIB) is a rare but serious complication of bariatric surgery. The recent rise in extended venous thromboembolism regimens as well as outpatient bariatric surgery may increase the risk of postoperative GIB or lead to delay in diagnosis. This study seeks to use machine learning (ML) to create a model that predicts postoperative GIB to aid surgeon decision-making and improve patient counseling for postoperative bleeds.

Prediction of Ureteral Injury During Colorectal Surgery Using Machine Learning.

Background: Ureteral injury (UI) is a rare but devastating complication during colorectal surgery. Ureteral stents may reduce UI but carry risks themselves. Risk predictors for UI could help target the use of stents, but previous efforts have relied on logistic regression (LR), shown moderate accuracy, and used intraoperative variables.

Computer Vision Analysis of Specimen Mammography to Predict Margin Status.

Intra-operative specimen mammography is a valuable tool in breast cancer surgery, providing immediate assessment of margins for a resected tumor. However, the accuracy of specimen mammography in detecting microscopic margin positivity is low. We sought to develop a deep learning-based model to predict the pathologic margin status of resected breast tumors using specimen mammography.

Characteristics and symptomatology of colorectal cancer in the young.

Background: The incidence of colorectal cancer in patients <50 years has rapidly risen recently. Understanding the presenting symptoms may facilitate earlier diagnosis. We aimed to delineate patient characteristics, symptomatology, and tumor characteristics of colorectal cancer in a young population.

Improved Prediction of Surgical-Site Infection After Colorectal Surgery Using Machine Learning.

Background: Surgical-site infection is a source of significant morbidity after colorectal surgery. Previous efforts to develop models that predict surgical-site infection have had limited accuracy. Machine learning has shown promise in predicting postoperative outcomes by identifying nonlinear patterns within large data sets.