目的评估不同剂量甘露醇喷洒于十二指肠乳头局部,预防内镜逆行胰胆管造影术(ERCP)后胰腺炎的临床疗效及安全性。方法回顾性分析2020年1月-2024年10月该院消化内科收治的138例成功完成ERCP的患者的临床资料。根据手术结束前喷洒不同剂量...目的评估不同剂量甘露醇喷洒于十二指肠乳头局部,预防内镜逆行胰胆管造影术(ERCP)后胰腺炎的临床疗效及安全性。方法回顾性分析2020年1月-2024年10月该院消化内科收治的138例成功完成ERCP的患者的临床资料。根据手术结束前喷洒不同剂量甘露醇,将患者分为4组:D1组(33例)喷洒20 mL 20%甘露醇溶液,D2组(37例)喷洒60 mL 20%甘露醇溶液,D3组(33例)喷洒100 mL 20%甘露醇溶液,C组(对照组,35例)未喷洒任何液体。比较4组患者术前12 h、术后12 h、术后24 h和术后48 h的白细胞(WBC)、C反应蛋白(CRP)和淀粉酶(AMS)水平变化情况;评估4组患者术后高淀粉酶血症(PEHA)和术后胰腺炎(PEP)的发生率,以及不良反应发生情况。结果术前12 h,4组间WBC、CRP和AMS水平比较,差异均无统计学意义(P>0.05)。术后12、24和48 h,D2组和D3组同时点WBC、CRP和AMS水平明显低于C组和D1组,差异均有统计学意义(P<0.05);D2组与D3组、C组与D1组同时点组间WBC、CRP和AMS水平比较,差异均无统计学意义(P>0.05)。术后,D2组和D3组PEHA发生率分别为:21.6%(8/37)和18.2%(6/33),明显低于C组的48.6%(17/35)和D1组的45.5%(15/33),差异均有统计学意义(P<0.05);D2组和D3组PEP发生率分别为:2.7%(1/37)和3.0%(1/33),低于C组的11.4%(4/35)和D1组的9.1%(3/33),但4组间比较,差异无统计学意义(P>0.05)。术后,D3组不良反应总发生率为45.5%(15/33),明显高于其他3组,差异有统计学意义(P<0.05);D2组不良反应总发生率为8.1%(3/37),但与C组和D1组比较,差异无统计学意义(P>0.05)。结论ERCP结束前于十二指肠乳头局部喷洒甘露醇60和100 mL,均能明显降低患者术后WBC、CRP、AMS水平和PEHA发生率,且对PEP具有一定的预防作用,而60 mL为更优剂量选择,不良反应少,且安全性高。展开更多
Postoperative infection is a major global health concern,affecting 5%-10%of surgical patients and nearly doubling mortality in severe cases[1].Transplant recipients are particularly vulnerable,with 30%-80%developing i...Postoperative infection is a major global health concern,affecting 5%-10%of surgical patients and nearly doubling mortality in severe cases[1].Transplant recipients are particularly vulnerable,with 30%-80%developing infections within 30 days,often from opportunistic pathogens[2,3].Key risk factors include epidemiological exposure,net immunosuppression,age,transplant type,and surgical history[4].Despite known infection risks,current evidence remains transplantation type-specific and neglects behavioral modulators[5].Different types of transplantation may share similar risk factors[6].To identify common factors affecting postoperative infection,this study collected standardized clinical data-including diet,psychological response,medication use,and biochemical indicators-from liver and kidney transplant patients across six hospitals using a unified standard operating procedure(SOP).展开更多
Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategie...Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.展开更多
文摘目的评估不同剂量甘露醇喷洒于十二指肠乳头局部,预防内镜逆行胰胆管造影术(ERCP)后胰腺炎的临床疗效及安全性。方法回顾性分析2020年1月-2024年10月该院消化内科收治的138例成功完成ERCP的患者的临床资料。根据手术结束前喷洒不同剂量甘露醇,将患者分为4组:D1组(33例)喷洒20 mL 20%甘露醇溶液,D2组(37例)喷洒60 mL 20%甘露醇溶液,D3组(33例)喷洒100 mL 20%甘露醇溶液,C组(对照组,35例)未喷洒任何液体。比较4组患者术前12 h、术后12 h、术后24 h和术后48 h的白细胞(WBC)、C反应蛋白(CRP)和淀粉酶(AMS)水平变化情况;评估4组患者术后高淀粉酶血症(PEHA)和术后胰腺炎(PEP)的发生率,以及不良反应发生情况。结果术前12 h,4组间WBC、CRP和AMS水平比较,差异均无统计学意义(P>0.05)。术后12、24和48 h,D2组和D3组同时点WBC、CRP和AMS水平明显低于C组和D1组,差异均有统计学意义(P<0.05);D2组与D3组、C组与D1组同时点组间WBC、CRP和AMS水平比较,差异均无统计学意义(P>0.05)。术后,D2组和D3组PEHA发生率分别为:21.6%(8/37)和18.2%(6/33),明显低于C组的48.6%(17/35)和D1组的45.5%(15/33),差异均有统计学意义(P<0.05);D2组和D3组PEP发生率分别为:2.7%(1/37)和3.0%(1/33),低于C组的11.4%(4/35)和D1组的9.1%(3/33),但4组间比较,差异无统计学意义(P>0.05)。术后,D3组不良反应总发生率为45.5%(15/33),明显高于其他3组,差异有统计学意义(P<0.05);D2组不良反应总发生率为8.1%(3/37),但与C组和D1组比较,差异无统计学意义(P>0.05)。结论ERCP结束前于十二指肠乳头局部喷洒甘露醇60和100 mL,均能明显降低患者术后WBC、CRP、AMS水平和PEHA发生率,且对PEP具有一定的预防作用,而60 mL为更优剂量选择,不良反应少,且安全性高。
基金the MOST Key Research and Development Program of China(grant number 2022YFC2304703)the Natural Science Foundation of China(grant number 32422004)+5 种基金The Medicine and Engineering Interdisciplinary Research Fund of Shanghai Jiao Tong University(grant number 24X010301328)the Natural Science Foundation of China(grant number 32270202)the Computational Biology Program of Science and Technology Commission of Shanghai Municipality(STCSM)(grant number 25JS2810200)the MOST Key Research and Development Program of China(grant number 2020YFA0907200)Program of Shanghai Academic Research Leader(grant number 23XD1422300)Innovative research team of high-level local universities in Shanghai.All funding sources are attributed to N.N.L.
文摘Postoperative infection is a major global health concern,affecting 5%-10%of surgical patients and nearly doubling mortality in severe cases[1].Transplant recipients are particularly vulnerable,with 30%-80%developing infections within 30 days,often from opportunistic pathogens[2,3].Key risk factors include epidemiological exposure,net immunosuppression,age,transplant type,and surgical history[4].Despite known infection risks,current evidence remains transplantation type-specific and neglects behavioral modulators[5].Different types of transplantation may share similar risk factors[6].To identify common factors affecting postoperative infection,this study collected standardized clinical data-including diet,psychological response,medication use,and biochemical indicators-from liver and kidney transplant patients across six hospitals using a unified standard operating procedure(SOP).
基金funding from the China National Key Research and Development Program(No.2023YFC3603104)the National Natural Science Foundation of China(Nos.82472243 and 82272180)+6 种基金the Fundamental Research Funds for the Central Universities(No.226-2025-00024)the Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China(No.LHDMD24H150001)the Key Research&Development Project of Zhejiang Province(No.2024C03240)a collaborative scientific project co-established by the Science and Technology Department of the National Administration of Traditional Chinese Medicine and the Zhejiang Provincial Administration of Traditional Chinese Medicine(No.GZY-ZJ-KJ-24082)he General Health Science and Technology Program of Zhejiang Province(No.2024KY1099)the Project of Zhejiang University Longquan Innovation Center(No.ZJDXLQCXZCJBGS2024016)Wu Jieping Medical Foundation Special Research Grant(No.320.6750.2024-23-07).
文摘Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.
