The risk assessment model of fracture nonunion after intramedullary nailing for subtrochanteric femur fracture

To investigate the influencing factors of fracture nonunion after intramedullary nailing for subtrochanteric fractures and to construct a risk assessment model.Based on the multicenter retrospective analysis of 251 patients, all patients were divided into modeling group and verification group. In the modeling group, postoperative fracture nonunion rate, general data, fracture-related factors, surgical reduction-related factors, mechanical and biological factors were calculated, and the influencing factors of fracture nonunion were screened by univariate analysis. Logistic regression model was used for multifactor analysis to construct the risk assessment model. Based on the logistic regression model, the risk prediction model was constructed by drawing the Nomogram diagram. Through the verification group, the influencing factors were evaluated again, and the differentiation and calibration of the model were evaluated. The calibration degree was evaluated by Hosmer-Lemeshow test, goodness of fit test, and calibration curve. The discriminant degree was evaluated by the receiver operating characteristic curve.Fracture nonunion occurred in 34 of 149 patients in the modeling group. Among the 14 potential influencing factors, univariate analysis and logistic regression analysis showed that postoperative hip varus, intramedullary nail fixation failure, and reduction of fracture with large incision were the risk factors of fracture nonunion. The medial cortex fracture was seen reduced on X-Ray was a protective factor for fracture nonunion, and a regression equation was established. Based on the logistic regression model, the Nomogram diagram is drawn. Twenty-four cases of fracture nonunion occurred in the verification group. The area under the receiver operating characteristic curve was area under curve =0.883 > 0.7, indicating that there was a moderate differentiation to evaluate the occurrence of fracture nonunion after operation. The goodness of fit test: the Hosmers-Lemeshow test (X² = 2.921, P = .712 > .05) showed that the model had a good calibration.After intramedullary nailing of subtrochanteric fracture, hip varus, failure of intramedullary nail fixation and wide surgical dissection are the risk factors of fracture nonunion, and the postoperative reduction of medial cortex fracture is protective factor.National key research and development projects: 2016YFC0105806     

列线图模型在肺炎支原体感染患儿中塑型性支气管炎发生的预测价值

目的：探究列线图模型在肺炎支原体肺炎（MPP）患儿中塑型性支气管炎（PB）发生的预测价值。方法：以2018年6月至2022年6月兰州市西固区人民医院儿科收治的MPP患儿246例为研究对象进行回顾性分析,根据患儿是否发生PB分为PB组（n=66）和非PB组（n=180）。通过单因素分析及多因素Logistic回归分析筛选变量,构建MPP患儿PB发生的列线图预测模型,再分别通过校准曲线评估预测模型的一致性,受试者工作特征（ROC）曲线评估预测模型的准确性,决策曲线分析（DCA）评估预测模型的临床价值。结果：与非PB组比较,PB组患儿热程、体温热峰、中性粒细胞百分比、白细胞介素-6、乳酸脱氢酶、D-二聚体、C-反应蛋白、低氧血症比例、应用糖皮质激素比例、肺不张比例、胸腔积液比例显著升高（P<0.05）,血小板显著降低（P<0.05）。多因素Logistic回归结果示,热程、体温热峰、肺不张、胸腔积液、中性粒细胞百分比、血小板、白细胞介素-6、乳酸脱氢酶是MPP患儿PB发生的影响因素。校准曲线结果示,列线图模型预测PB的发生概率与实际发生率的一致性较好。ROC曲线结果示,列线图模型...     

乳腺癌新辅助化疗后腋窝淋巴结转移综合预测模型的建立

目的:建立乳腺癌新辅助化疗后淋巴结转移的综合预测模型,评估新辅助化疗后淋巴结转移情况,指导临床手术方案选择。方法:回顾分析2015年1月至2018年12月143例乳腺癌新辅助化疗患者的临床、病理及影像资料,并根据术后淋巴结病理分为转移组与无转移组。采用χ2/t检验对两组指标进行单因素分析;将P<0.05的指标纳入多因素Logistic回归分析。用多因素分析有统计学意义(P<0.05)的指标构建乳腺癌新辅助化疗后淋巴结转移综合预测模型的列线图,并应用受试者工作特征（receiver operation characteristic,ROC)曲线评价此模型的性能。结果:单因素分析表明化疗方案、化疗前淋巴结穿刺病理、术前查体、术前彩超、术前CT/MRI、RECIST分级对腋窝淋巴结转移有预测作用;多因素分析表明,化疗前淋巴结穿刺病理、术前彩超、RECIST分级是新辅助化疗后腋窝淋巴结转移的独立预测因素。乳腺癌新辅助化疗后淋巴结转移的预测模型的曲线下面积为0.785,特异度为85.4%,敏感度为59.8%。结论:乳腺癌新辅助化疗后淋巴结转移的综合预测模型对腋窝淋巴结有较好的预测能力,可为选择合适的手术方式提供临床指导。     

Comprehensive analysis of the relationship between competitive endogenous RNA (ceRNA) networks and tumor infiltrating-cells in hepatocellular carcinoma

BackgroundThe innovation of immune checkpoint blockade (ICB) represents a promising shift in the treatment of advanced hepatocellular carcinoma (HCC). However, response to ICB has varied largely due to the high tumor heterogeneity and complex tumor microenvironment (TME). The competitive endogenous RNA (ceRNA) network also plays an important role in tumor occurrence and progression, but its relation with tumor-infiltrating immune cells (TICs) remains largely unexplored in HCC. The overriding objective of our study was thus to construct a prognosis-related risk model and to further evaluate the relationship between ceRNA networks and TICs.MethodsDifferentially expressed gene (DEG) analysis was performed to identify the differentially expressed RNAs. Lasso and multivariable Cox regression analyses were used to construct risk models, which were assessed by the area under the receiver operating characteristic curve (AUC of ROC) and Kaplan-Meier (K-M) curves. Then, a single-sample gene set enrichment analysis (ssGSEA) algorithm was adopted to dissect the TICs in HCC samples. Nomograms were constructed and calibration curves were used to verify the discrimination and accuracy of the nomograms. Finally, integration analysis was performed to validate the correlation of ceRNA and TICs.ResultsIn the study, 7 differentially expressed RNAs [5 messenger RNA s (mRNAs) and 2 micro RNAs (miRNAs)] were incorporated to construct a ceRNA risk model. The AUC of the 1-, 3-, and 5-year overall survival (OS) were 0.784, 0.685, and 0.691 respectively. Likewise, 7 types TICs were in the TICs signature model and the AUC of the 1-, 3-, and 5-year OS were 0.706, 0.731, and 0.721 respectively. The integration analysis showed that 7 pairs of mRNA-TICs and 1 pair of miRNA-TICs had a close relation (all correlation coefficients >0.2, P<0.001).ConclusionsThrough constructing two risk models based on ceRNA network and TICs, we identified the hub RNAs and key TICs in the progression and prognosis of HCC, and further explored the relationship between ceRNA and TME. Importantly, targeting these hub RNAs may facilitate the remodeling of the TME and be a potential therapeutic alternative to enhancing the response to ICB, thus improving the prognosis of HCC patients.     

体质量指数对前列腺癌合并心血管疾病的老年患者预后的影响及列线图构建

目的 探讨体质量指数(BMI)对前列腺癌合并心血管疾病的老年患者预后的影响,构建并验证患者1年内心血管病再入院的预测列线图。方法 回顾性分析2019年5月至2021年5月于山西医科大学第一医院初诊为前列腺癌伴心血管疾病的237例患者的临床资料。根据中国肥胖工作组(WGOC)推荐的BMI标准将患者分为高BMI组(110例)和低BMI组(127例),比较两组患者基线资料、实验室和影像学检查等临床资料。主要终点事件为1年内心血管病再入院,次要终点为1年内全因死亡。采用SPSS 26.0和R Studio(4.1.2版本)进行数据分析。根据数据类型,分别采用t检验、Mann-Whitney U检验或χ²检验进行组间比较。采用Kaplan-Meier法绘制生存曲线,通过多因素Cox回归模型分析患者预后的影响因素并建立患者预后预测列线图模型。结果 118例患者CVD再入院,其中低BMI组71例(55.9%),高BMI组47例(42.7%);全因死亡4例,其中低BMI组3例(2.4%),高BMI组1例(0.9%)。Kaplan-Meier生存分析显示,低BMI组患者首次CVD再...     

上气道形态学参数联合临床特征列线图模型诊断儿童阻塞性睡眠呼吸暂停

目的 观察以上气道形态学参数联合临床特征建立的列线图模型诊断儿童阻塞性睡眠呼吸暂停(OSA)的效能。方法 收集355例接受睡眠监测及鼻咽部CT检查的≤10岁儿童的影像学及临床资料,按7∶3比例将其随机归入训练集(n=248)或验证集(n=107);其中237例确诊OSA。以训练集中的OSA为结局变量,采用单因素及多因素logistic回归分析筛选OSA影响因素,建立OSA列线图模型;以受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)评价该模型诊断儿童OSA的效能。结果 单因素及多因素logistic回归分析显示,上气道最狭窄处左右径、腺样体形态和睡眠打鼾病程是OSA的独立影响因素(P均<0.05)。以上述3个变量构建OSA列线图模型,ROC曲线显示其诊断OSA的曲线下面积(AUC)为0.93[95%CI(0.89,0.96)]。以Bootstrap法行内部验证,校准曲线的平均绝对误差为0.01;于验证集进行外部验证,其AUC为0.85[95%CI(0.78,0.93)],校准曲线的平均绝对误差为0.02。DCA示训练集和验证集的净收益率均高于无效线。结论 基于上气道...