Comparison study of patient demographics and patient-related risk factors for peri-prosthetic joint infections following primary total shoulder arthroplasty

BackgroundWhile studies have demonstrated favorable outcomes in utilization of primary total shoulder arthroplasty (TSA) for the treatment of glenohumeral osteoarthritis (OA), adverse events such as infections can still occur. Periprosthetic joint infections (PJIs) are associated with worse outcomes and patient morbidity. The purpose of this study was to: (1) compare patient demographics amongst TSA patients with and without PJIs following primary TSA; and (2) identify patient-related risk factors for PJIs following primary TSA.MethodsPatients undergoing primary TSA for the treatment of glenohumeral OA were identified using the Mariner administrative claims database by CPT code 23,472. Laterality modifiers were utilized to ensure PJIs were developing in the correct laterality as those patients undergoing primary TSA. Inclusion for the study group consisted of patients who developed PJIs within 2-years after the index procedure, whereas patients who did not develop PJIs served as the comparison cohort. Primary outcomes analyzed included patient demographics and patient-related risk factors for PJIs following primary TSA. A stepwise backwards elimination multivariate binomial logistic regression analyses was performed to determine the odds (OR) of PJIs in patients undergoing primary TSA. A P value less than .05 was considered statistically significant.ResultsThe query yielded 15,396 patients who underwent primary TSA for glenohumeral OA, of which 191 patients developed PJIs and 15,205 did not develop PJIs. The study found statistically significant differences amongst patients who did and did not develop PJIs following primary TSA with respect to age, sex, and presence of comorbid conditions. Risk factors associated with developing PJIs following primary TSA included: pathologic weight loss (OR: 2.06, P < .0001), obesity (OR: 1.56, P = .0001), male sex (OR: 1.52, P = .007), and peripheral vascular disease (OR: 1.46, P = .022).ConclusionAs the number of primary TSAs for the treatment of glenohumeral OA increase worldwide, identifying modifiable risk-factors to reduce the incidence of infection is critical. The study found various modifiable and non-modifiable risk factors associated with developing PJIs following primary TSA. This study is valuable to orthopedists in order to identify and risk-stratify patients with regard to PJI in the setting of primary TSA for OA.Level of EvidenceLevel III; Case-Control Study     

补肾活血方对血管性痴呆大鼠海马神经细胞自噬的影响＊

目的 探究补肾活血方对血管性痴呆（Vascular Dementia， VD）大鼠模型自噬的影响。方法 52周龄SD雄性大鼠50只，随机分为假手术组（Sham组）、模型组（VD组）、模型+补肾活血方组（BSHX组）、模型+雷帕霉素组（Rap组）和模型+3-甲基腺嘌呤组（3-MA组），每组10只大鼠。除Sham组外其余各组采用两血管阻断法（2-VO）建立VD模型。BSHX组中药灌胃治疗28天；自噬干预组于造模前30 min侧脑室给药。运用Morris水迷宫测试各组大鼠的学习记忆能力；通过尼氏染色和透射电子显微镜（Transmission electron microscope，TEM）观察大鼠海马区病理形态及自噬变化；采用蛋白免疫印迹（Western blot）法和反转录实时荧光定量PCR（RT-qPCR）检测大鼠海马Beclin-1、P62以及微管相关蛋白1轻链3（LC3）蛋白及mRNA表达情况。结果 与VD组比较，BSHX组大鼠学习记忆能力显著提升（P<0.05），镜下观察BSHX组和3-MA组的细胞形态及数量均有改善，自噬小体鲜见，Beclin-1以及LC3蛋白和mRNA表达水平显著降低（P<0.05），P62蛋白和mRNA表达水平明显升高（P<0.05）结论 补肾活血方可以降低VD大鼠海马区Beclin-1和LC3蛋白及mRNA的表达，提高P62的表达，通过抑制自噬的发生，减轻对神经细胞的损伤，改善学习记忆能力。     

健脾消癌方通过PI3K/Akt信号通路抑制结肠癌血管生成的研究＊

目的 观察结肠癌HCT116细胞健脾消癌方的条件培养液对HUVEC细胞管腔形成的影响，从PI3K/Akt生物轴调控角度探讨其作用机制。方法 培养HCT116细胞，细胞设3组：对照组，健脾消癌方组（加入15%健脾消癌方含药血清）及人参皂苷Rg3组；制备HCT116细胞健脾消癌方条件培养液（分组及制备方法见实验方法），用条件培养液干预HUVEC（脐静脉内皮细胞，Human Umbilical Vein Endothelial Cells），Matrigel基质胶法检测HCT116细胞健脾消癌方条件培养液对HUVEC小管形成的影响。随后采用蛋白免疫印迹法（Western blot）检测各组HCT116细胞磷脂酰肌醇3-激酶（PI3K）、蛋白激酶B（Akt）、p-Akt、VEGF（血管内皮生长因子，Vascular endothelial growth factor）蛋白表达。最后在结肠癌HCT116荷瘤小鼠中验证健脾消癌方对肿瘤生长速度的影响，并经瘤组织VEGF蛋白表达、CD31免疫组化染色检测肿瘤内血管生成情况。结果 模型组HUVEC细胞管腔形成较空白血清组显著增加（P<0.05）；健脾消癌方组及人参皂苷Rg3组较模型组HUVEC细胞管腔形成显著减少（P<0.01）。p-Akt和VEGF蛋白表达水平模型组高于空白血清组（P<0.05），健脾消癌方组及人参皂苷Rg3组显著低于模型组（P<0.01）；PI3K、Akt蛋白表达量组间差异无统计学意义。与对照组比较，模型组荷瘤小鼠肿瘤体积显著性增大，瘤组织内VEGF表达、CD31阳性面积显著性增加，差异有统计学意义（P<0.05）；与模型组比较，健脾消癌方组及人参皂苷Rg3组荷瘤小鼠肿瘤体积显著减小，瘤组织内VEGF表达、CD31阳性面积降低，差异有统计学意义（P<0.05）。结论 健脾消癌方可抑制肿瘤的血管生成和生长，其作用机制可能与PI3K/Akt生物轴调控VEGF表达有关。     

香萱益神方对血管性痴呆模型大鼠神经元凋亡机制研究

目的:探讨香萱益神方治疗血管性痴呆(VD)模型大鼠认知功能作用及其对神经元凋亡机制的研究。方法:两血管阻断法建立VD大鼠模型,给予中药方香萱益神方灌胃治疗6周,分别于造模后、中药喂养6周后进行Morris水迷宫行为学检测,测试大鼠认知行为能力改变,行为学测试结束后,检测VD模型大鼠海马中海马组织脑源性神经营养因子(BDNF)表达水平的变化。结果:香萱益神方治疗6周后,血管性痴呆大鼠模型学习记忆能力得到改善,上调脑内海马组织神经营养因子水平,海马神经元凋亡率下降。结论:香萱益神方是治疗血管性痴呆的有效方剂,可以有效改善VD大鼠模型认知行为功能的障碍情况,起到减少海马神经元细胞凋亡,诱导海马神经元细胞修复的作用。香萱益神方可能是通过激活BDNF相关通路,起到保护海马神经元的作用。     

Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma

ObjectiveTo evaluate the performance of a deep learning (DL)-based radiomics strategy on contrast-enhanced computed tomography (CT) to predict microvascular invasion (MVI) status and clinical outcomes, recurrence-free survival (RFS) and overall survival (OS) in patients with early stage hepatocellular carcinoma (HCC) receiving surgical resection.MethodsAll 283 eligible patients were included retrospectively between January 2008 and December 2015, and assigned into the training cohort (n = 198) and the testing cohort (n = 85). We extracted radiomics features via handcrafted radiomics analysis manually and DL analysis of pretrained convolutional neural networks via transfer learning automatically. Support vector machine was adopted as the classifier. A clinical-radiological model for MVI status integrated significant clinical features and the radiological signature generated from the radiological model with the optimal area under the receiver operating characteristics curve (AUC) in the testing cohort. Otherwise, DL-based prognostic models were constructed in prediction of recurrence and mortality via Cox proportional hazard analysis.ResultsThe clinical-radiological model for MVI represented an AUC of 0.909, accuracy of 96.47%, sensitivity of 90.91%, specificity of 97.30%, positive predictive value of 83.33%, and negative predictive value of 98.63% in the testing cohort. The clinical-radiological models for identification of RFS and OS outperformed prediction performance of the clinical model or the DL signature alone. The DL-based integrated model for prognostication showed great predictive value with significant classification and discrimination abilities after validation.ConclusionsThe integrated DL-based radiomics models achieved accurate preoperative prediction of MVI status, and might facilitate predicting tumor recurrence and mortality in order to optimize clinical decisions for patients with early stage HCC.