Characteristics of Deep Venous Thrombosis in Isolated Lower Extremity Fractures and Unsolved Problems in Guidelines: A Review of Recent Literature

Deep venous thrombosis (DVT) has been characterized by a disorder of venous return caused by abnormal blood clotting in deep veins. It often occurs in the lower limbs and is a common complication in orthopaedics. Therefore, relevant professional organizations domestic and overseas had formulated and constantly updated relevant guidelines to prevent the occurrence of DVT. According to the management strategy of the guidelines, the incidence of DVT can be significantly reduced. However, due to the variety of fractures types, the guidelines cannot expound precautions and characteristics of DVT for all fracture types at present, and there are other related unresolved problems. For example, there is still a lack of consistent optimal strategies for the management of DVT following isolated lower extremity fractures with a higher incidence. The best anticoagulant strategies for patients with upper limb fractures, pediatric fractures, and those combined with other injuries are rarely described in orthopaedic guidelines, but such fractures are common in clinical orthopaedics. The long‐term complications after DVT, such as post‐thrombotic syndrome, are not well‐understood. In the absence of clear guidance, orthopaedic surgeons often resort to empiric anticoagulation or conservative treatment, so the prevention effects of DVT are inconsistent. The purpose of this review is to summarize the characteristics of DVT events after isolated lower extremity fractures and to discuss the unsolved issues in the guidelines by reviewing the previous literature and tracing the history of DVT discovery, to provide more scientific and comprehensive recommendations for the prediction and prevention of DVT.     

昆山市2006~2012年甲状腺癌发病率趋势分析

[目的]分析昆山市甲状腺癌发病趋势。[方法]甲状腺癌新发病例来源于昆山市肿瘤登记报告系统,计算甲状腺癌发病率、年度变化百分比（APC）等指标。[结果]2006～2012年昆山市甲状腺癌中标发病率由2006年的2.76/10万上升至2012年的12.91/10万,年度变化百分比（APC）为29.71%（P〈0.0001）,其中女性甲状腺癌中标发病率由2006年的5.01/10万上升至2012年的21.39/10万,APC为27.39%（P〈0.0001）。灰色模型预测2013～2015年甲状腺癌发病率呈上升趋势。[结论]昆山市甲状腺癌发病率呈上升趋势,需加强肿瘤防治工作。     

Daily resting-state intracranial EEG connectivity for seizure risk forecasts

Forecasting seizure risk aims to detect proictal states in which seizures would be more likely to occur. Classical seizure prediction models are trained over long-term electroencephalographic (EEG) recordings to detect specific preictal changes for each seizure, independently of those induced by shifts in states of vigilance. A daily single measure—during a vigilance-controlled period—to estimate the risk of upcoming seizure(s) would be more convenient. Here, we evaluated whether intracranial EEG connectivity (phase-locking value), estimated from daily vigilance-controlled resting-state recordings, could allow distinguishing interictal (no seizure) from preictal (seizure within the next 24 h) states. We also assessed its relevance for daily forecasts of seizure risk using machine learning models. Connectivity in the theta band was found to provide the best prediction performances (area under the curve ≥ .7 in 80% of patients), with accurate daily and prospective probabilistic forecasts (mean Brier score and Brier skill score of .13 and .72, respectively). More efficient ambulatory clinical application could be considered using mobile EEG or chronic implanted devices.     

2012—2021 监测的季节特征分析 年甘肃省急性弛缓性麻痹病例

摘 要：目的：分析甘肃省急性弛缓性麻痹病例的季节分布特征，进一步构建时间序列模型，为甘肃省急性弛缓性麻痹 病例的早期发现提供参考依据。方法：通过“中国急性弛缓性麻痹病例监测信息管理系统”收集甘肃省 2012—2021年急性 弛缓性麻痹病例信息，采用回顾性流行病学方法对急性弛缓性麻痹病例报告发病数进行描述，使用聚类和时间序列模型对病 例进行时间序列分析和预测。结果：2012—2021年甘肃省急性弛缓性麻痹病例年发病数变化趋势较为平稳，月发病数从2月 开始出现大幅上升，6月和10月达到高峰后缓慢下降；以每月发病例数为单位可将月份聚为3类，第1类为4月、5月，第2 类为1月、2月，第3类为其他月份；预测出未来1年的发病例数与前10年的发病例数基本一致。结论：甘肃省急性弛缓性麻 痹病例发病呈现夏秋季高发，季节性差分自回归滑动平均模型较好拟合了2012—2021年每月发病例数，并预测2022年各月 发病例数，可以为急性弛缓性麻痹病例的监测及防控提供科学依据。     

基于机器学习组合模型预测结直肠腺癌生存

目的 基于机器学习模型（machine learning,ML）和logistic回归构建预测结直肠腺癌5年生存结局的组合模型。方法 选取SEER数据库中12 980名患者，采用传统logistic回归分析影响患者5年存活的相关因素。使用相关因素构建以极限梯度提升、自适应提升、支持向量机、随机森林、回归决策树的预测概率为自变量，分别纳入极限梯度提升、自适应提升和logistic回归做最终预测的组合模型，比较各组合模型5年结直肠腺癌生存预测效果。结果 年龄、手术、化疗、分化程度、T分期、N分期、M分期、CEA状况和婚姻，9个因素影响结直肠腺癌患者5年生存。组合模型logistic+Adaboost+RF+XGboost，内部测试集AUC、准确率、F1分数分别为0.861、0.801、0.832。外部验证集AUC、准确率、F1分数分别为0.833、0.806、0.869。组合模型效能优于单一模型。结论 机器学习组合模型更具有优势，可以有效预测结直肠腺癌5年生存结局，辅助临床工作者制定诊疗方案和优化癌症防治措施。     

妊娠糖尿病患者血清C肽对妊娠不良事件和胎儿生长发育的预测价值

目的 探讨妊娠糖尿病（GDM）患者血清C肽对妊娠不良事件和胎儿生长发育的预测价值。方法 回顾性分析2021年6月—2022年12月在宣城市人民医院分娩的98例GDM患者的临床资料，统计GDM患者临床妊娠结局和胎儿生长发育情况。根据GDM患者妊娠结局分为结局不良组和结局良好组；根据胎儿生长发育情况分为发育异常组和发育正常组。比较结局不良组、结局良好组，发育异常组、发育正常组的临床资料及血清C肽水平。采用多因素Logistic逐步回归模型分析影响GDM患者妊娠结局和胎儿生长发育的相关因素。绘制受试者工作特征（ROC）曲线分析血清C肽对GDM患者妊娠不良事件和胎儿生长发育的预测效能。结果 98例GDM患者临床妊娠结局不良共37例、妊娠结局良好61例，胎儿发育异常22例、发育正常76例。结局不良组的年龄、孕次、空腹血糖（FPG）、糖化血红蛋白（HbA1c）及C肽水平高于结局良好组（P<0.05）。发育异常组FPG、HbA1c及C肽水平高于发育正常组（P<0.05）。多因素Logistic逐步回归分析结果显示：年龄[■=2.927(95%CI:1.056,8.111）]、HbA1c[...     

Prediction of diabetic foot amputation using newly revised DIRECT coding system: Comparison of accuracy with that of five existing classification systems

Diabetes mellitus (DM) causes various complications over time, one such complication is diabetic foot ulcers (DFU), which are challenging to treat and can lead to amputation. Additionally, a system for accurate prediction of amputation has yet to be developed. In total, 131 patients were included in the study after retrospectively collecting data from 2016 to 2020 about DFU. The collected data were used for comparison of the accuracy between five existing classification systems and the newly revised DIRECT coding system, and investigation of risk factors for lower extremity amputation (LEA). The existing five classification systems and DIRECT system can effectively predict LEA. The DIRECT3 system has three elements, C-reactive protein (CRP), ulcer history (UH), and hypertension (HTN) in addition to those of the DIRECT system. It had a high predictive value and accuracy similar to that of Wagner and University of Texas (UT) on depth among the five classification systems. Among the statistically significant risk factors, duration of DM and HTN, haemoglobin (Hb), CRP, and UH showed an association with LEA. The DIRECT coding system is effective for predicting LEA and explaining appropriate treatment methods for DFU, and is widely applicable because of its user accessibility and convenience.