目的 汇总分析肝硬化患者消化道出血风险预测模型，为今后模型的建立和优化提供参考。方法   系统检索中国知网、维普、PubMed数据库在2025年4月22日前公开发表的所有肝硬化患者消化道出血风险预测模型，按纳入标准筛选文献，对最终纳入文章分析摘录并系统汇总，包括模型特征、危险因素及模型预测评估效果等信息。结果   共检索3 603篇预测模型相关研究论文，最终纳入30篇，其中中国27篇、韩国1篇、印度1篇、埃及1篇。22项研究收集了肝硬化病因，其中病毒性肝病最多（72.94%，2 922/4 006），药物性肝病及非酒精性脂肪性肝病最少（均为0.02%，1/4 006）。在研究类型上，有28篇单中心研究，2篇为多中心研究，其中有12个模型未进行验证，只有1个模型进行了外部验证，其余模型只进行了内部验证，曲线下面积（AUC）范围0.680~0.994。根据模型纳入因素特点，分为血常规指标、凝血指标、生化指标、影像学指标、复合指标、其他指标共6种，其中纳入因素最多为影像学指标，最少为凝血指标。在纳入危险因素中，第1位为门静脉直径，第2位为血小板计数，第3位为血红蛋白水平及脾脏硬度，所有因素中与脾脏相关的指标最多。结论   肝硬化患者消化道出血风险预测模型研究质量有待提升，影像学指标应用最广，脾脏相关指标重要性突出，门静脉直径、血小板计数、血红蛋白水平及脾脏硬度为最常用的危险预测因素。

       Objective  To  summarize and analyze the  prediction models for gastrointestinal  bleeding  risk in  patients with cirrhosis，providing references for the establishment and optimization of future models．Methods  A systematic search was conducted in CNKI，VIP，and PubMed for all published prediction models for gastrointestinal bleeding risk in patients with cirrhosis before April 22，2025．Articles were screened according to the inclusion criteria，and the finally included articles were analyzed and summarized，including model characteristics，risk factors，and model prediction evaluation effects．Results  A total of 3 603 related research papers on prediction models were initially retrieved，and 30 were finally included，with 27 from China，one from South Korea，one from India，and one from Egypt．Among the 22 studies that collected the etiology of cirrhosis，viral hepatitis was the most common（72.94%，2 922/4 006），while drug-induced liver disease and non-alcoholic fatty liver disease were the least common（0.02%，1/4 006）．In terms of study type，28 were single-center studies and two were multicenter studies．Among them，12 models were not validated，only one model was externally validated，and the rest were only internally validated，with an area under the curve range of 0.680-0.994．According to the characteristics of the factors included in the models，they were divided into six types of indicators：blood routine，coagulation，biochemistry，imaging，composite，and others，among which imaging indicators were the most common and coagulation indicators were the least．In the included risk factors，the first was portal vein diameter，the second was platelets count，and the third was hemoglobin level and spleen stiffness，with the most factors related to the spleen．Conclusions  The quality of studies on prediction models for gastrointestinal bleeding risk in cirrhosis patients needs to be improved．Imaging indicators are the most widely used，and spleen-related indicators are of prominent importance，with portal vein diameter，platelets count，hemoglobin level，and spleen stiffness being the most commonly used risk prediction factors．

      目的 分析儿童大环内酯类耐药重症肺炎支原体肺炎（SMPP）的危险因素,构建列线图预测模型。 方法 回顾性收集2023年1月—2024年9月在广州医科大学附属番禺中心医院儿科住院治疗的1 121例大环内酯类耐药肺炎支原体肺炎患儿入院初期的临床资料。按7∶3比例将患儿资料随机分为训练集（784例）和验证集（337例）。采用R4.4.1软件使用10重交叉验证最小绝对收缩与选择算法（LASSO）回归分析进行单因素变量筛选,采用Logistics回归分析建立预测模型, 绘制可视化列线图。使用受试者操作特征曲线（ROC）, 校准曲线、Hosmer-Lemeshow（HL）检验及临床决策曲线（DCA）分别评估模型的区分度、校准度和临床使用价值。 结果 在训练集中, LASSO回归结合Logistics回归分析结果显示,院前发热时间>5.5 d、谷丙转氨酶>14.5 U/L、乳酸脱氢酶>287.5 U/L、C反应蛋白>18.65 mg/L、肺实变、合并病毒感染是大环内酯类耐药SMPP发生的危险因素（P<0.05）, 根据上述危险因素构建列线图预测模型。训练集和验证集ROC曲线下面积分别为0.847和0.822; 校准曲线和HL检验显示模型具有良好的校准度; DCA显示预测模型在风险阈值为0.05~0.95时预测性能最优。 结论 院前发热时间、谷丙转氨酶、乳酸脱氢酶、C反应蛋白、肺实变、合并病毒感染是大环内酯类耐药SMPP发生的影响因素, 基于以上因素构建的列线图模型具有较好的预测效能, 有利于早期识别耐药重症病例, 及早采取有效干预,改善患者预后。

      Objective To explore the risk factors and to construct a nomogram prediction model for severe macrolide-resistant Mycoplasma pneumoniae pneumonia（MPP）in children．Methods The clinical data during the initial admission period of 1 121 children with macrolide-resistant MPP who were hospitalized in the Department of Pediatrics of the Affiliated Panyu Central Hospital of Guangzhou Medical University from January 2023 to September 2024 were retrospectively collected．The children data were randomly divided into a training set（n=784）and a validation set（n=337）at a ratio of 7∶3．With R language software（version 4.4.1）, least absolute shrinkage and selection operator（LASSO）regression analysis with tenfold cross-validation was used to screen risk factors, Logistics regression analysis was used to establish prediction model, and a visualization of the risk variables was created using a nomogram．The receiver operating characteristic（ROC）curves, calibration curves, Hosmer-Lemeshow（HL）test and clinical decision curve analysis（DCA）were used to evaluate the discrimination, calibration and clinical application value of the model．Results In the training set, LASSO regression analysis combined with Logistics regression analysis showed that prehospital fever duration > 5.5 days, alanine aminotransferase level> 14.5 U/L, lactate dehydrogenase level> 287.5 U/L, C-reactive protein > 18.65 mg/L, lung consolidation, and co-infection with virus were risk factors for severe macrolide-resistant MPP（P<0.05）．A nomogram prediction model was constructed based on the above risk factors．The area under the ROC curves of the training set and the validation set were 0.847 and 0.822, respectively．The calibration curves and HL test showed that the model had good calibration． The DCA curves showed that the prediction model had the best prediction performance when the risk threshold was between 0.05-0.95．Conclusions Prehospital fever duration, alanine aminotransferase level, lactate dehydrogenase level, C-reactive protein level, lung consolidation and co-infection with virus were risk factors for prediction of severe macrolide-resistant MPP．The nomogram model based on the above factors had a good prediction efficiency, which was conducive to early identification of severe cases with macrolide-resistant, and taking early effective interventions to improve the prognosis．

      目的   残余胆固醇（RC）是反映动脉粥样硬化性血脂异常的重要指标，其在糖尿病合并冠心病患者中的临床意义尚不明确。本研究旨在探讨RC水平对糖尿病合并冠心病患者心力衰竭风险的预测价值，并分析其相关性。方法   本研究为回顾性横断面研究，纳入2021年1月—2024年1月期间在鹤壁市人民医院接受诊治的292例糖尿病合并冠心病患者。根据是否存在心力衰竭分为心力衰竭组（128例）和无心力衰竭组（164例）。对基线特征进行比较，采用单因素和多因素Logistic回归分析RC与心力衰竭的相关性。同时，通过限制性立方样条（RCS）分析探讨RC与心力衰竭风险的线性关系，并通过受试者操作特征（ROC）曲线和曲线下面积（AUC）评估RC的预测价值。结果   心力衰竭组患者的男性比例、高血压患病率、RC水平等高于无心力衰竭组，而估算肾小球滤过率水平显著降低（P＜0.05）。单因素分析显示，RC＞0.7 mmol/L显著增加心力衰竭风险（OR=1.854，95%CI：1.161~2.960，P=0.010）。多因素Logistic回归分析中，全调整模型结果显示，RC作为分类变量时，RC＞0.7 mmol/L的患者心力衰竭风险显著增加1.891倍（OR=1.891，95%CI：1.047~3.415，P=0.035）；作为连续变量时，RC每增加1单位，心力衰竭风险增加2.464倍（OR=2.464，95%CI：1.495~4.064，P＜0.001）；Log₁₀RC的风险比为6.411（95%CI：2.246~18.302，P=0.001）；标化RC的风险比为1.687（95%CI：1.262~2.255，P＜0.001）。限制性立方样条分析表明RC与心力衰竭风险呈线性正相关，ROC分析显示RC预测心力衰竭的AUC为0.621（95%CI：0.555~0.687，P＜0.001）。结论  RC水平与糖尿病合并冠心病患者心力衰竭风险显著相关，且呈线性正相关。RC具有一定的预测价值，可作为该人群心力衰竭风险评估的潜在指标。

       Objective  Residual cholesterol（RC）is  an important marker  reflecting  dyslipidemia  associated with atherosclerosis．Its clinical significance in patients with diabetes and coronary heart disease（CHD）remains unclear．To explore the predictive value of RC level for the risk of heart failure（HF）in patients with diabetes and CHD and analyze their association．Methods  This retrospective cross-sectional study included 292 patients with diabetes and CHD who were treated at Hebi People’s Hospital between January 2021 and January 2024．Patients were divided into the HF group（128 cases）and the non-HF group（164 cases）based on the presence of HF．Baseline characteristics were compared，and univariate and multivariate Logistic  regression analyses were performed to assess the association between RC and HF．Additionally，restricted cubic spline（RCS）analysis was used to explore the linear relationship between RC and HF risk，and the predictive value of RC was evaluated using receiveroperating characteristic（ROC）curves and the area under the curve（AUC）．Results  The HF group had significantly higher proportions of males，hypertension prevalence and RC levels，while estimated glomerular filtration rate were significantly lower compared to the non-HF group（P＜0.05）．Univariate analysis showed that RC＞0.7 mmol/L significantly increased the risk of HF（OR=1.854，95%CI：1.161–2.960，P=0.010）．In the fully adjusted multivariate Logistic regression model，RC（RC＞0.7 mmol/L）was associated with a 1.891-fold increased risk of HF as a categorical variable（OR=1.891，95%CI：1.047–3.415，P=0.035）．As a continuous variable，each increased unit in RC was associated with a 2.464-fold increased risk of HF（OR=2.464，95%CI：1.495–4.064，P＜0.001）．The odds ratios for Log₁₀RC and standardized RC were 6.411（95%CI：2.246–18.302，P=0.001）and 1.687（95%CI：1.262–2.255，P＜0.001），respectively．ROC analysis indicated a linear positive association between RC and HF risk（P=0.002）．ROC analysis showed that RC had predictive value for HF，with an AUC of 0.621（95%CI：0.555–0.687，P＜0.001）．Conclusions  RC levels are significantly associated with the risk of HF in patients with diabetes and CHD，demonstrating a linear positive correlation．RC has potential predictive value and may serve as a useful indicator for assessing HFrisk in this population．

      目的   探讨妊娠期糖尿病（GDM）患者载脂蛋白B（Apo-B）、载脂蛋白A1（Apo-A1）水平在分娩巨大儿中的预测价值。方法   选取2023年1月—2024年1月在珠海市第五人民医院建档并进行孕检、分娩的85例GDM患者，按照分娩的新生儿体质量情况分为分娩正常组55例（新生儿体质量＜4 000 g）和分娩异常组30例（新生儿体质量≥4 000 g）。比较两组孕妇一般资料及孕早期的Apo-B、Apo-A1、Apo-B/Apo-A1比值，采用受试者操作特征（ROC）曲线分析Apo-B、Apo-A1、Apo-B/Apo-A1对GDM患者分娩巨大儿的预测价值。结果   分娩异常组Apo-B水平、Apo_B/Apo_A1比值（1.05±0.15）g/L、（0.81±0.23）］高于分娩正常组（0.95±0.12）g/L、（0.65±0.18）］（t分别为3.357、3.544，P＜0.05）；Apo-A1水平［（1.29±0.26）g/L］低于分娩正常组［（1.47±0.23）g/L］（t=3.292，P＜0.05）；ROC曲线显示，Apo-B、Apo-A1水平及Apo-B/Apo-A1比值预测GDM患者分娩巨大儿的曲线下面积（AUC）分别为0.705、0.660、0.709，灵敏度分别为63.33%、63.33%、66.67%，特异度分别为72.73%、74.55%、76.36%，其中Apo-B/Apo-A1比值预测效能最高（P＜0.05）。结论  GDM患者分娩巨大儿与孕早期Apo-B升高、Apo-A1水平降低密切相关，监测患者孕早期的Apo-B、Apo-A1水平及Apo-B/Apo-A1比值有助于临床对分娩巨大儿进行预测。

      Objective  To explore the predictive value of apolipoprotein B（Apo-B）and apolipoprotein A1（Apo-A1）levels on delivery of macrosomia in patients with gestational diabetes mellitus（GDM）．Methods  From January 2023 to January 2024，85 patients with GDM who were filed in the hospital and received pregnancy examination and delivery were selected．According to the neonatal body mass，the patients were divided into 55 cases in normal delivery group（newborn birth weight ＜4 000 g）and 30 cases in abnormal delivery group（ newborn birth weight ≥4 000 g）．The general data and levels of Apo-B，Apo-A1 and Apo-B/Apo-A1 in early pregnancy were compared between the two groups．Receiver operating characteristic（ROC）curve was used to analyze the predictive value of Apo-B，Apo-A1 and Apo-B/Apo-A1 on delivery of macrosomia in GDM patients．Results  The Apo-B and Apo-B/Apo-A1 in abnormal delivery group were（1.05±0.15）g/L and（0.81±0.23），which were higher than（0.95±0.12）g/L and（0.65±0.18）in normal delivery group（t=3.357，3.544，P＜0.05）．While the level of Apo-A1 in abnormal delivery group，（1.29±0.26）g/L，was lower than（1.47±0.23）g/L in normal delivery group（t=3.292，P＜0.05）．ROC curve showed that the areas under the curve（AUC）of Apo-B，Apo-A1 and Apo-B/Apo-A1 in  predicting macrosomia in GDM patients were 0.705，0.660 and 0.709，and the sensitivities were 63.33%，63.33% and 66.67%，and the specificities were 72.73%，74.55% and 76.36%，respectively．Apo-B/Apo-A1 had the highest predictive efficiency（P＜0.05）．Conclusions  The delivery of macrosomia in GDM patients is closely related to the increase of Apo-B and the decrease of Apo-A1 in early pregnancy．Monitoring Apo-B，Apo-A1 and Apo-B/Apo-A1 in early pregnancy is helpful to predict the delivery of macrosomia．

       目的   探讨脓毒性休克患者肿瘤坏死因子相关受体6 （TRAF6）、胆碱酯酶（ChE）及急性生理学和慢性健康状况评价Ⅱ（APACHE Ⅱ）对预后不良的预测价值。方法   回顾分析2023年2月—2024年3月于某院ICU病区收治的226例脓毒性休克患者的临床资料，基于患者预后情况分为预后良好组（n=151）以及预后不良组（n=75）。回顾226例脓毒性休克患者入院时及治疗后的TRAF6、ChE表达变化，并记录患者APACHEⅡ评分和序贯器官功能衰竭评估（SOFA）评分动态变化；比较并分析两组患者详尽的临床资料，探讨TRAF6、ChE联合APACHE Ⅱ评分之间的关联性以及上述指标对脓毒性休克患者预后情况的临床评估价值。采用Logistic回归来分析对脓毒性休克患者生存状况产生影响的潜在因素。结果   多因素Logistic回归分析，年龄、APACHE Ⅱ评分、SOFA评分、机械通气时间、TRAF6与ChE表达水平均是影响患者预后的独立危险因素（P＜0.05）；受试者操作特征曲线分析显示，年龄、APACHE Ⅱ评分、机械通气时间、SOFA评分、TRAF6、ChE表达水平联合预测脓毒性休克患者预后不良的曲线下面积为0.925，高于单独检测的0.689、0.783、0.794、0.781、0.708、0.827。结论   临床需要及时识别高龄、长时间机械通气时间、高APACHE Ⅱ与SOFA评分、高TRAF6和ChE表达水平的高风险患者，TRAF6、ChE表达水平、SOFA评分、APACHE Ⅱ评分可作为评估脓毒性休克患者预后情况的临床指标，联合应用能进一步提升临床价值。

      Objective  To explore the predictive value of tumor necrosis factor receptor associated factor 6（TRAF6），cholinesterase（ChE）and Acute Physiology and Chronic Health Evaluation II scove（APACHE II）for adverse prognosis in patients with septic shock．Methods  The clinical data of 226 patients with septic shock admitted to the Intensive Care Unit（ICU） of a hospital from February 2023 to March 2024 were retrospectively analyzed，and the patients were divided into a good prognosis group（n=151）and an adverse prognosis group（n=75）based on their prognosis．The expression of TRAF6 and ChE in 226 patients with septic shock was reviewed at admission and after treatment，while the dynamic changes of APACHE  II score and Sequential Organ Failure Assessment（SOFA）score were recorded．Detailed clinical data of the two groups were compared and analyzed to explore the correlation between TRAF6，ChE，APACHE II scores and the clinical evaluation value of the above indexes in the prognosis of patients with septic shock．Logistic regression was used to analyze the potential factors affecting the survival of septic shock patients．Results  Multiple Logistic regression analysis revealed that age，APACHE II score，SOFA score，mechanical ventilation time，TRAF6 and ChE expression levels were independent risk factors for prognosis（P＜0.05）．Receiver Operating Characteristic（ROC）curve analysis showed that the area under curve（AUC）was 0.925，which was higher than single index prediction（0.689，0.783，0.794，0.781，0.708 and 0.827）．Conclusions  High-risk patients with advanced age，prolonged mechanical ventilation，high APACHE II and SOFA scores，and high TRAF6 and ChE expression levels need to be identified in time．TRAF6，ChE expression levels，SOFA scores，and APACHE  II scores can be used as clinical indicators to evaluate the prognosis of septic shock patients．The combined application of those four indicators can further improve the clinical value．

       目的   通过机器学习方法构建脓毒症谵妄患者30 d死亡的预测模型，并识别关键预测因子。方法   采用基于医疗信息集成重症监护数据库（Medical Information Mart for Intensive Care IV）的回顾性队列研究方法，boruta筛选重要特征，并通过决策树，K近邻，LightGBM，随机森林，支持向量机，XGBoost构建模型进行分析，通过ROC曲线下面积进行评估，利用F1分数、召回率、精确率、特异度、灵敏度和阳性预测值比较模型表现。结果  XGBoost模型在训练集和验证集中的ROC曲线下面积分别为0.906和0.762，表明该模型具有良好的预测能力，入院年龄、红细胞分布宽度和白细胞计数是最重要的预测因子。结论   基于机器学习的脓毒症谵妄患者预后预测模型展现出良好的预测效能，为临床早期干预提供了重要参考依据。

       Objective  To construct a  30-day mortality  prediction model for  patients with  sepsis-associated  delirium using machine learning methods and identify key predictive factors．Methods  A  retrospective cohort study was conducted based on the Medical Information Mart for Intensive Care IV database．Important features were selected using the Boruta algorithm，and models including Decision Tree，K-Nearest Neighbors，LightGBM，Random Forest，Support Vector Machine，and XGBoost were constructed and analyzed．Model performance was evaluated using the area under the reciver operater characteristic（ROC）curve（AUC），along with F1 score，recall，precision，specificity，sensitivity，and positive predictive value．Results  The XGBoost model demonstrated strong predictive performance，with AUC values of 0.906 in the training set and 0.762 in the test set．Key predictors identified included admission age，red blood cell distribution width，and white blood cell count．Conclusions  The machine learning-based prediction model for sepsis-associated delirium prognosis exhibits robust predictive efficacy，providing a valuable tool for early clinical intervention．

目的 探讨振幅整合脑电图（aEEG）联合头颅磁共振成像（cMRI）对早产儿矫正12月龄时神经发育的预测价值。方法 选取110例早产儿为研究对象,并在矫正12月龄时采用Gesell 发育量表评估发育商（DQ）,依据DQ分为Gesell 正常组（DQ≥85,n=83）、Gesell 异常组（DQ<85,n=27）。采集早产儿及母亲临床资料,对比两组出生后72 h内aEEG、矫正胎龄37周时cMRI检查指标差异。结果 两组早产儿及母亲基线资料比较差异无统计学意义（P>0.05）。相较于Gesell 正常组,Gesell 异常组双顶径（BPW）降低[（70.68±5.32）mm vs（66.54±3.69）mm],睡眠-觉醒周期（SWC）不成熟率（20.48% vs 85.19%）、aEEG异常率（30.12% vs 70.37%）、两半球间距（IHD）增高[（2.95±0.83） mm vs（3.56±0.72）mm]（P<0.05）。Pearson相关分析结果显示,DQ值与IHD呈负相关,DQ值与BPW呈正相关（r=-0.361、0.598,P<0.05）。二元Logistic回归分析结果显示,BPW增高是Gesell 异常的独立保护因素（P<0.05）,IHD增高、SWC不成熟及aEEG异常是Gesell 异常的独立危险因素（P<0.05）。结论 早产儿出生后72 h内aEEG异常、矫正胎龄37周时cMRI异常可能提示矫正12月龄时不良神经发育结局。

Objective To evaluate the predictive value of amplitude-integrated electroencephalogram combined with cranial magnetic resonance on neurodevelopment for preterm infants at corrected age of 12 months．Methods A total of 110 preterm infants were selected as study subjects,and Gesell developmental scale was used to evaluate developmental quotient（DQ）at corrected age of 12 months．According to DQ,they were divided into normal Gesell group（DQ≥85,n=83）and abnormal Gesell group（DQ<85,n=27）．Clinical data of preterm infants and their mothers were collected,and the differences of amplitude-integrated electroencephalogram and cranial MRI（cMRI）were compared between two groups．Results There was no significant difference in baseline data between two groups（P>0.05）．Compared with the normal Gesell group,the biparirtal width（BPW）in the abnormal Gesell group was decreased（70.68±5.32mm vs 66.54±3.69mm）,the immaturity rate of sleep-wake cycle（SWC）（20.48% vs 85.19%）,the abnormal rate of aEEG（30.12% vs 70.37%）,and（IHD）（2.95±0.83mm vs 3.56±0.72mm）were increased（P<0.05）．The results of Pearson correlation analysis showed that DQ was negatively correlated with IHD,and DQ was positively correlated with BPW（r=-0.361、0.598,P<0.05）．Binary Logistic regression analysis showed that increased BPW was an independent protective factor for abnormal Gesell（P<0.05）,and increased IHD,immature SWC and abnormal aEEG were independent risk factors for abnormal Gesell（P<0.05）．Conclusions Abnormal aEEG within 72h after birth and abnormal cMRI at corrected age of 37 weeks may lead to adverse neurodevelopmental outcomes at corrected age of 12 months．

目的 分析产后出血预测评分与产妇凝血指标的相关性,以及出血预测评分对阴道分娩产后出血的预测效能。方法 采用回顾性研究,纳入2021年1月—2022年12月河南科技大学第二附属医院收治的136例阴道分娩产妇,根据产后出血情况,将合并产后出血的36例患者列为病例组,其余100例列为对照组,比较两组患者的产后出血预测评分及凝血指标,经Spearman相关性系数验证产后出血预测评分结果与凝血指标的相关性,依据实际出血情况,验证产后出血预测评分、各凝血指标对产后出血的预测效能。结果 病例组患者的产后出血预测评分为（7.33±2.46）分,D-二聚体（D-D）为（2.62±0.41）mg/L,均高于对照组[（6.14±2.06）分、（2.17±0.45）mg/L],纤维蛋白原（FIB）为（4.42±1.25）g/L,低于对照组（5.23±1.16）g/L;活化部分凝血活酶时间（APTT）为（37.44±10.25）s,凝血酶原时间（PT）为（15.45±4.12）s,凝血酶时间（TT）为（16.77±4.25）s,均高于对照组[（30.11±10.12）s、（12.49±4.11）s、（13.34±4.18）s],差异具有统计学意义（P<0.05）。经Spearman相关性系数分析,产后出血预测评分与经阴道分娩产妇的D-D、APTT、PT、TT呈正相关,与FIB呈负相关。通过绘制受试者工作特征曲线（ROC）后得知,产后出血预测评分及凝血指标对产后出血均有一定预测价值,但产后出血预测评分的AUC值大于各凝血指标。结论 产后出血预测评分与产妇凝血功能指标呈正相关,将产后出血预测评分与凝血指标检测相结合能实现对产后出血的早期识别及诊断。

Objective To analyze the correlation between postpartum bleeding prediction score and maternal blood coagulation index and the prediction efficiency of postpartum bleeding in vaginal delivery．Methods This is a retrospective study．The cases were included from January 2021 to December 2022．The subjects of the study were 136 vaginal delivery mothers． According to the delivery situation,36 patients with postpartum bleeding were included in the case group,and the rest 100 patients were included in the control group．The postpartum bleeding prediction score and coagulation indicators of the two groups were compared．The correlation between postpartum bleeding prediction score and coagulation indicators was verified by Spearman correlation coefficient．According to the actual bleeding situation,verify the predictive score for postpartum bleeding and the diagnostic efficacy of various coagulation indicators on postpartum bleeding．Results According to the test,the predictive score for postpartum bleeding in the case group was（7.33±2.46）,D-dimer（D-D）was（2.62±0.41）mg/L,which were higher than those in the control group [（6.14±2.06）,（2.17±0.45）mg/L]．Fibrinogen（FIB）was（4.42±1.25）g/L,lower than the control group（5.23±1.16）g/L,activated partial thromboplastin time（APTT）was（37.44±10.25）s,prothrombin time（PT）was（15.45±4.12）s,and thrombin time（TT）was（16.77±4.25）s．Compared with the control group [（30.11±10.12）s,（12.49±4.11）s,and（13.34±4.18）s）],the above indicators were all higher（P<0.05）．Through Spearman correlation coefficient analysis,the predictive score of postpartum bleeding was positively correlated with the D-D,APTT,PT,TT,negatively correlated with the FIB of the parturient who delivered through vagina．After drawing the ROC curve,it was found that both the postpartum hemorrhage prediction score and coagulation indicators had certain predictive value for postpartum hemorrhage,but the AUC value of the postpartum hemorrhage prediction score was greater than each coagulation indicator．Conclusions The prediction score of postpartum bleeding is positively correlated with the coagulation function indicators of the parturient,combining the score and indicators can achieve early identification and diagnosis of postpartum bleeding．

胶质瘤是颅内最常见的原发性恶性肿瘤,其分级对患者治疗方式的选择和预后至关重要。尽管目前组织病理学仍是其最为可靠的分级手段,但需通过有创性手术以获取组织样本,存在一定的风险。相较之下,磁共振成像（MRI）作为一种非侵入性影像诊断工具,在胶质瘤分级中发挥着不可或缺的作用。然而,传统MRI评估受限于医师个体主观性强和可重复性差的问题,一定程度上影响了准确的分级结果。近年来,影像组学技术的崭露头角为解决上述难题开辟了新视角,通过高通量提取影像数据特征捕捉并量化肿瘤的影像学表现,避免因主观因素而导致的不确定性,协助医师更准确地评估肿瘤的恶性程度。本文对近五年来MRI影像组学在胶质瘤术前分级预测方面的相关研究进行了简要综述,旨在为相关领域研究者提供有益的参考和借鉴,以推动MRI影像组学在临床实践中的应用。

Glioma is the most common primary malignant brain tumor,and its grading is crucial for treatment decisions and prognosis．Currently,histopathology remains the gold standard for grading,but it requires invasive procedures and carries inherent risks．In contrast,magnetic resonance imaging（MRI）,a non-invasive diagnostic tool,plays an indispensable role in glioma grading．However,traditional MRI assessment is hampered by interobserver subjectivity and limited repeatability,which compromise grading accuracy．In recent years,radiomics,a burgeoning field,has offered a promising solution to address these challenges．By extracting high-dimensional imaging data features,radiomics enables the quantification of tumor radiological characteristics and elimination of subjectivity-related discrepancies．This technology assists clinicians in more precisely assessing the malignancy of gliomas．This article summarizes relevant studies in the past five years on the application of MRI radiomics in preoperative glioma grading,aiming to provide valuable insights and guidance to researchers in the field and promote the clinician implementation of MRI radiomics．

目的 分析常规炎性指标与进展性脑梗死（PCI）患者病灶损害程度的关联,及其对预后水平的预测效能。方法 采用回顾性研究,纳入2021年6月—2023年2月平顶山市第二人民医院收治的100例PCI患者,根据入院时神经功能缺损评分（NIHSS）结果,将NIHSS评分≥21分的30例患者列为重度组,将NIHSS评分15~20分的35例患者列为中度组,将NIHSS评分<15分的35例患者列为轻度组,比较三组患者的神经功能血清学指标及炎症指标,经Pearson相关性分析炎症指标与神经功能血清学指标的相关性;根据是否发生不良预后将入组患者分为预后良好组和预后不良组,比较两组患者各炎症指标及改良Rakin量表（mRS）评分间的差异,并通过绘制受试者操作特征（ROC）曲线、曲线下面积（AUC）评估炎症指标对PCI患者预后水平的预测效能。结果 重度组患者的C-反应蛋白（CRP）、白细胞介素-6（IL-6）、肿瘤坏死因子-α（TNF-α）分别为（26.44±5.18）mg/L、（95.28±10.46）ng/L、（45.24±10.31）pg/mL,均高于中度组[（23.12±5.46）mg/L、（90.44±10.17）ng/L、（40.25±10.18）pg/mL],轻度组[（20.28±5.33）mg/L、（84.33±10.27）ng/L、（35.62±8.45）pg/mL],差异具有统计学意义（P<0.05）。重度组的神经元特异性烯醇化酶（NSE）、S100钙结合蛋白β（S100β）分别为（25.45±5.69）μg/L、（60.45±10.31）ng/mL,均高于中度组[（22.18±5.36）μg/L、（55.27±10.46）ng/mL],轻度组[（19.44±5.37）μg/L、（50.49±10.25）ng/mL],差异具有统计学意义（P<0.05）。经Pearson相关性分析,PCI患者的CRP、IL-6、TNF-α等常见炎性指标水平与NSE、S100β等神经功能血清学指标水平正相关（P<0.05）。经检测,预后不良组的CRP、IL-6、TNF-α、mRS分别为（26.62±5.31）mg/L、（96.77±10.24）ng/L、（47.25±10.33）pg/mL、（4.24±1.33）分,均高于预后良好组[（23.75±5.44）mg/L、（91.25±10.37）ng/L、（41.12±10.44）pg/mL,（3.36±0.27）分],差异具有统计学意义（P<0.05）。经ROC曲线验证,CRP、IL-6、TNF-α等常见炎性指标水平越高,PCI患者的mRS评分越高（AUC均>0.85）。结论 CRP、IL-6、TNF-α等常见炎性指标会随PCI患者脑神经功能损伤程度加剧而不断升高,与病灶损害程度正相关;通过检测上述炎性指标能实现对患者不良预后的早期预测。

Objective To analyze the correlation between routine inflammatory indicators and the degree of lesion damage in progressive cerebral infarction（PCI） patients,as well as predictive efficacy of indicators on prognosis levels．Methods This is a retrospective study,with case enrollment from June 2021 to February 2023．The study subjects were 100 PCI patients．Based on the NIHSS score at admission,30 patients with a NIHSS score ≥ 21 were classified as the severe group,35 patients with a NIHSS score of 15~20 were classified as the moderate group,and 35 patients with a NIHSS score <15 were classified as the mild group．The neurological function serological and inflammatory indicators of the three groups of patients were compared．The correlation between inflammatory indicators and neurological serological indicators was verified by Pearson correlation coefficient．According to the occurrence of adverse prognosis,enrolled patients were divided into good prognosis group and poor prognosis group．The differences in inflammatory indicators and mRS scores between the two groups were compared,and the predictive power of inflammatory indicators on the prognosis level of PCI patients was evaluated by plotting ROC and observing AUC．Results After testing,the levels of CRP,IL-6 and TNF in the severe group were（26.44±5.18）mg/L,（95.28±10.46）ng/L and（45.24±10.31）pg/mL,respectively,higher than those in the moderate group[（23.12±5.46）mg/L,（90.44±10.17）ng/L and（40.25±10.18）pg/mL]and the mild group[（20.28±5.33）mg/L,（84.33±10.27）ng/L and（35.62±8.45）pg/mL]（P<0.05）．NSE and S100β in the severe group were（25.45±5.69）μg/L and（60.45±10.31）ng/mL,all higher than those in the moderate group[（22.18±5.36）μg/L,（55.27±10.46）ng/mL]and mild group[（19.44±5.37）μg/L,（50.49±10.25）ng/mL]（P<0.05）．According to Pearson correlation coefficient test,CRP,IL-6,TNF-α and mRS in PCI patients positively correlated with NSE,S100β（P<0.05）．After testing,CRP,IL-6,TNF-α and mRS in the group with poor prognosis were（26.62±5.31）mg/L,（96.77±10.24）ng/L,（47.25±10.33）pg/mL and（4.24±1.33）scores,respectively,which were higher than those in the group with good prognosis[（23.75±5.44）mg/L,（91.25±10.37）ng/L,（41.12±10.44）pg/mL and（3.36±0.27）scores]（P<0.05）．Verified by ROC curve,the higher the levels of CRP,IL-6 and TNF- α,the higher the mRS scores of PCI patients（AUC>0.85）．Conclusions Common inflammatory indicators such as CRP,IL-6 and TNF- α of PCI will continue to increase with the severity of brain nerve function damage in patients,and are positively correlated with the degree of lesions damage．By detecting the aforementioned inflammatory indicators,early prediction of poor prognosis can be achieved for patients．