目的 探讨血清乳酸脱氢酶（LDH）在中晚期肝癌患者接受靶向联合免疫治疗后的预后预测价值。方法 选取2022年1月—2024年8月在莆田学院附属医院肿瘤内科经病理和影像学检查确诊的中晚期肝癌患者作为研究对象。从医院的电子病历系统中收集患者的基线资料，随访截止2025年8月，并记录随访结果，包括患者的疾病缓解情况和死亡情况，以及无疾病进展生存期（PFS）、总生存期（OS）。采用Kaplan-Meier方法绘制不同基线LDH水平患者的OS生存曲线，并通过Log-rank检验比较生存曲线。同时，运用多因素Cox比例风险回归分析探讨影响中晚期肝癌患者在接受靶向联合免疫治疗后OS的相关因素。结果 结果显示，在50例肝癌患者中，基线LDH低于200 U/L的有15例，而高于200 U/L的有35例。与基线LDH＜200 U/L组相比，基线 LDH≥200 U/L患者PFS、OS更短，差异均有统计学意义（χ²分别为5.51、15.6，P值分别为0.019、0.017）。治疗8周后，与LDH降低患者相比，LDH升高患者OS更短，差异有统计学意义（χ²=13.2，P=0.04）。多因素Cox比例风险回归分析结果表明，基线LDH水平超过200 U/L是中晚期肝癌患者接受靶向联合免疫治疗后OS的影响因素［P=0.035，HR（95%CI）=5.03（1.12，22.54）］。结论 基线LDH水平较低的患者表现出更好的OS。基线LDH水平可以作为预测中晚期肝癌患者在接受靶向联合免疫治疗时预后的指标。 

   Objective To evaluate the prognostic significance of serum lactate dehydrogenase（LDH）levels in patients with advanced hepatocellular carcinoma（HCC）undergoing targeted therapy combined immunotherapy．Methods Patients diagnosed with advanced HCC were selected in Putian College Affiliated Hospital from January 2022 to August 2024，diagnosed with pathological and imaging examinations results．Patient baseline data were collected from the hospital’s electronic medical records，with follow-up extending until August 2025．We documented outcomes such as disease response and mortality，along with progression-free survival（PFS）and overall survival（OS）．Kaplan-Meier survival curves were constructed based on baseline LDH levels，and the Log-rank test was employed for comparison．Additionally，multivariate Cox proportional hazards regression analysis was conducted to identify factors influencing OS in patients receiving targeted therapy combined immunotherapy．Results Among the 50 patients，15 had baseline LDH levels below 200 U/L，while 35 had levels above．Patients with baseline LDH≥200 U/L had significantly shorter PFS and OS than those with baseline LDH ＜200 U/L（χ²=5.51 and 15.6 for PFS and OS，respectively；P=0.019 and 0.017，respectively）．After 8 weeks of treatment，patients with increased LDH had significantly shorter OS compared with patients with decreased LDH（χ²=13.2，P=0.04）．Multivariate Cox proportional hazards regression analysis indicated that a baseline LDH level exceeding 200 U/L is an independent prognostic factor for OS in patients with intermediate to advanced HCC receiving targeted therapy combined with immunotherapy（P=0.035，HR 5.03［1.12，22.54］）．Conclusions Patients with lower baseline LDH levels demonstrated better OS，suggesting that baseline LDH can serve as an important prognostic indicator for advanced HCC patients undergoing targeted combined immunotherapy．

       目的 构建首发脑出血患者并发卒中相关性肺炎的风险预测模型并验证模型的预测性能。方法 回顾性分析2012年1月—2022年12月广州市第一人民医院治的419例首发脑出血患者的临床资料，按照7︰3比例随机化分为训练列（293例）和验证队列（126例）。统计基于开发队列数据，采用Logistic回归模型分析首发脑出血患者并发卒中相关性肺炎的影响因素，并构建风险预测模型。基于开发队列和验证队列数据，采用校准曲线、受试者操作特征（ROC）曲线下面积和决策曲线分析模型的预测性能。结果 419例首发脑出血患者中有113例发生卒中相关性肺炎，发生率为26.97%。美国国立卫生研究院卒中量表（NIHSS）评分、吞咽困难、初始血肿体积、中性粒细胞百分比与白蛋白比值（NPAR）、中性粒细胞计数与淋巴细胞计数比值（NLR）、手术治疗、气管插管、留置胃管均是首发脑出血患者并发卒中相关性肺炎的影响因素（P＜0.05）。基于上述影响因素构建了首发脑出血患者并发卒中相关性肺炎的风险预警模型，校准曲线显示模型在开发队列和验证队列中预测卒中相关性肺炎发生率均与实际发生率相近；ROC曲线显示此模型在开发队列、验证队列中预测的曲线下面积分别为0.906（95%CI：0.867~0.937）、0.884（95%CI：0.815~0.934）；决策曲线分析显示当开发队列阈概率在3%~80%内、验证队列阈概率在2%~76%内使用此模型干预比全/无干预更有临床价值。结论 基于NIHSS评分、吞咽困难、初始血肿体积、NPAR、NLR、手术治疗、气管插管、留置胃管构建的首发脑出血患者并发卒中相关性肺炎的风险预测模型具有良好预测性能和临床应用价值。

      Objective To construct a risk prediction model for stroke associated pneumonia in patients with initial cerebral hemorrhage（ICH）and validate the predictive performance of the model．Methods A retrospective analysis was conducted on the clinical data of 419 patients with ICH admitted to our hospital from January 2012 to December 2022．They were randomly divided into a development cohort（293 cases）and a validation cohort（126 cases）according to a 7∶3 ratio．The Logistic regression model was used to analyze the influencing factors of stroke related pneumonia in patients with ICH based on the development cohort data，and a risk prediction model was constructed．Based on the development cohort data and validation cohort data，the predictive performance of the model was analyzed using calibration curves，receiver operating characteristic（ROC）curve，and decision curve analysis．Results Among 419 patients，113 developed stroke associated pneumonia，with a rate of 26.97%．The National Institutes of Health Stroke Scale（NIHSS）score，swallowing difficulties，initial hematoma volume，neutrophil percentage to albumin ratio（NPAR），neutrophil count to lymphocyte count ratio（NLR），surgical treatment，endotracheal intubation，and indwelling gastric tube were all independent influencing factors for stroke associated pneumonia in patients with ICH（P＜0.05）．Based on the above influencing factors，a risk prediction model for stroke associated pneumonia in patients with ICH was constructed．The calibration curve showed that the predicted incidence of stroke associated pneumonia by the model in both the development and validation cohorts was close to the actual incidence．The ROC curve showed that the predicted area under the curve for this model in the development cohort and validation cohort was 0.906（95%CI：0.867-0.937）and 0.884（95%CI：0.815-0.934），respectively．The decision curve analysis showed that when the threshold probability of the development cohort was between 3%-80%，and the threshold probability of the validation cohort was between 2%-76%，the intervention using this model was more clinically valuable than all/no intervention．

Conclusions The risk prediction model for stroke associated pneumonia in patients with ICH based on NIHSS score，swallowing difficulties，initial hematoma volume，NPAR，NLR，surgical treatment，tracheal intubation，and indwelling gastric tube has good predictive performance and clinical application value．

目的：分析急性有机磷农药中毒（AOPP）引发缺血缺氧性脑病预后相关因素，建立相关的预后预测模型。方法：回顾性分析90例（33例预后不良、57例预后良好）AOPP致HIE患者（2022年3月～2025年8月）的临床资料、中毒指标和血清学指标，独立危险因素用Logistic回顾分析筛选，并构建预后不良预测模型，采用ROC工具对模型效能进行验证。结果：Logistic 回归分析显示，年龄≥60岁、重度中毒、中毒至就诊时间、LAC水平、CHE水平、CRP水平及NSE水平均为患者预后不良的独立危险因素（P＜0.05）；AUC、灵敏度、特异度为0.943、90.91%、87.72%。结论：高龄、中毒程度高及中毒至就诊时间长等因素可导致AOPP致HIE患者出现不良结局，据此构建风险预测模型可有效预测预后不良的发生风险。

To determine the key impacting factors for hypoxic ischemic encephalopathy (HIE) caused by acute organophosphorus pesticide poisoning (AOPP) and build a prediction model. Methods: The clinical data, poisoning indicators and serological indicators of 90 patients (33 cases with poor prognosis and 57 cases with good prognosis) with HIE caused by AOPP (from March 2022 to Aug 2025) were analyzed. Independent risk factors were screened using logistic retrospective analysis, and a poor prognosis prediction model was constructed. The model efficiency was verified by the receiver operating curve (ROC). Results: Logistic regression analysis showed that age ≥ 60 years, severe poisoning, time from poisoning to treatment, LAC level, CHE level, CRP level, and NSE level were all risk factors for the prognosis in patients (P < 0.05). The AUC, sensitivity, and specificity were 0.943, 90.91%, and 87.72%.Conclusion: Factors such as advanced age, high degree of poisoning, and long time from poisoning to treatment can lead to adverse outcomes in patients with HIE caused by AOPP. Based on this, building a risk prediction model can effectively predict the risk of poor prognosis.

       目的  探讨结肠镜下息肉切除术后复发的危险因素，并基于机器学习算法构建复发风险预警模型，为防治对策提供依据。方法  回顾性收集2018年9月—2023年9月六安市人民医院1 058例初次行无痛结肠镜下息肉切除术患者的临床资料，使用单因素和多因素Logistic回归分析筛选复发危险因素。采用7∶3随机抽样分为训练集和验证集，分别通过决策树、贝叶斯及Logistic回归算法构建预测模型，并以受试者工作特征曲线（ROC）曲线下面积（AUC）、灵敏度、特异度等指标来评估模型效能。结果  单因素分析显示，性别、吸烟、代谢综合征、息肉数量、息肉位置、山田分型、组织病理学类型、切除方式、复查时间、肠息肉直径、手术时间是复发的危险因素（P＜0.05）。多因素分析显示，性别、代谢综合征、息肉数量、息肉直径、肠息肉位置、山田分型、组织学病理类型、切除方式、手术时间均是结肠息肉内镜下切除术后复发的危险因素。模型评估显示，决策树算法、贝叶斯算法、Logistic回归算法的ROC曲线下面积（AUC）分别为0.849、0.818、0.811；灵敏度分别为85.14%、81.62%、79.43%；特异度分别为81.69%、79.45%、74.18%；约登指数分别为0.534、0.551、0.573；95%CI分别为0.810~0.876、0.794~0.860、0.782~0.850；决策树算法模型效能最佳，Logistic回归算法的性能最差。结论  性别、代谢综合征、肠息肉特征（数量、直径、位置等）是术后复发的关键危险因素。决策树模型在风险预测中表现最优，可为临床制定个体化随访策略提供参考。

       Objective  To explore the  risk factors for  recurrence after painless colonoscopic polypectomy and construct a recurrence risk warning model based on machine learning algorithms to provide evidence for prevention and treatment strategies．Methods  A retrospective analysis was conducted on clinical data from 1 058 patients who underwent their first painless colonoscopy-guided polypectomy at our hospital between September 2018 and September 2023．Univariate and multivariate Logistic  regression analyses were performed to identify recurrence risk factors．The dataset was randomly divided into training and validation sets using a 7∶3 ratio．Prediction models were constructed using decision tree，Bayesian，and Logistic regression algorithms，and their performance was evaluated using metrics such as the area under the receiver operating characteristic curve（AUC），sensitivity，specificity，and others．Results  Univariate analysis revealed that gender，smoking，metabolic syndrome，number of polyps，polyp location，Yamada classification，histopathological type，resection method，follow-up time，polyp diameter，and operation duration were risk factors for recurrence（P＜0.05）．Multivariate analysis identified gender，metabolic syndrome，number of polyps，polyp diameter，polyp location，Yamada classification，histopathological type，resection method，and operation duration as independent risk factors for recurrence after endoscopic polypectomy．Model evaluation showed AUC values of 0.849，0.818，and 0.811 for the decision tree，Bayesian，and Logistic regression algorithms，respectively．Sensitivity values were 85.14%，81.62%，and 79.43%；specificity values were 81.69%，79.45%，and 74.18%；Youden’s indices were 0.534，0.551，and 0.573；and 95% confidence intervals（CIs）were 0.810–0.876，0.794–0.860，and 0.782–0.850，respectively．The  decision tree algorithm demonstrated the best predictive performance，while the Logistic regression algorithm performed the least favorably．Conclusions  Gender，metabolic syndrome，and polyp characteristics（number，diameter，location，etc．）are key  risk factors for recurrence after polypectomy．The decision tree algorithm exhibited optimal predictive efficacy，offering valuable insights for developing individualized follow-up strategies in clinical practice．

      目的   基于决策树构建老年患者吞咽障碍预警模型。方法  采用便利取样法对宁夏银川市宁夏回族自治区人民医院老年科住院的200例老年患者进行调查。结果  200例老年患者中，吞咽障碍发生率为40.5%。依据是否发生吞咽障碍将其患者分为两组，两组患者在性别、年龄、文化程度、职业、医保类型、家庭年收入、日常生活能力、衰弱、抑郁、营养、体质指数（BMI）比较（χ ² 值分别为13.321、4.064、31.944、36.695、18.230、19.681、52.509、10.253、20.456、9.070、9.483），差异均有统计学意义（均P＜0.05）。决策树模型筛选出老年患者吞咽障碍的影响因素主要有自理能力、职业、文化程度和抑郁，决策树模型受试者工作特征曲线下面积为0.862，灵敏度为79.8%，特异度为79.0%，P＜0.001。结论  基于自理能力、职业、文化程度和抑郁构建的决策树模型，能有效预测老年患者吞咽障碍风险。

       Objective  To construct a swallowing disorder warning model for elderly patients based on decision tree．Methods  Convenience  sampling was  used to  study  200  elderly  patients  admitted to the  geriatric  department  of  a tertiary comprehensive hospital in Yinchuan，Ningxia．Results  Among 200 elderly patients，the incidence of swallowing disorders was 40.5%．The two groups of patients were compared in terms of gender，age，education level，occupation，medical insurance type，annual family income，daily living ability，frailty，depression，nutrition，and BMI（χ ²  values were 13.321，4.064，31.944，36.695，18.230，19.681，52.509，10.253，20.456，9.070，9.483，respectively），and the  differences were  statistically significant（all P＜0.05）．The decision tree model identified the main influencing factors of swallowing disorders in elderly patients as self-care ability，occupation，education level，and depression．The Receiver Operating Characteristic curve of the decision tree model had an area under the curve of 0.862，sensitivity of 79.8%，and specificity of 79.0%，P＜0.001．Conclusions  A decision tree model based on self-care ability，occupation，education level，and depression can effectively predict the  risk of swallowing disorders in elderly patients．

       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．