右美托咪定联合综合体温保护对腔镜手术治疗老年恶性肿瘤患者苏醒期质量及免疫功能的影响

目的 探讨右美托咪定联合综合体温保护对腔镜手术治疗老年恶性肿瘤患者苏醒期质量及免疫功能的影响。方法 选择择期行腔镜手术治疗的老年恶性肿瘤患者90例，随机均分为3组：对照组（C组）、体温保护组（T组）和体温保护联合右美托咪定组（T-D组），每组30例。C组常规体温保护，T组和T-D组综合体温保护；T-D组麻醉诱导前10 min泵注右美托咪定0.5 μg/kg。记录3组患者麻醉诱导开始时（T₀）、手术开始30 min（T₁）、60 min（T₂）、90 min（T₃）、120 min（T₄）以及手术结束时（T₅）的鼻咽温度；于T₀、术后2 h（T₆）、24 h（T₇）和48 h（T₈）时抽取静脉血标本，测定T淋巴细胞亚群（CD3⁺、CD4⁺和CD8⁺）和自然杀伤细胞（NK cell）水平；记录患者术中麻醉药物用量及苏醒期质量指标。结果 与T₀比较，C组T₂～T₅时点鼻咽温度均明显降低（P < 0.05）；与C组比较，T组和T-D组T₂～T₅时点鼻咽温度明显升高（P < 0.05）。与T₀时点比较，C组、T组和T-D组T₆、T₇和T₈时点CD3⁺和NK cell活性均明显降低（P < 0.05）；C组在T₆、T₇和T₈时点，T组和T-D组在T₆和T₇时点，CD4⁺活性均明显降低（P < 0.05）。与C组比较，T组和T-D组T₆和T₇时点CD3⁺细胞活性均明显升高（P < 0.05）；T组在T₇时点，T-D组在T₆和T₇时点，CD4⁺细胞活性均明显升高（P < 0.05）；T组在T₇时点，T-D组在T₆、T₇和T₈时点，NK cell活性均明显升高（P < 0.05）。结论 采用体温保护措施联合右美托咪定能够维持老年恶性肿瘤患者的体温稳定，减少围手术期意外低体温（IPH）的发生，并有效提高患者苏醒期质量，减轻免疫抑制程度，加速患者早期恢复。     

COVID-19 convalescent plasma: current status,lessons from the past and future perspectives

When the COVID-19 pandemic hit, blood transfusion services worldwide started collection of convalescent plasma as early as possible, as exemplified by the response in Norway. There were challenges related to donor selection, donor safety, testing for relevant antibodies and indications for and dosing of the convalescent plasma. As more knowledge became available, the product quality was more standardised. Multiple case reports, observational studies and some randomized studies were published during the pandemic, as well as laboratory studies reporting different approaches to antibody testing. The results were conflicting and the importance of convalescent plasma was disputed.Even though there has been strong international collaboration with involvement of many key organisations, we may better prepare for the next pandemic. An even stronger, more formalised collaboration between these organisations could provide more clear evidence of the importance of convalescent plasma, based on the principles of passive immunisation.     

A Coupled FEM-BEM Approach for the Solution of the Free-Boundary Axi-Symmetric Plasma Equilibrium Problem

In this paper we present a coupled Finite Element Method – Boundary Element Method (FEM-BEM) approach for the solution of the free-boundary axi-symmetric plasma equilibrium problem. The proposed method, obtained from an improvement of the Hagenow-Lackner coupling method, allows to efficiently model the equilibrium problem in unbounded domains by discretizing only the plasma region; the external conductors can be modelled either as 2D or 3D models, according to the problem of interest. The paper explores different iterative methods for the solution of the nonlinear Grad-Shafranov equation, such as Picard, Newton-Raphson and Newton-Krylov, in order to provide a robust and reliable tool, able to handle large-scale problems (e.g. high resolution equilibria). This method has been implemented in the FRIDA code (FRee-boundary Integro-Differential Axisimmetric – https://github. om/matteobonotto/ FRIDA), together with a suitable Adaptive Integration Technique (AIT) for the computation of the source term. FRIDA has been successfully tested and validated against experimental data from RFX-mod device, and numerical equilibria of an ITER-like device.     

Orientation and mobility outcome measures

Despite orientation and mobility (O&M) being a significant factor determining quality of life of people with low vision or blindness, there are no gold standard measures or agreement on how to measure O&M performance. In the first part of this systematic review, an inventory of O&M outcome measures used by recent studies to assess the performance of orientation and/or mobility of adults with vision impairment (low vision and blindness) is presented. A wide variety of O&M outcome measures have been implemented in different fields of study, such as epidemiologic research and interventional studies evaluating training, assistive technology, vision rehabilitation and vision restoration. The most frequent aspect of outcome measures is efficiency such as time, distance, speed and percentage of preferred walking speed, followed by obstacle contacts and avoidance, and dis/orientation and veering. Other less commonly used aspects are target identification, safety and social interaction and self-reported outcome measures. Some studies employ sophisticated equipment to capture and analyse O&M performance in a laboratory setting, while others carry out their assessment in real-world indoor or outdoor environments. In the second part of this review, the appropriateness of implementing the identified outcome measures to assess O&M performance in clinical and functional O&M practice is evaluated. Nearly a half of these outcome measures meet all four criteria of face validity (either clinical or functional), responsiveness, reliability and feasibility and have the potential to be implemented in clinical or functional O&M practice. The findings of this review confirm the complicated and dynamic nature of O&M. Multiple measures are required in any evaluation of O&M performance to facilitate holistic assessment of O&M abilities and limitations of each individual.     

Plasmacytic cutaneous pathology: A review

We review the spectrum of cutaneous disorders associated with inflammatory and neoplastic plasmacytic pathology. Because plasma cells are derived from B‐lymphocytes our overview includes discussion of certain lymphoplasmacytic proliferations. It is structured along histopathological lines, addressing conditions characterized by (a) cutaneous plasma cell infiltrates, (b) deposits of plasma cell products or their derivatives in the skin and (c) miscellaneous, poorly understood cutaneous complications of plasmacytic disorders. Lesions arising primarily in the skin and those due to cutaneous involvement by multisystem disorders are addressed. The range includes a spectrum of tumefactive and circulatory manifestations. We highlight key clinical and pathological features of the different conditions and outline recent advances in our understanding of these entities. By emphasizing the dermatopathological characteristics of this spectrum of disorders we hope to hone the diagnostic accuracy of practitioners in the field.     

CT Densitometry and Morphology of Radiofrequency-Ablated Stage IA Non–Small Cell Lung Cancer: Results from the American College of Surgeons Oncology Group Z4033 (Alliance) Trial

PurposeTo evaluate tumor and ablation zone morphology and densitometry related to tumor recurrence in participants with Stage IA non–small cell lung cancer undergoing radiofrequency ablation in a prospective, multicenter trial.Materials and MethodsForty-five participants (median 76 years old; 25 women; 20 men) from 16 sites were followed for 2 years (December 2006 to November 2010) with computed tomography (CT) densitometry. Imaging findings before and after ablation were recorded, including maximum CT attenuation (in Hounsfield units) at precontrast and 45-, 90-, 180-, and 300-s postcontrast.ResultsEvery 1-cm increase in the largest axial diameter of the ablation zone at 3-months’ follow-up compared to the index tumor reduced the odds of 2-year recurrence by 52% (P = .02). A 1-cm difference performed the best (sensitivity, 0.56; specificity, 0.93; positive likelihood ratio of 8). CT densitometry precontrast and at 45 seconds showed significantly different enhancement patterns in a comparison among pretreated lung cancer (delta = +61.2 HU), tumor recurrence (delta = +57 HU), and treated tumor/ablation zone (delta [change in attenuation] = +16.9 HU), (P < .0001). Densitometry from 45 to 300 s was also different among pretreated tumor (delta = −6.8 HU), recurrence (delta = −11.2 HU), and treated tumor (delta = +12.1 HU; P = .01). Untreated and residual tumor demonstrated washout, whereas treated tumor demonstrated increased attenuation.ConclusionsAn ablation zone ≥1 cm larger than the initial tumor, based on 3-month follow-up imaging, is recommended to decrease odds of recurrence. CT densitometry can delineate tumor versus treatment zones.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.