Prospective Cohort Study

Secret History: Return of the Black Death Channel 4, 7-8pm In 1348 the Black Death swept through London, killing people within days of the appearance of their first symptoms. Exactly how many died, and why, has long been a mystery. This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale. And they ask, what might be coming next?

Medscape

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

https://www.commed.vcu.edu/Chronic_Disease/2012/cochranrvwrschbias.pdf

The Cochrane Collaboration's tool for assessing risk of bias in randomised trials

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Food, Nutrition, Physical Activity, and the Prevention of Cancer : a Global Perspective : 食物、栄養、身体活動とがんの予防 : 世界的展望(後篇)

Effect of age, patient's sex, and type of trauma on the correlation between size of sphincter defect and anal pressures in posttraumatic fecal incontinence

Aim Three-dimensional (3D) printing has been recognized as a revolutionary technological innovation that has benefitted numerous disciplines, including medicine. The present systematic review aimed to demonstrate the current applications of 3D printing in colorectal surgery along with the limitations and potential future applications of this innovation. Method A PRISMA-compliant systematic literature search of studies that applied 3D printing in colorectal surgery in the period from January 1990 to July 2018 was conducted. Electronic databases including PubMed/Medline, Scopus and the Cochrane Library were searched. All full-text original articles were eligible for inclusion. Results Nine studies including 58 patients with a median age of 60.7 years were reviewed. The studies assessed 3D printing in patients with planned stoma construction, colon cancer with liver metastasis, right colon cancer, rectal cancer, intractable constipation and anal fistula. The applications of 3D printing were classified into three categories: patient education, preoperative planning and evaluation of response of colorectal liver metastasis to chemotherapy. 3D printed models aided in planning resection of colorectal liver metastasis, facilitating D3 lymphadenectomy in complete mesocolic excision, improving the understanding of pelvic anatomy in laparoscopic rectal cancer treatment, guiding electrode implantation in sacral neuromodulation for intractable constipation, and elucidating the morphology of anal fistula tract and anal sphincter muscles. Conclusion Colorectal surgery may benefit from 3D printing in enhancing patient education before stoma construction, preoperative planning and evaluation of the response of liver metastasis to chemotherapy using 3D ultrasonography.

Systematic review of the applications of three-dimensional printing in colorectal surgery

Acute mesenteric ischemia (AMI) is a serious medical condition that can progress to transmural bowel necrosis. Prediction of the onset of bowel necrosis in AMI is crucial to justify surgical intervention before more severe consequences supervene. This systematic review aimed to identify the significant predictors of bowel necrosis in AMI in the current literature. In adherence to the PRISMA guidelines, electronic databases were searched for studies that reported significant independent predictors of bowel necrosis in AMI. The quality of the studies was assessed with MINORS score. The main outcomes of the review were the incidence and predictors of bowel necrosis in patients with AMI and the mortality rate. This systematic review comprised nine articles that included 963 patients of a median age of 57 years. Irreversible bowel necrosis was found in 402 (41.7%) patients. The significant predictors of bowel necrosis were subdivided into eight clinical, seven biochemical, and six radiologic parameters. Eight parameters were reported by two or more studies, whereas 13 were reported by a single study. Based on the weight and odds ratio of the predictive parameters, a prognostic scoring system, Emile-Khan Score, was proposed. Several clinical, biochemical, and radiologic predictors of bowel necrosis were reported in the literature. Pooling of odds ratios was feasible for eight factors that were reported by more than one study. Further studies are needed to ascertain the utility of the other predictive factors. Level of evidence: Level II (systematic review and meta-analysis).

Predictors of bowel necrosis in patients with acute mesenteric ischemia: systematic review and meta-analysis.

Abstract Purpose Prediction of the onset of de novo gastroesophageal reflux disease (GERD) after sleeve gastrectomy (SG) would be helpful in decision-making and selection of the optimal bariatric procedure for every patient. The present study aimed to develop an artificial intelligence (AI)-based model to predict the onset of GERD after SG to help clinicians and surgeons in decision-making. Materials and Methods A prospectively maintained database of patients with severe obesity who underwent SG was used for the development of the AI model using all the available data points. The dataset was arbitrarily split into two parts: 70% for training and 30% for testing. Then ranking of the variables was performed in two steps. Different learning algorithms were used, and the best model that showed maximum performance was selected for the further steps of machine learning. A multitask AI platform was used to determine the cutoff points for the top numerical predictors of GERD. Results In total, 441 patients (76.2% female) of a mean age of 43.7 ± 10 years were included. The ensemble model outperformed the other models. The model achieved an AUC of 0.93 (95%CI 0.88–0.99), sensitivity of 79.2% (95% CI 57.9–92.9%), and specificity of 86.1% (95%CI 70.5–95.3%). The top five ranked predictors were age, weight, preoperative GERD, size of orogastric tube, and distance of first stapler firing from the pylorus. Conclusion An AI-based model for the prediction of GERD after SG was developed. The model had excellent accuracy, yet a moderate sensitivity and specificity. Further prospective multicenter trials are needed to externally validate the model developed. Graphical Abstract 

/pdf/development-and-validation-of-an-artificial-intelligence-2pi89s21.pdf

Development and Validation of an Artificial Intelligence-Based Model to Predict Gastroesophageal Reflux Disease After Sleeve Gastrectomy

Impact of change in the surgical plan based on indocyanine green fluorescence angiography on the rates of colorectal anastomotic leak: a systematic review and meta-analysis

Sameh Hany Emile

Papers

Effect of age, patient's sex, and type of trauma on the correlation between size of sphincter defect and anal pressures in posttraumatic fecal incontinence

Systematic review of the applications of three-dimensional printing in colorectal surgery

Predictors of bowel necrosis in patients with acute mesenteric ischemia: systematic review and meta-analysis.

Development and Validation of an Artificial Intelligence-Based Model to Predict Gastroesophageal Reflux Disease After Sleeve Gastrectomy

Impact of change in the surgical plan based on indocyanine green fluorescence angiography on the rates of colorectal anastomotic leak: a systematic review and meta-analysis