Cystic colon duplication causing intussusception in a 25-year-old man: report of a case and review of the literature

<p>Abstract</p> <p>Background</p> <p>Colonic intussusception is a rare congenital abnormality, mostly manifesting before the age of two with abdominal pain and acute intestinal obstruction with or without bleeding. In adults it may occur idiopathically or due to an intraluminal tumor mass.</p> <p>Case presentation</p> <p>A 25-year-old man presented with an acute abdomen and severe crampy abdominal pain. The clinical picture mimicked acute appendicitis. Transabdominal ultrasound examination revealed a 5 cm circular mass in the right upper abdomen. The ensuing computed tomography suggested an intussusception in the ascending colon. Intraoperatively, no full thickness invagination was detected. Due to a hard, intraluminal tumor a standard right hemicolectomy with ileotransversostomy was performed. The histopathological analysis revealed a cystic colon duplication leading to mucosal invagination and obstruction.</p> <p>Conclusions</p> <p>In adults, colon intussusception is a rare event causing approximately 1% of all acute intestinal obstructions. Unlike its preferentially nonsurgical management in children, a bowel intussusception in adults should be operated because an organic, often malignant lesion is present in most cases.</p

Enhanced recovery program in laparoscopic colectomy for cancer

Introduction: Both laparoscopic colectomy and application of enhanced recovery program (ERP) in open colectomy have been demonstrated to enable early recovery and to shorten hospital stay. This study evaluated the impact of ERP on results of laparoscopic colectomy and comparison was made with the outcomes of patients prior to the application of ERP. Methods: An ERP was implemented in the authors' center in December 2006. Short-term outcomes of consecutive 84 patients who underwent laparoscopic colonic cancer resection 23 months before (control group) and 96 patients who were operated within 13 months; after application of ERP (ERP group) were compared. Results: Between the ERP and control groups, there was no statistical difference in patient characteristics, pathology, operating time, blood loss, conversion rate or complications. Compared to the control group, patients in the ERP group had earlier passage of flatus [2 (range: 1-5) versus 2 (range: 1-4) days after operation respectively; p∈=∈0.03)] and a lower incidence of prolonged post-operative ileus (6% versus 0 respectively; p∈=∈0.02). There was no difference in the hospital stay between the two groups [4 (range: 2-34) days in control group and 4 (range: 2-23) days in ERP group; p∈=∈0.4)]. The re-admission rate was also similar (7% in control group and 5% in ERP group; p∈=∈0.59). Conclusions: In laparoscopic colectomy for cancer, application of ERP was associated with no increase in complication rate but significant improvement of gastrointestinal function. ERP further hastened patient recovery but resulted in no difference in hospital stay. © 2010 The Author(s).published_or_final_versionSpringer Open Choice, 31 May 201

L-arginine Supplementation Improves Responses to Injury and Inflammation in Dextran Sulfate Sodium Colitis

Inflammatory bowel disease (IBD), consisting of Crohn's disease and ulcerative colitis (UC), results in substantial morbidity and is difficult to treat. New strategies for adjunct therapies are needed. One candidate is the semi-essential amino acid, L-arginine (L-Arg), a complementary medicine purported to be an enhancer of immunity and vitality in the lay media. Using dextran sulfate sodium (DSS) as a murine colonic injury and repair model with similarities to human UC, we assessed the effect of L-Arg, as DSS induced increases in colonic expression of the y+ cationic amino acid transporter 2 (CAT2) and L-Arg uptake. L-Arg supplementation improved the clinical parameters of survival, body weight loss, and colon weight, and reduced colonic permeability and the number of myeloperoxidase-positive neutrophils in DSS colitis. Luminex-based multi-analyte profiling demonstrated that there was a marked reduction in proinflammatory cytokine and chemokine expression with L-Arg treatment. Genomic analysis by microarray demonstrated that DSS-treated mice supplemented with L-Arg clustered more closely with mice not exposed to DSS than to those receiving DSS alone, and revealed that multiple genes that were upregulated or downregulated with DSS alone exhibited normalization of expression with L-Arg supplementation. Additionally, L-Arg treatment of mice with DSS colitis resulted in increased ex vivo migration of colonic epithelial cells, suggestive of increased capacity for wound repair. Because CAT2 induction was sustained during L-Arg treatment and inducible nitric oxide (NO) synthase (iNOS) requires uptake of L-Arg for generation of NO, we tested the effect of L-Arg in iNOS−/− mice and found that its benefits in DSS colitis were eliminated. These preclinical studies indicate that L-Arg supplementation could be a potential therapy for IBD, and that one mechanism of action may be functional enhancement of iNOS activity

A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy

Background: Machine learning (ML) and artificial intelligence are emerging as important components of precision medicine that enhance diagnosis and risk stratification. Risk stratification tools for hypertrophic cardiomyopathy (HCM) exist, but they are based on traditional statistical methods. The aim was to develop a novel machine learning risk stratification tool for the prediction of 5-year risk in HCM. The goal was to determine if its predictive accuracy is higher than the accuracy of the state-of-the-art tools. Method: Data from a total of 2302 patients were used. The data were comprised of demographic characteristics, genetic data, clinical investigations, medications, and disease-related events. Four classification models were applied to model the risk level, and their decisions were explained using the SHAP (SHapley Additive exPlanations) method. Unwanted cardiac events were defined as sustained ventricular tachycardia occurrence (VT), heart failure (HF), ICD activation, sudden cardiac death (SCD), cardiac death, and all-cause death. Results: The proposed machine learning approach outperformed the similar existing risk-stratification models for SCD, cardiac death, and all-cause death risk-stratification: it achieved higher AUC by 17%, 9%, and 1%, respectively. The boosted trees achieved the best performing AUC of 0.82. The resulting model most accurately predicts VT, HF, and ICD with AUCs of 0.90, 0.88, and 0.87, respectively. Conclusions: The proposed risk-stratification model demonstrates high accuracy in predicting events in patients with hypertrophic cardiomyopathy. The use of a machine-learning risk stratification model may improve patient management, clinical practice, and outcomes in general

Disease Progression of Hypertrophic Cardiomyopathy: Modeling Using Machine Learning

Background: Cardiovascular disorders in general are responsible for 30% of deaths worldwide. Among them, hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease that is present in about 1 of 500 young adults and can cause sudden cardiac death (SCD). Objective: Although the current state-of-the-art methods model the risk of SCD for patients, to the best of our knowledge, no methods are available for modeling the patient's clinical status up to 10 years ahead. In this paper, we propose a novel machine learning (ML)-based tool for predicting disease progression for patients diagnosed with HCM in terms of adverse remodeling of the heart during a 10-year period. Methods: The method consisted of 6 predictive regression models that independently predict future values of 6 clinical characteristics: left atrial size, left atrial volume, left ventricular ejection fraction, New York Heart Association functional classification, left ventricular internal diastolic diameter, and left ventricular internal systolic diameter. We supplemented each prediction with the explanation that is generated using the Shapley additive explanation method. Results: The final experiments showed that predictive error is lower on 5 of the 6 constructed models in comparison to experts (on average, by 0.34) or a consortium of experts (on average, by 0.22). The experiments revealed that semisupervised learning and the artificial data from virtual patients help improve predictive accuracies. The best-performing random forest model improved R2 from 0.3 to 0.6. Conclusions: By engaging medical experts to provide interpretation and validation of the results, we determined the models' favorable performance compared to the performance of experts for 5 of 6 targets

Health-oriented physical activity in prevention of musculoskeletal disorders among young Polish musicians

Objectives: Musicians represent a very specific professional group, which due to some occupational hazards is exposed to different health problems known as playing-related musculoskeletal disorders (PRMDs). The aim of this study was to assess correlations between the level of physical activity, and the occurrence of musculoskeletal pain among young instrumentalists. Materials and Methods: Total of 225 Polish musical school students were investigated. To assess the study participants' physical activity level, the moderate to vigorous physical activity (MVPA) index was used. To assess pain complaints on the side of the musculoskeletal system, Nordic Musculoskeletal Questionnaire (NMQ) was applied. The NMQ questionnaire was complemented by adding a visual-analog scale (VAS), which also allowed to assess pain intensity on a numerical scale 1-10. Results: The pain localized in neck, shoulders, upper and lower back was reported significantly more often by the participants who did not meet standard criteria for the recommended or minimal physical activity level. Conclusion: Performing the recommended health-oriented physical activity may reduce the prevalence of musculoskeletal pain in young musicians