股骨转子间骨折的稳定性重建概念演化与研究进展

目的总结近年来股骨转子间骨折在稳定性重建方面的概念演化与研究进展。方法查阅国内外相关文献并结合自身经验，从股骨转子间骨折的解剖特点、稳定型骨折与不稳定型骨折分类、稳定性复位与不稳定性复位、术中加压初始稳定与术后滑动二次稳定、内固定术后稳定性评估、早期下地站立负重等方面进行总结分析。结果股骨转子间骨折发生于股骨颈干骺端转换区，具有天然的内翻不稳定倾向。骨折复位质量是影响后续内固定物安放的最重要前提因素。判断骨折复位质量有对线和对位两方面，对线采用 Garden 指数；在对位方面，随着皮质对位理念（正性、中性、负性）的提出，特别强调前内侧皮质的相互砥住支撑（解剖、正性），是获得骨折稳定性复位的关键，而不再强调后内侧小转子骨块的作用。术后影像学的稳定性评分为早期下地站立负重提供了量化指标。但术中的前内侧皮质支撑复位，在术后头颈骨块滑动获得二次稳定的过程中，仍有皮质对位丢失现象，需研究其危险因素和防范措施。结论股骨转子间骨折在取得良好对线的基础上，只要获得了前内侧皮质的相互砥住和支撑，并用内固定器械维持住，就获得了术后稳定性。术后稳定性评分优良者，可以安全地早期下地负重、站立行走活动。     

Resistin is elevated in cystic fibrosis sputum and correlates negatively with lung function

Background

Resistin is an immunometabolic mediator that is elevated in several inflammatory disorders. A ligand for Toll-like receptor 4, resistin modulates the recruitment and activation of myeloid cells, notably neutrophils. Neutrophils are major drivers of cystic fibrosis (CF) lung disease, in part due to the release of human neutrophil elastase- and myeloperoxidase-rich primary granules, leading to tissue damage. Here we assessed the relationship of resistin to CF lung disease.

How structural and functional MRI can inform dual-site tACS parameters: A case study in a clinical population and its pragmatic implications

BackgroundAbnormalities in frontoparietal network (FPN) were observed in many neuropsychiatric diseases including substance use disorders. A growing number of studies are using dual-site-tACS with frontoparietal synchronization to engage this network. However, a computational pathway to inform and optimize parameter space for frontoparietal synchronization is still lacking. In this case study, in a group of participants with methamphetamine use disorders, we proposed a computational pathway to extract optimal electrode montage while accounting for stimulation intensity using structural and functional MRI.MethodsSixty methamphetamine users completed an fMRI drug cue-reactivity task. Four main steps were taken to define electrode montage and adjust stimulation intensity using 4x1 high-definition (HD) electrodes for a dual-site-tACS; (1) Frontal seed was defined based on the maximum electric fields (EF) predicted by simulation of HD montage over DLPFC (F3/F4 in EEG 10–10), (2) frontal seed-to-whole brain context-dependent correlation was calculated to determine connected regions to frontal seeds, (3) center of connected cluster in parietal cortex was selected as a location for placing the second set of HD electrodes to shape the informed montage, (4) individualized head models were used to determine optimal stimulation intensity considering underlying brain structure. The informed montage was compared to montages with large electrodes and classic frontoparietal HD montages (F3-P3/F4-P4) in terms of tACS-induced EF and ROI-to-ROI task-based/resting-state connectivity.ResultsCompared to the large electrodes, HD frontoparietal montages allow for a finer control of the spatial peak fields in the main nodes of the FPN at the cost of lower maximum EF (large-pad/HD: max EF[V/m] = 0.37/0.11, number of cortical sub-regions that EF exceeds 50% of the max = 77/13). For defining stimulation targets based on EF patterns, using group-level head models compared to a single standard head model results in comparable but significantly different seed locations (6.43 mm Euclidean distance between the locations of the frontal maximum EF in standard-space). As expected, significant task-based/resting-state connections were only found between frontal-parietal locations in the informed montage. Cue-induced craving score was correlated with frontoparietal connectivity only in the informed montage (r = ?0.24). Stimulation intensity in the informed montage, and not in the classic HD montage, needs 40% reduction in the parietal site to reduce the disparity in EF between stimulation sites.ConclusionThis study provides some empirical insights to montage and dose selection in dual-site-tACS using individual brain structures and functions and proposes a computational pathway to use head models and functional MRI to define (1) optimum electrode montage for targeting FPN in a context of interest (drug-cue-reactivity) and (2) proper transcranial stimulation intensity.     

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%.     

单纯 Ilizarov 环形外固定技术治疗合并骨筋膜室综合征的胫骨平台骨折

目的探讨单纯 Ilizarov 环形外固定技术治疗合并骨筋膜室综合征的胫骨平台骨折的疗效。方法2013 年 9 月—2017 年 3 月，收治 30 例合并骨筋膜室综合征的胫骨平台骨折患者，采用单纯 Ilizarov 环形外固定技术治疗。男 23 例，女 7 例；年龄 23～43 岁，平均 34.4 岁。致伤原因：交通事故伤 12 例，高处坠落伤 4 例，摔伤 8 例，重物砸伤 6 例。受伤至入院时间 1～12 h，平均 4.8 h。骨折 Schatzker 分型：Ⅱ型 1 例、Ⅲ型 3 例、Ⅳ型 10 例、Ⅴ型 7 例、Ⅵ型 9 例。30 例均因骨筋膜室综合征行切开减压；切开减压至手术时间为 10～15 d，平均 12.5 d。治疗后采用膝关节学会评分系统（KSS）及 Ilizarov 方法研究与应用协会（ASAMI）协议评价膝关节功能。结果手术时间 110～155 min，平均 123.1 min；术中出血量 100～500 mL，平均 245 mL；术后住院时间 3～5 d，平均 3.8 d。患者均获随访，随访时间 20～24 周，平均 22.7 周。除 2 例患者出现针道感染征象外，无其他并发症发生。X 线片复查显示骨折均愈合，愈合时间 10～20 周，平均 14.6 周。末次随访时，膝关节 KSS 临床评分总分为 70～95 分，平均 87.5 分；功能评分总分为 70～90 分，平均 79.0 分。参照 ASAMI 协议评价获优 24 例、良 3 例、可 2 例、差 1 例。结论对于合并骨筋膜室综合征的胫骨平台骨折，单纯 Ilizarov 环形外固定技术治疗后患者关节功能可以基本恢复且并发症少，是一项相对安全、有效的治疗方法。