A comparison of the academic impact of plastic surgery units in the United Kingdom and Ireland using bibliometric analysis

Academic output is just one aspect of a successful career as a plastic surgeon. However, for those with a strong interest in academia, the academic output of a department will likely be a key factor when deciding how to rank jobs. The aim of this study was to quantify and rank the academic output of plastic surgery units across the UK and Ireland. The Institute for Scientific Information (ISI) Web of Science Bibliometric analysis tool was used to collate cumulative (1950–2016), 10 year (2006–2016) and 3 years (2013–2015) research output data for plastic surgery units in the UK and Ireland. Sixty-six plastic surgery units were identified. Departments were ranked for each time period according to the number of papers produced, number of citations (Nc) and h-index (a measure of the impact of scientific output). The top 3 departments for number of papers in the last 10 years were The Royal Free Hospital, London (226) Broomfield Hospital, Chelmsford (218), and Morriston Hospital and Swansea (188). The top 3 for h-number were The Royal Free Hospital (21) Wythenshawe Hospital, Manchester (18) and Morriston Hospital (17). Academic output varies across plastic surgery units in the UK and Ireland. A number of departments have consistently maintained high academic outputs across the years and will be of interest to surgeons hoping to pursue a career in academia.     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.     

Valor de la escala ASPECTS de circulación posterior y del índice puente-mesencéfalo en imágenes de TC sin contraste y angiografía por TC en pacientes con oclusiones de la arteria basilar recanalizados tras trombectomía mecánica

Purpose

Endovascular treatment with mechanical thrombectomy devices demonstrated high recanalization rates but functional outcome did not correlate with high rates of recanalization obtained. Patient selection prior to the endovascular treatment is very important in the final outcome of the patient. The primary aim of our study was to evaluate the prognostic value of posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) and Pons-Midbrain Index (PMI) scores in patients with Basilar Artery Occlusion (BAO) treated with successful angiographic recanalization after mechanical thrombectomy.

Ethik,Kommunikation und interdisziplinäre Zusammenarbeit – per Gesetz?!

Die Onkologie - Die Corona-Pandemie hat in den letzten Monaten verdeutlicht, dass das Thema Sterblichkeit trotz erheblicher Fortschritte im Bereich der Hospiz- und Palliativversorgung zu...     

甲状腺疾病患者血清 Tg-CIC 中 Tg-Ab 水平检测及相关临床研究

目的　对血清甲状腺球蛋白免疫复合物 (thyroglobulin circulating immune complex, Tg-CIC) 中抗甲状腺球蛋白抗体 (anti-thyroglobulin antibody, Tg-Ab) 含量检测，探讨 Tg-CIC 在甲状腺疾病中的临床以及流行病学意义。方法　收集甲状腺疾病患者血清标本 187 例，每例血清标本分为两组 ( 实验组和空白对照组 )，采用免疫复合物解离专利技术对甲状腺疾病患者血清标本 Tg-CIC 进行分离、解离，通过检测 Tg-CIC 解离后的 Tg-Ab 含量来间接反映甲状腺疾病患者血清中Tg-CIC 水平，按照不同的甲状腺疾病进行分组并对实验结果分析讨论。结果　不同甲状腺患者血清中 Tg-CIC 总阳性率达 92.51%，不同甲状腺疾病血清中 Tg-CIC 的阳性率差异无统计学意义 (χ?=2.917, P>0.05)。不同甲状腺疾病患者间血清游离 Tg-Ab 含量差异无统计学意义 (H=3.882, P>0.05)，不同甲状腺疾病患者间血清 CIC 中 Tg-Ab 含量差异无统计学意义(H=5.5842, P>0.05)。不同甲状腺疾病患者中，甲状腺功能亢进、甲状腺炎以及甲状腺结节患者血清游离 Tg-Ab 的含量与血清 CIC 中的 Tg-Ab 含量呈正相关 (P<0.05)，甲状腺功能减退、甲状腺肿瘤患者血清游离 Tg-Ab 的含量与血清 CIC 中的Tg-Ab 含量不相关 (P>0.05)。结论　在甲状腺疾病患者血清中，大部分可检出 Tg-CIC，与疾病类型无关。而甲状腺疾病患者中，甲状腺功能亢进、甲状腺炎以及甲状腺结节患者血清游离 Tg-Ab 含量与血清 CIC 中 Tg-Ab 含量存在相关性，为我们进一步了解 Tg-CIC 与甲状腺疾病的发生、发展的相关性研究奠定了基础，提供了新的研究视角。     

Prevalence of HER2 Expression and Its Correlation with Clinicopathological Parameters in Gastric or Gastroesophageal Junction Adenocarcinoma in North-East Indian Population

Objective: Human epidermal growth factor receptor 2 (erbb2/HER2) overexpression, has now been implicatedin advanced gastric and gastroesophageal junction cancers. The study was conducted to determine the rate of HER2positivity in patients with locally advanced or metastatic gastric and gastroesophageal adenocarcinoma in North-EastIndia and to assess the impact of various demographic and clinical parameters on HER2 positivity. Methods: A total of68 patients of age >18 years of gastric and gastroesophageal adenocarcinoma diagnosed on histopathological examinationfrom September 2016 to February 2018 at Dr B Borooah Cancer Institute, Assam were enrolled for the observational(epidemiological) study. All patients were subjected to the HER2 immunohistochemistry test using a FDA-approved,standardized test kit. HER2 expression was correlated with various demographic and clinicopathological parameters.Results: The overall rate of HER2 positivity in the population studied was 56% (n=38). The rate was non-significantlyhigher in male, older age group (>60 years) and Hindu population. Similarly, HER2 positivity rate was higher in patientswith well differentiated histology and was more common in patients with stage II and III diseases, but neither of theassociations is statistically significant. HER2 positivity rate was significantly higher in proximal and in GEJ tumours(56% versus 44%, P=0.002). Conclusion: HER2 overexpression was evident in 56% of the North-East Indian patientswith locally advanced and metastatic gastric and gastroesophageal adenocarcinoma. The overexpression correlatedsignificantly with primary tumour site. Routine testing of gastric and gastroesophageal tumours for HER2 expressionis recommended to provide a therapeutic advantage in Indian patients.     

Explicit Finite Element Models Accurately Predict Subject-Specific and Velocity-Dependent Kinetics of Sideways Fall Impact

The majority of hip fractures in the elderly are the result of a fall from standing or from a lower height. Current injury models focus mostly on femur strength while neglecting subject-specific loading. This article presents an injury modeling strategy for hip fractures related to sideways falls that takes subject-specific impact loading into account. Finite element models (FEMs) of the human body were used to predict the experienced load and the femoral strength in a single model. We validated these models for their predicted peak force, effective pelvic stiffness, and fracture status against matching ex vivo sideways fall impacts (n = 11) with a trochanter velocity of 3.1 m/s. Furthermore, they were compared to sideways impacts of volunteers with lower impact velocities that were previously conducted by other groups. Good agreement was found between the ex vivo experiments and the FEMs with respect to peak force (root mean square error [RMSE] = 10.7%, R² = 0.85) and effective pelvic stiffness (R² = 0.92, RMSE = 12.9%). The FEMs were predictive of the fracture status for 10 out of 11 specimens. Compared to the volunteer experiments from low height, the FEMs overestimated the peak force by 25% for low BMI subjects and 8% for high BMI subjects. The effective pelvic stiffness values that were derived from the FEMs were comparable to those derived from impacts with volunteers. The force attenuation from the impact surface to the femur ranged between 27% and 54% and was highly dependent on soft tissue thickness (R² = 0.86). The energy balance in the FEMS showed that at the time of peak force 79% to 93% of the total energy is either kinetic or was transformed to soft tissue deformation. The presented FEMs allow for direct discrimination between fracture and nonfracture outcome for sideways falls and bridge the gap between impact testing with volunteers and impact conditions representative of real life falls. © 2019 American Society for Bone and Mineral Research.