Identification of clinical subphenotypes of sepsis after laparoscopic surgery

Objective:Some patients exhibit septic symptoms following laparoscopic surgery,leading to a poor prognosis.Effective clinical subphenotyping is critical for guiding tailored therapeutic strategies in these cases.By identifying predisposing factors for postoperative sepsis,clinicians can implement targeted interventions,potentially improving outcomes.This study outlines a workflow for the subphenotype methodology in the context of laparoscopic surgery,along with its practical application.Methods:This study utilized data routinely available in clinical case systems,enhancing the applicability of our findings.The data included vital signs,such as respiratory rate,and laboratory measures,such as blood sodium levels.The process of categorizing clinical routine data involved technical complexities.A correlation heatmap was used to visually depict the relationships between variables.Ordering points were used to identify the clustering structure and combined with Consensus K clustering methods to determine the optimal categorization.Results:Our study highlighted the intricacies of identifying clinical subphenotypes following laparoscopic surgery,and could thus serve as a valuable resource for clinicians and researchers seeking to explore disease heterogeneity in clinical settings.By simplifying complex methodologies,we aimed to bridge the gap between technical expertise and clinical application,fostering an environment where professional medical knowledge is effectively utilized in subphenotyping research.Conclusion:This tutorial could primarily serve as a guide for beginners.A variety of clustering approaches were explored,and each step in the process contributed to a comprehensive understanding of clinical subphenotypes.

Real-time embedded software testing method based on extended finite state machine

The reliability of real-time embedded software directly determines the reliability of the whole real-time embedded sys- tem, and the effective software testing is an important way to ensure software quality and reliability. Based on the analysis of the characteristics of real-time embedded software, the formal method is introduced into the real-time embedded software testing field and the real-time extended finite state machine （RT-EFSM） model is studied firstly. Then, the time zone division method of real-time embedded system is presented and the definition and description methods of time-constrained transition equivalence class （timeCTEC） are presented. Furthermore, the approaches of the testing sequence and test case generation are put forward. Finally, the proposed method is applied to a typical avionics real- time embedded software testing practice and the examples of the timeCTEC, testing sequences and test cases are given. With the analysis of the testing result, the application verification shows that the proposed method can effectively describe the real-time embedded software state transition characteristics and real-time requirements and play the advantages of the formal methods in accuracy, effectiveness and the automation supporting. Combined with the testing platform, the real-time, closed loop and automated simulation testing for real-time embedded software can be realized effectively.

老年重症患者骨质流失相关危险因素分析

目的探讨老年重症患者骨质流失的相关危险因素。方法纳入2020年7月至2021年7月浙江大学医学院附属金华医院收治的老年重症患者,测量其入住ICU前后的骨密度数据,T值下降>10%为存在骨质流失。先采用t检验、秩和检验、χ^(2)检验比较骨质流失组与对照组临床资料的差异,再通过多因素logistic回归分析骨质流失的相关危险因素。结果共纳入老年重症患者71例,骨质流失组41例,对照组30例。与对照组比较,骨质流失组入院时氧合指数较低、序贯器官衰竭评估评分较高、接受连续性肾脏替代治疗患者的比例较高、机械通气时间及制动时间均较长(t=-3.516,χ^(2)=8.019,Z=-3.990、-3.161、-2.056,P<0.05或0.01)。两组患者入ICU时实验室检查指标中仅白细胞计数、C反应蛋白、白介素-6的差异有统计学意义(t=2.682,Z=-3.108、3.307,P<0.01)。多因素分析结果显示,引起患者骨质流失的相关危险因素包括入ICU时SOFA评分高、白介素-6水平高,住ICU期间行CRRT以及机械通气时间长(OR=1.223、1.080、6.635、1.004,P<0.05)。结论老年重症患者住ICU期间发生骨质流失的风险较高,引起骨质流失相关的危险因素包括入ICU时SOFA评分高、白介素-6水平高,住ICU期间进行CRRT以及机械通气时间长。