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   评估ChatGPT 4与Llama 3微调模型在乳腺癌诊断中的应用效果，特别是在超声、钼靶及超声联合钼靶的非结构化报告和影像诊断方面。方法   回顾性收集了689例同时接受乳腺超声和钼靶检查的患者数据，比较两种模型在文本和图像模态下的诊断性能，并探讨乳腺密度对模型表现的影响。结果   在文本模态下，微调Llama 3表现优异，联合诊断准确率达91.7%，优于ChatGPT 4的71.7%。图像模态中两模型准确率均低于70%，但ChatGPT 4灵敏度较高（78.3%），Llama 3特异度突出（98.3%）。分组分析表明，在非致密型乳腺中钼靶表现更佳，而致密型乳腺中超声诊断更具优势。结论   大语言模型在医学图像处理和多模态整合方面仍需进一步优化，医学领域微调的大语言模型在处理非结构化临床文本方面具有潜力。

       Objective  To evaluate the application effectiveness of ChatGPT 4 and the fine-tuned Llama 3 model in breast cancer diagnosis，particularly in processing unstructured reports and diagnostic imaging of ultrasound，mammography，and their combined modalities．Methods  Retrospective data from 689 patients who underwent both breast ultrasound and mammography examinations were collected．The diagnostic performance of the two models was compared across text and image modalities，and the impact of breast density on model performance was explored．Results  In the text modality，the fine-tuned Llama 3 model performed excellently，achieving a combined diagnostic accuracy of 91.7%，outperforming 71.7% of ChatGPT 4．In the image modality，both models had accuracies below 70%，but ChatGPT 4 exhibited higher sensitivity（78.3%），while Llama 3 demonstrated outstanding specificity（98.3%）．Subgroup analysis indicated that mammography performed better in non-dense breasts，whereas ultrasound was more advantageous in dense breasts．Conclusions  The large language models  still  require further optimization in medical image processing and multimodal integration，but fine-tuned large language models in the medical field show potential in handling unstructured clinical texts．

       目的   针对孤独症多模态证据融合与定量化辨识的关键问题，本研究提出基于图卷积神经网络（GCN）的孤独症谱系障碍（ASD）诊断模型研究思路。方法  通过对来源于ABIDE的ASD儿童脑部fMRI数据进行整理和筛选，提取脑区功能连接矩阵作为图结构的邻接矩阵，并融合临床表型数据，构建了ASD多模态关联网络。通过网络特征比较分析，识别出了ASD与典型发育组的脑功能连接网络组间差异。进一步地构建一个端到端的GCN模型，并尝试引入注意力机制，提高模型决策的可解释性。结果  该模型在诊断性能指标优于传统机器学习方法（准确率=0.710，精确率=0.709，召回率=0.780，F1=0.743，曲线下面积=0.746）。背侧注意网络与边缘系统-颞极枢纽的功能连接减弱是模型做出判断的最主要依据。结论  以异质图为多模态数据整合的基本架构，本模型为ASD的潜在病理机制探索提供了新的方法学范例。

      Objective   To develop a quantitative model for autism spectrum disorder（ASD）integration multimodal evidences．Methods The fMRI  dataset from ABIDE was  used for extracting connectivity function  network of ASD after  data preprocessing．Difference between ASD and typical development about their brain connectivity function was evaluated with t-test．Integrating phenotypic data and fMRI dataset，an graph convolutional neural network （GCN）with attention module was estimated and compared against benchmark models about their efficiency and interpretability．Results  The GCN model was evaluated outperformed other models with better accuracy indices．And regions from Dorsal Attention Network and Limbic-Temporal Pole were ranked as the highest weights for the differentiation in the model．Conclusions  This study provided a novel paradigm for quantitative diagnosis and exploring pathogenesis of ASD．

       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 基于Donabedian环节模型构建急诊脑出血患者护理质量评价体系, 并应用于临床,为急诊脑出血患者护理质量管理、监测与评价提供客观、科学的参考依据。方法 通过文献查阅、筛查与评价, 提取可行性资料, 基于Donabedian环节模型构建急诊脑出血患者护理质量评价体系的框架, 并采用德尔菲法完成两轮专家函询,确定最终的指标体系。选择2021年1月—2024年1月本院收治的230例急诊脑出血患者为研究对象, 将2021年1月—2022年6月作为干预前监测节点,该阶段的165例患者为传统组, 实施常规的护理质量管理;将2022年7月—2024年1月作为干预后监测节点,该阶段的165例患者为观察组, 实施以急诊脑出血患者护理质量评价指标进行护理质量监测管理。结果 两轮函询中专家积极系数分别为95%和100%, 意见提出率分别为56.25%和35.54%; 两轮函询专家权威系数为0.945、0.893; 第1轮函询中各项指标变异系数（CV）均值为0~0.136, Kendall’s W协调系数为0.065; 第2轮函询中变异系数（CV）均值为0~0.110, Kendall’s W协调系数为0.186。最终形成的急诊脑出血患者护理质量评价体系共涵盖一级指标3个、二级指标11个、三级指标55个。观察组入院-用药时间合格率、吞咽障碍患者动态评估率、气道管理合格率、早期被动/主动活动落实率高于传统组,差异具有统计学意义（χ²=14.850、12.261、8.183、37.420, P<0.05）, 观察组患者满意度明显高于传统组（χ²=14.049, P<0.001）。结论 本研究构建的急诊脑出血患者护理质量评价体系具有一定的科学性、可靠性和实用性, 可作为临床实现护理质量持续改进的重要评价工具。

Objective Based on the Donabedian model,the nursing quality evaluation system of emergency cerebral hemorrhage patients was constructed, and applied to clinical practice, providing an objective and scientific reference basis for realizing the nursing quality management, monitoring and evaluation of emergency cerebral hemorrhage patients．Methods Through literature review, screening and evaluation, the feasibility data was extracted, and the framework of the nursing quality evaluation system for patients with emergency cerebral hemorrhage was constructed based on the Donabedian model, and the Delphi method was adopted to complete two rounds of expert letter inquiry to determine the final index system．The study selected 230 patients with acute cerebral hemorrhage admitted to our hospital from January 2021 to January 2024 as the research subjects．The period from January 2021 to June 2022 was used as the pre-intervention monitoring period, during which 165 patients were in the traditional group, receiving routine nursing quality management．The period from July 2022 to January 2024 was used as the post-intervention monitoring period, during which 165 patients were in the observation group,implementing nursing quality monitoring and management based on evaluation indicators for the care of patients with acute cerebral hemorrhage．Results In the two rounds of letter inquiry, the positive coefficient of experts was 95% and 100%, respectively, and the rate of suggestions was 56.25% and 35.54%, respectively; the authority coefficient of experts in the two rounds of letter inquiry was 0.945 and 0.893．In the first round the mean value of coefficient of variation（CV）of each index was 0~0.136, and the coordination coefficient of Kendall’s W was 0.065; in the second round the mean value of variation coefficient（CV）was 0-0.110, and the coordination coefficient of Kendall's W was 0.186．The final nursing quality evaluation system for emergency cerebral hemorrhage patients covers 11 first-level indicators, 11 second-level indicators and 55 third-level indicators．The results showed that the pass rate of admission-medication time, dynamic assessment rate of dysphagia patients, airway management rate, and early passive / active activity implementation rate of the observation group were statistically significant different from those in the traditional group（χ²=14.850,12.261, 8.183, 37.420, P<0.05）, and the patient satisfaction in the observation group was significantly higher than that in the traditional group（χ²=14.049, P<0.001）．Conclusions The nursing quality evaluation system for emergency cerebral hemorrhage patients constructed in this study is scientific,reliable and practical, and can be used as an important evaluation tool to achieve continuous improvement of nursing quality in clinical practice．

心血管疾病是导致我国居民死亡的首要原因。在2006—2019年间,我国每年因心血管疾病死亡的人数从215万人增加到328万人。斑马鱼因个体小、成本低廉、体外发育、身体透明、基因组与人类高度同源等特点,近年来被广泛应用于医学研究。斑马鱼模型有利于推动心血管疾病领域的基础性研究。该文通过对前期研究进行综述,重点介绍了斑马鱼模型在心血管疾病中基因筛选、心脏再生、药物筛选、毒性评估等方面的研究进展。

Cardiovascular disease is the leading cause of death in China．Between 2006 and 2019,the annual number of deaths due to cardiovascular diseases increased from 2.15 million to 3.28 million．Zebrafish has been widely used in medical research in recent years because of its small individual size,low cost,in vitro development,transparent body and high homology of genome with human．The zebrafish model is conducive to promoting basic research in the field of cardiovascular disease．Based on the review of previous studies,this paper focuses on the research progress of zebrafish model in gene screening,cardiac regeneration,drug screening,toxicity assessment and other aspects of cardiovascular diseases．

伴随着对医疗领域人才水平要求的逐步提高,医院人力资源管理尤其是医院人才引进工作正在由规模化发展向精细化发展转变。当前医院人才引进过程中存在缺乏人力资源发展规划、高层次人才引进方法有待完善、人才管理能力亟须提高、科室用人需求脱离实际、忽视对于岗位胜任力的分析等问题。人力资源成熟度模型（People Capability Maturity Model,P-CMM）作为一种系统的管理理论,其具备很强的实践性,文章对人力资源成熟度模型在医院人才引进工作中的本土化应用进行相关讨论与研究,将P-CMM不同成熟度等级、过程域目标与医院人才引进工作相结合,并提出可操作性指导,具有一定的理论与实践价值。

With the gradual improvement of the requirements for talents in the medical field,hospital human resource management,especially the introduction of talents in hospitals,is changing from large-scale development to refined development．At present,there are some problems in the process of hospital talent introduction,such as lack of human resource development plan,improvement of high-level talent introduction method,improvement of talent management ability,separation of department employment demand from reality,neglect of post competency analysis,etc．People Capability Maturity Model（P-CMM）,as a systematic management idea,has strong practicality．This study discusses and studies the localization application of human resource maturity model in hospital talent introduction,combines different maturity levels and process area objectives of P-CMM with hospital talent introduction,and puts forward operational guidance It has certain theoretical and practical value．

目的 探讨与分析基于信息-动机-行为（IMB）模型的护理干预对造口患者并发症及生活质量的影响。方法 选择2021年5月—2023年4月本院进行结直肠癌行肠造口患者84例作为研究对象,根据1∶1随机电脑抽签分配原则把患者分为IMB组42例与常规组42例。常规组给予常规护理干预,IMB组在常规组护理的基础上给予基于IMB模型的护理干预,IMB组与常规组护理观察时间为3个月,观察与记录IMB组与常规组患者并发症、生活质量、心理状况、自我管理能力评分变化情况。结果 IMB组护理3个月期间的腹腔脓肿、肠梗阻、肺部感染、造口感染等并发症发生率为4.8%,与常规组的19.0%相比降低更多（P<0.05）。IMB组护理3个月期间的遵医依从性为100.0%,与常规组的90.5%相比提高更多（P<0.05）。护理3个月后IMB组的症状识别、症状处理、处理后评价等自我管理能力评分与常规组相比提高更多（P<0.05）。IMB组与常规组护理3个月后的焦虑评分与抑郁评分与护理前相比都有统计学意义的降低（P<0.05）,护理3个月后IMB组的焦虑评分、抑郁评分与常规组对比降低（P<0.05）。护理3个月后IMB组的总生活质量量表、症状子量表、症状量表、功能量表评分都与常规组相比提高（P<0.05）。结论 基于IMB模型的护理干预在造口患者的应用能提高遵医依从性,缓解焦虑与抑郁情绪,提高患者自我管理能力,从而可有效减少患者并发症的发生,促进提高患者的预后生活质量。

Objective To explore and analysis the effects of nursing intervention based on Information-Motivation-Behavioral（IMB）model on complications and quality of life of patients with stoma. Methods Eighty-four cases of patients with colorectal cancer undergoing enterostomy in our hospital from May 2021 to Aprilt 2023 were selected as the study subjects．According to the principle of 1∶1 random computer lottery,the patients were divided into IMB group（42 cases）and traditional group（42 cases）．The traditional group were given routine nursing intervention,and the IMB group were given nursing intervention based on the IMB model on the basis of the traditional group．The nursing observation time of the traditional group and IMB group were 3 months,the changes in complications,quality of life,psychological status,and self-management ability scores of patients were observed and recorded. Results The incidence of complications such as abdominal abscess,intestinal obstruction,pulmonary infection and stoma infection in IMB group during nursing were 4.8%,which were significantly lower than 19.0% in the traditional group（P<0.05）．The compliance of IMB group during nursing were 100.0%,which were significantly higher than 90.5% in the traditional group（P<0.05）．After nursing of 3 months,the scores of self-management ability such as symptom recognition,symptom treatment and post-treatment evaluation in IMB group were significantly higher than those in the traditional group（P<0.05）．The scores of anxiety and depression in the traditional group and IMB group after nursing of 3 months were significantly lower than those before nursing（P<0.05）,and the scores of anxiety and depression in the IMB group after nursing of 3 months were also significantly lower than those in the traditional group（P<0.05）．After nursing of 3 months,the scores of IMB group on function scale,symptom scale,symptom subscale and total quality of life scale were significantly higher than those of the traditional group（P<0.05）. Conclusions The application of nursing intervention based on the IMB model in patients with stoma can improve the compliance with medical treatment,reduce the occurrence of complications,improve the self-management ability of patients,relieve anxiety and depression,and continue to improve the prognosis and quality of life of patients．