1.Countermeasures for invasive catheter infections in neurosurgical intensive care unit
Yunxia ZHAI ; Danfen ZHANG ; Lin JIA
Modern Clinical Nursing 2014;(6):12-14
Objective To study the characteristics of invasive catheter infection in neurosurgery intensive care unit (NICU) to provide theoretical basis for the prevention of the infections.Method A retrospective analysis was done into the clinical data of 563 patients with indwelling catheter from January 2011 to December 2012 in our department.Results Among 563 cases undergoing invasive catheteration,there were 106 cases of catheter-associated infections with an incidence of 18.8%. The urinary catheter-associated infection was 24.5% and epidural drainage catheter-associated infection was 16.9%.Conclusion The enhanced consciousness of critical catheter infections,abiding by principles for aseptic operation and strengthened nursing to catheters or tubes are critical for reducing the incidence of invasive catheter-associated infections and ensuring the safety patients.
2.Construction of a predictive diagnostic model for pulmonary aspergillosis using GM test combined with serum albumin
Yunxia ZHAI ; Ping XU ; Jing ZHAO ; Jing XUE ; Fanghua LI ; Jin LI
International Journal of Laboratory Medicine 2024;45(21):2566-2571,2576
Objective To evaluate the biochemical indicators,nutritional status,and immune levels of pa-tients with pulmonary aspergillosis(PA)and other pulmonary diseases,and to construct a predictive model for PA so as to improve the diagnostic efficacy of clinical PA.Methods A total of 40 PA patients and 39 pa-tients with other pulmonary diseases who were hospitalized in the hospital from January 2020 to August 2022 were retrospectively analyzed.The expression trends and differences of serum 1,3-β-D Glucan(G test),galac-tomannan test(GM test),biochemical indexes,blood routine indexes and immune cell subsets were analyzed and compared.The receiver operating characteristic(ROC)curve and binary Logistic regression analysis were used to construct the predictive model for PA by the combination of clinical indicators.Results Serum GM test,G test,albumin,hemoglobin,hematocrit,lymphocytes,B lymphocytes,CD44 T lymphocytes and CD4/CD8 ratio displayed significant differences between PA patients and patients with other lung disease(P<0.05).The levels of GM test in alveolar lavage fluid of PA patients were significantly higher than that in the serum,and the differences were statistically significant(P<0.05).The ROC curve analysis showed that the GM test,as an independent predictor of PA,had good predictive accuracy[0.85<area under the curve(AUC)<0.95].Besides,albumin,natural killev cells,CD4+T lymphocytes and CD4/CD8 ratio had general predictive efficacy(0.70<AUC<0.85).The prediction efficacy of G test and B lymphocytes was poor(AUC<0.70).The Logistic regression analysis showed that the combination of GM test and serum albumin could construct the optimal prediction model,and the prediction formula of the combined model was as fol-lows:Logit(P)=17.781× GM-0.131×albumin+1.394.The prediction accuracy of the combined model was 0.924(95%CI:0.865-0.982),the sensitivity was 87.5%,the specificity was 81.2%,and the cut off value was 17.781×GM-0.131×albumin-1.735.Conclusion This study retrospectively analyzed the differences in various clinical indicators between patients with PA and patients with other pulmonary diseases,and then screen the key clinical indicators as candidate predictors which displayed significantly different ex-pression between the two groups.The optimal prediction model for the diagnosis of PA is constructed by the combination of GM test and serum albumin through ROC curve and Logistic regression analysis.This model may significantly improve the diagnostic efficiency of PA in clinical,and provide the reference for the early di-agnosis and effective treatment of PA patients.
3.Application progress of latent class growth models in dynamic prevention and control strategies for acquired immunodeficiency syndrome
Mimi ZHAI ; Yamin LI ; Sushun LIU ; Yunxia LI ; Yiting LIU ; Li LI ; Xianyang LEI
Journal of Central South University(Medical Sciences) 2024;49(4):621-627
The prevention and control requirements for HIV/AIDS vary significantly among different populations,posing substantial challenges to the formulation and implementation of intervention strategies.Dynamically assessing the heterogeneity and disease progression trajectories of various groups is crucial.Latent class growth model(LCGM)serves as a statistical approach that fits a longitudinal data into N subgroups of individual development trajectories,identifying and analyzing the progression paths of different subgroups,thereby offering a novel perspective for disease control strategies.LCGM has shown significant advantages in the application of HIV/AIDS prevention and control,especially in gaining a deeper understanding and analysis of epidemiological characteristics,risk behaviors,psychological research,heterogeneity in testing,and dynamic changes.Summarizing the advantages and limitations of applying LCGM can provide a reliable basis for precise prevention and control of HIV/AIDS.