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. We sought to use an emerging approach in predictive analytics, machine learning, to create a model for UI. Methods Patients who underwent colorectal surgery were identified in the National Surgical Quality Improvement Program (NSQIP) database. Patients were split into training, validation, and test sets. The primary outcome was UI. Three machine learning approaches were tested including random forest (RF), gradient boosting (XGB), and neural networks (NN), and compared with traditional LR. Model performance was assessed using area under the curve (AUROC). Results The data set included 262,923 patients, of whom 1519 (.578%) experienced UI. Of the modeling techniques, XGB performed the best, with an AUROC score of .774 (95% CI .742-.807) compared with .698 (95% CI .664-.733) for LR. Random forest and NN performed similarly with scores of .738 and .763, respectively. Type of procedure, work RVUs, indication for surgery, and mechanical bowel prep showed the strongest influence on model predictions. Conclusions Machine learning-based models significantly outperformed LR and previous models and showed high accuracy in predicting UI during colorectal surgery. With proper validation, they could be used to support decision making regarding the placement of ureteral stents preoperatively

Increased colonic expression of ACE2 associates with poor prognosis in Crohn’s disease

The host receptor for SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2), is highly expressed in small intestine. Our aim was to study colonic ACE2 expression in Crohn's disease (CD) and non-inflammatory bowel disease (non-IBD) controls. We hypothesized that the colonic expression levels of ACE2 impacts CD course. We examined the expression of colonic ACE2 in 67 adult CD and 14 NIBD control patients using RNA-seq and quantitative (q) RT-PCR. We validated ACE2 protein expression and localization in formalin-fixed, paraffin-embedded matched colon and ileal tissues using immunohistochemistry. The impact of increased ACE2 expression in CD for the risk of surgery was evaluated by a multivariate regression analysis and a Kaplan–Meier estimator. To provide critical support for the generality of our findings, we analyzed previously published RNA-seq data from two large independent cohorts of CD patients. Colonic ACE2 expression was significantly higher in a subset of adult CD patients which was defined as the ACE2-high CD subset. IHC in a sampling of ACE2-high CD patients confirmed high ACE2 protein expression in the colon and ileum compared to ACE2-low CD and NIBD patients. Notably, we found that ACE2-high CD patients are significantly more likely to undergo surgery within 5 years of CD diagnosis, and a Cox regression analysis found that high ACE2 levels is an independent risk factor for surgery (OR 2.17; 95% CI, 1.10–4.26; p = 0.025). Increased intestinal expression of ACE2 is associated with deteriorated clinical outcomes in CD patients. These data point to the need for molecular stratification that can impact CD disease-related outcomes

Building Rapport and Earning the Surgical Patient\u27s Trust in the Era of Social Distancing: Teaching Patient-Centered Communication During Video Conference Encounters to Medical Students.

BACKGROUND: Effective physician communication improves care, and many medical schools and residency programs have adopted communication focused curricula. The COVID-19 pandemic has shifted the doctor-patient communication paradigm with the rapid adoption of video-based medical appointments by the majority of the medical community. The pandemic has also necessitated a sweeping move to online learning, including teaching and facilitating the practice of communication skills remotely. We aimed to identify effective techniques for surgeons to build relationships during a video consult, and to design and pilot a class that increased student skill in communicating during a video consult. METHODS: Fourth-year medical students matched into a surgical internship attended a 2-hour class virtually. The class provided suggestions for building rapport and earning trust with patients and families by video, role play sessions with a simulated patient, and group debriefing and feedback. A group debriefing generated lessons learned and best practices for telemedicine communication in surgery. RESULTS: Students felt the class introduced new skills and reinforced current ones; most reported higher self-confidence in target communication skills following the module. Students were particularly appreciative of opportunity for direct observation of skills and immediate faculty feedback, noting that the intimate setting was unique and valuable. Several elements of virtual communications required increased focus to communicate empathy and concern. Proper lighting and positioning relative to the camera were particularly important and body movement required narration to minimize misinterpretation. A patient\u27s distress was more difficult to interpret; asking direct questions was recommended to understand the patient\u27s emotional state. CONCLUSIONS: There is a need to teach video-conference communication skills to enable surgical teams to build rapport in this distinct form of consultation. Our training plan appears effective at engaging learners and improving skills and confidence, and identifies areas of focus when teaching virtual communication skills

Virtual Communication Across Differences: Development of a Workshop on Managing Patient Bias

PROBLEM: Despite the prevalence and detrimental effects of racial discrimination in American society and its health care systems, few medical schools have designed and implemented curricula to prepare medical students to respond to patient bias and racism. APPROACH: During the summer of 2020, a virtual communication class was designed that focused on training medical students in how to respond to patient bias and racism. Following brief didactics at the start of the session, students practiced scenarios with actors in small groups and received direct feedback from faculty. For each scenario, students were instructed to briefly gather a patient\u27s history and schedule an appointment with the attending whose name triggered the patient to request an American provider. In one scenario, the patient\u27s request was motivated by untreated hearing loss and difficulty understanding accents. In another, it was motivated by racist views toward foreign physicians. Students were to use motivational interviewing (MI) to uncover the reasoning behind the request and respond appropriately. Students assessed their presession and postsession confidence on 5 learning objectives that reflect successful communication modeled after MI techniques. OUTCOMES: Following the session, student skills confidence increased in exploring intentions and beliefs (P = .026), navigating a conversation with a patient exhibiting bias (P = .019) and using nonverbal skills to demonstrate empathy (P = .031). Several students noted that this was their first exposure to the topic in a medical school course and first opportunity to practice these skills under supervision. NEXT STEPS: The experience designing and implementing this module preparing students in responding to patient bias and racism suggests that such an effort is feasible, affordable, and effective. With the clear need for such a program and positive impact on student confidence navigating these discussions, including such training in medical school programs appears feasible and is strongly encouraged

Educating the surgeon-scientist: A qualitative study evaluating challenges and barriers toward becoming an academically successful surgeon

Background: The advancement of surgical science relies on educating new generations of surgeon-scientists. Career development awards (K Awards) from the National Institutes of Health, often considered a marker of early academic success, are one way physician-scientists may foster skills through a mentored research experience. This study aimed to develop a conceptual framework to understand institutional support and other factors leading to a K Award.Methods: A national, qualitative study was conducted with academic surgeons. Participants included 15 K Awardees and 12 surgery department Chairs. Purposive sampling ensured a diverse range of experiences. Semistructured, in-depth telephone interviews were conducted. Interviews were audio recorded and transcribed verbatim, and 2 reviewers analyzed the transcripts using Grounded Theory methodology.Results: Participants described individual and institutional factors contributing to success. K Awardees cited personal factors such as perseverance and team leadership skills. Chairs described the K Awardee as an institutional investment requiring protected time for research, financial support, and mentorship. Both K Awardees and Chairs identified a number of challenges unique to the surgeon-scientist, including financial strains and competing clinical demands.Conclusion: Institutional support for surgeons pursuing K Awards is a complex investment with significant initial costs to the department. Chairs act as stewards of institutional resources and support those surgeon-scientists most likely to be successful. Although the K Award pathway is one way to develop surgeon-scientists, financial burdens and challenges may limit its usefulness. These findings, however, may better prepare young surgeons to develop career plans and identify new mechanisms for academic productivity

Heightened efficacy of nitric oxide-based therapies in type II diabetes mellitus and metabolic syndrome

Type II diabetes mellitus (DM) and metabolic syndrome are associated with accelerated restenosis following vascular interventions due to neointimal hyperplasia. The efficacy of nitric oxide (NO)-based therapies is unknown in these environments. Therefore, the aim of this study is to examine the efficacy of NO in preventing neointimal hyperplasia in animal models of type II DM and metabolic syndrome and examine possible mechanisms for differences in outcomes. Aortic vascular smooth muscle cells (VSMC) were harvested from rodent models of type II DM (Zucker diabetic fatty), metabolic syndrome (obese Zucker), and their genetic control (lean Zucker). Interestingly, NO inhibited proliferation and induced G0/G1 cell cycle arrest to the greatest extent in VSMC from rodent models of metabolic syndrome and type II DM compared with controls. This heightened efficacy was associated with increased expression of cyclin-dependent kinase inhibitor p21, but not p27. Using the rat carotid artery injury model to assess the efficacy of NO in vivo, we found that the NO donor PROLI/NO inhibited neointimal hyperplasia to the greatest extent in type II DM rodents, followed by metabolic syndrome, then controls. Increased neointimal hyperplasia correlated with increased reactive oxygen species (ROS) production, as demonstrated by dihydroethidium staining, and NO inhibited this increase most in metabolic syndrome and DM. In conclusion, NO was surprisingly a more effective inhibitor of neointimal hyperplasia following arterial injury in type II DM and metabolic syndrome vs. control. This heightened efficacy may be secondary to greater inhibition of VSMC proliferation through cell cycle arrest and regulation of ROS expression, in addition to other possible unidentified mechanisms that deserve further exploration

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

Abstract 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. Clinical outcomes including development of strictures or fistulas and progression to surgery were analyzed using differential expression and modeled using machine learning. Differential expression analysis revealed downregulation of pathways related to inflammation and extra-cellular matrix production in patients with strictures. Machine learning-based models were able to incorporate colonic gene expression and clinical characteristics to predict outcomes with high accuracy. Models showed an area under the receiver operating characteristic curve (AUROC) of 0.84 for strictures, 0.83 for remission, and 0.75 for surgery. Genes with potential prognostic importance for strictures (REG1A, MMP3, and DUOX2) were not identified in single gene differential analysis but were found to have strong contributions to predictive models. Our findings in FFPE tissue support the importance of colonic gene expression and the potential for machine learning-based models in predicting outcomes for pediatric CD