Point-of-care measured serum cholinesterase activity predicts patient outcome following severe burns

Risk stratification is of utmost importance in burn therapy. However, suitable bedside biomarkers to evaluate the emerging inflammatory response following burn injuries are missing. Serum cholinesterase (butyrylcholinesterase, BChE) has been shown to be a clinically relevant biomarker in acute inflammatory diseases including burns.In this observational cohort study BChE activity was measured by using point-of-care testing (POCT), a novel method in acute burn care. POCT measurements were performed at emergency room admission (ERA) of 35 patients and repeated 12, 24 and 48 h later. All patients or their legal designees gave informed consent.Patients with burn injuries showed sustained BChE activity reduction following hospital admission. BChE activity correlated negatively with burn injury severity, organ failure severity and intensive care unit resource requirements. BChE activity measured at ERA and 12 h later identified survivors and predicted 28-day patient outcome with noninferior efficacy compared to the abbreviated burn severity index (ABSI) scoring. Finally, POCT-measured BChE activity might complement ABSI scoring and possibly improve early risk stratification in acute burn care therapy.     

Can Machine Learning Methods Produce Accurate and Easy-to-Use Preoperative Prediction Models of One-Year Improvements in Pain and Functioning After Knee Arthroplasty?

BackgroundApproximately 15%-20% of total knee arthroplasty (TKA) patients do not experience clinically meaningful improvements. We sought to compare the accuracy and parsimony of several machine learning strategies for developing predictive models of failing to experience minimal clinically important differences in patient-reported outcome measures (PROMs) 1 year after TKA.MethodsPatients (N = 587) in 3 large Veteran Health Administration facilities completed PROMs before and 1 year after TKA (92% follow-up). Preoperative PROMs and electronic health record data were used to develop and validate models to predict failing to experience at least a minimal clinically important difference in Knee Injury and Osteoarthritis Outcome Score (KOOS) Total, KOOS JR, and KOOS subscales (Pain, Symptoms, Activities of Daily Living, Quality of Life, and recreation). Several machine learning strategies were used for model development. Ten-fold cross-validation and bootstrapping were used to produce measures of overall accuracy (C-statistic, Brier Score). The sensitivity and specificity of various predicted probability cut-points were examined.ResultsThe most accurate models produced were for the Activities of Daily Living, Pain, Symptoms, and Quality of Life subscales of the KOOS (C-statistics 0.76, 0.72, 0.72, and 0.71, respectively). Strategies varied substantially in terms of the numbers of inputs required to achieve similar accuracy, with none being superior for all outcomes.ConclusionModels produced in this project provide estimates of patient-specific improvements in major outcomes 1 year after TKA. Integrating these models into clinical decision support, informed consent and shared decision making could improve patient selection, education, and satisfaction.Level of EvidenceLevel III, diagnostic study.     

Is Patient Satisfaction After Total Knee Arthroplasty Predictable Using Patient Characteristics and Preoperative Patient-Reported Outcomes?

BackgroundDissatisfaction after total knee arthroplasty (TKA) remains a difficult problem. Patient characteristics and preoperative patient-reported outcomes (PROs) are potential predictors of satisfaction one year after TKA. Being able to predict the outcome preoperatively might reduce the number of less satisfied patients.MethodsA retrospective cohort study on prospectively collected data of 1239 primary TKA patients (ASA I-II, BMI <35) was performed. Primary outcome was degree of patient satisfaction one year after TKA (Numeric Rating Scale (NRS) 0-10). Secondary outcomes were degree of patient satisfaction six months and two years after TKA and being dissatisfied (NRS 0-6) or satisfied (NRS 7-10) at all three time points. Multivariate linear and binary logistic regression analyses were executed with patient characteristics and preoperative PROs as potential predictors.ResultsOne year after TKA, median NRS satisfaction score was 9.0 (8.0-10.0) and 1117 (90.2%) patients were satisfied. BMI, degree of medial cartilage damage, previous knee surgery, Knee injury and Osteoarthritis Outcome Score-Physical Function Short Form score, EQ VAS score, and anxiety were identified as predictors of the degree of patient satisfaction (P = .000, R² = 0.027). Models on secondary outcomes reported R² of 1.7%-7.1% (P < .05). All models showed bad agreement between observed and predicted values for lower NRS satisfaction scores and being dissatisfied.ConclusionThe degree of patient satisfaction and the chance of being dissatisfied or satisfied six months, one, and two years after TKA are predictable by patient characteristics and preoperative PROs but not at a reliability level that is clinically useful.     

基于生物信息学探讨SARS-CoV-2介导免疫炎症反应诱发动脉粥样硬化进展的潜在机制与防治中药筛选

目的 应用生物信息学技术,从免疫炎症角度探索严重急性呼吸综合征冠状病毒-2(severe acute respiratory syndrome coronavirus-2,SARS-CoV-2)感染诱导动脉粥样硬化（atherosclerosis,AS）进展的核心靶点及重要通路,进而预测潜在防治中药。方法 从基因表达数据库（Gene Expression Omnibus,GEO）中获取新型冠状病毒肺炎患者和动脉粥样硬化患者芯片数据,利用“limmar”包及“Venn”包筛选2种疾病的共同差异表达基因（differentially expressed genes,DEGs）,对共同DEGs进行基因本体论（gene ontology,GO）和京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes,KEGG）分析,注释其功能及重要通路。对2组基因集进行免疫细胞和免疫功能打分,评估免疫细胞浸润水平。利用STRING数据库,构建蛋白-蛋白互作（protein-protein interaction,PPI）网络;通过Cytoscape的CytoH...     

Short-term multiorgan metabolic benefits of rapid weight loss after sleeve gastrectomy in severely obese patients

BackgroundSleeve gastrectomy (SG) has become the most prevalent bariatric-metabolic surgical approach in the United States. Its popularity among surgeons and patients is mainly due to a better safety profile and less overall morbidity, with broad benefits from a systemic and metabolic perspective.ObjectiveComprehensively describe the short-term multiorgan metabolic effects of rapid weight loss after SG.SettingAcademic hospital, United States.MethodsWe retrospectively reviewed the charts of patients that underwent SG at our institution between 2012 and 2016. We analyzed the required variables to calculate multiple risk scores, such as cardiovascular, hypertension, and diabetes risk scores. Furthermore, the renal and hepatic functions and the metabolic and hematologic profiles were assessed at 12 months of follow-up.ResultsA total of 1002 patients were included in the analysis. The percentage of excess body mass index loss was, on average, 65% at 12 months of follow-up. We observed a positive cardio-renal-hepatic improvement, demonstrated by a substantial reduction of the 10-year cardiovascular risk. We noticed an improvement of renal function, which was more significant in chronic kidney disease (stage ≥2), and a significant improvement on liver function tests (measured by decreased aspartate aminotransferase and alanine transaminase) at 12 months of follow-up. Our data also show a positive impact on decreasing the risk of developing hypertension and type 2 diabetes. There was a positive impact on the lipid profile, with the exception of low-density lipoprotein.ConclusionThere are significant short-term benefits on multiorgan metabolic parameters after rapid weight loss in severely obese patients undergoing sleeve gastrectomy.     

Risk of insomnia and hypnotics use among emergency physicians

This study investigated the risk of insomnia and hypnotics use among emergency physicians. This cross-sectional study recruited physicians working in Taiwanese hospitals in 2015 and the general population as the participants. Data from 1,097 emergency physicians obtained from the National Health Insurance Research Database were grouped into the case group, whereas 14,112 nonemergency physicians and 4,388 people from the general population were categorized into the control groups. This study used logistic regression and conditional logistic regression to compare the risks of insomnia between emergency and nonemergency physicians and between emergency physicians and the general population, respectively. The prevalence of insomnia among emergency physicians, nonemergency physicians and general population was 5.56%, 4.08%, and 1.73%, respectively. Compared with nonemergency physicians and the general population, emergency physicians had a significantly higher risk of insomnia. The proportions of emergency physicians, nonemergency physicians, and general population using hypnotics were 19.96%, 18.24%, and 13.26%, respectively. Among emergency physicians who used hypnotics, 49.77%, 25.57%, and 24.66% used only benzodiazepines, only nonbenzodiazepines, and both benzodiazepines and nonbenzodiazepines, respectively. Nonpharmacological interventions to improve insomnia and reminder of safe use of hypnotics to emergency physicians can serve as references for hospitals in developing health-promoting activities.