1.Changes of CD4+ CD25+ CD127low regulatory T cells in peripheral blood samples collected from the patients with cervical cancer and its clinical significance
Jianying ZHANG ; Ban LIU ; Yimin ZHANG ; Jie WU ; Jing ZHU ; Zhiwen PAN ; Juan XIONG ; Wenhu CHEN
Chinese Journal of Microbiology and Immunology 2015;35(10):753-758
Objective To investigate the changes of CD4+ CD25+ CD127low regulatory T cells (Treg) in peripheral blood samples collected from the patients with cervical cancer and its clinical signifi -cance , and to evaluate the correlations between Treg cells and the infection of high-risk human papillomavir-us ( HR-HPV) .Methods Flow cytometry analysis was performed to measure the percentages of CD4+ CD25+ CD127low Treg cells among CD4+T cells in peripheral blood samples collected from 249 patients with cervical cancer , 30 patients with cervix intraepithelial neoplasia ( CIN) and 60 healthy subjects .The corre-lations between the levels of Treg cells and the clinicopathological features of cervical cancer were analyzed . Flow-through hybridization and gene chip technology ( HybriMax) were used to analyze the genotypes of HPV strains isolated from the 339 subjects.The correlations between Treg cells and HR-HPV infection were ana-lyzed.Results Compared with the healthy subjects , the patients with cervical cancer or CIN showed higher percentages of CD4+ CD25+ CD127low Treg cells and rates of HR-HPV infection (P<0.01).The percentages of CD4+ CD25+ CD127low Treg cells in patients with cervical cancer were significantly correlated with the sta-ges of cervical cancer , which was staged by the Federation International of Gynecology and Obstetrics (FIGO) staging system,and the degrees of differentiation (P<0.05).The percentages of CD4+ CD25+ CD127low Treg cells in the peripheral blood of patients with positive HR-HPV were significantly higher than those in patients without HR-HPV infection (P<0.01).Conclusion The CD4+ CD25+ CD127low Treg cells in peripheral blood might play an important role in the oncogenesis and development of cervical carcinoma , thus it could be used as a potential marker for the evaluation of disease progression .Moreover , the CD4+ CD25+ CD127low Treg cells were closely related to the HR-HPV infection.
2.Clinical Results of Surgical Treatment for Lumbar Spinal Canal Stenosis
Cuoping CHEN ; Yucai FEN ; Yuqiang GU ; Wenhu ZHU ; Ronghao CHEN ; Qiuhua GU ; Xiaoxiang ZHOU ; Yongsheng SONG ; Yaohui HUN
Journal of Medical Research 2009;38(8):66-68
Objective To investigate the surgical outcome of lumbar spinal canal stenosis. Methods Forward analysis of 160 cases of the patients with lumbar spinal canal stenosis getting operative treament was performed. 87 cases were male and 73 case were female. The average age was 51 years old (18 ~ 78years old). The average course of deseases was 5 years (1 month ~ 36years). All of the cases used lumbar spinal canal decompression combined with pedicle screws fixation and posterolateral bone graft. All cases had a follow - up of 3 months to 5 years (mean 34 months). Results The (COA) recovery rate among the tolal patients was cassified as exellent in 120 ca-ses , good in 31 cases , fair in 7 cases. The excellent and good rate was 94.4%. Conclusion The operative intervention was an effective method for patients with severe or progressive clinical lumbar spinal canal stenosis. The procedure in decompressed compretely through pos-terior approach and the instability of cerrical apinein had the satisfactory clinical outcome.
3.Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020.
Longxiang SU ; Xudong MA ; Sifa GAO ; Zhi YIN ; Yujie CHEN ; Wenhu WANG ; Huaiwu HE ; Wei DU ; Yaoda HU ; Dandan MA ; Feng ZHANG ; Wen ZHU ; Xiaoyang MENG ; Guoqiang SUN ; Lian MA ; Huizhen JIANG ; Guangliang SHAN ; Dawei LIU ; Xiang ZHOU
Frontiers of Medicine 2023;17(4):675-684
This study aimed to explore key quality control factors that affected the prognosis of intensive care unit (ICU) patients in Chinese mainland over six years (2015-2020). The data for this study were from 31 provincial and municipal hospitals (3425 hospital ICUs) and included 2 110 685 ICU patients, for a total of 27 607 376 ICU hospitalization days. We found that 15 initially established quality control indicators were good predictors of patient prognosis, including percentage of ICU patients out of all inpatients (%), percentage of ICU bed occupancy of total inpatient bed occupancy (%), percentage of all ICU inpatients with an APACHE II score ⩾15 (%), three-hour (surviving sepsis campaign) SSC bundle compliance (%), six-hour SSC bundle compliance (%), rate of microbe detection before antibiotics (%), percentage of drug deep venous thrombosis (DVT) prophylaxis (%), percentage of unplanned endotracheal extubations (%), percentage of patients reintubated within 48 hours (%), unplanned transfers to the ICU (%), 48-h ICU readmission rate (%), ventilator associated pneumonia (VAP) (per 1000 ventilator days), catheter related blood stream infection (CRBSI) (per 1000 catheter days), catheter-associated urinary tract infections (CAUTI) (per 1000 catheter days), in-hospital mortality (%). When exploratory factor analysis was applied, the 15 indicators were divided into 6 core elements that varied in weight regarding quality evaluation: nosocomial infection management (21.35%), compliance with the Surviving Sepsis Campaign guidelines (17.97%), ICU resources (17.46%), airway management (15.53%), prevention of deep-vein thrombosis (14.07%), and severity of patient condition (13.61%). Based on the different weights of the core elements associated with the 15 indicators, we developed an integrated quality scoring system defined as F score=21.35%xnosocomial infection management + 17.97%xcompliance with SSC guidelines + 17.46%×ICU resources + 15.53%×airway management + 14.07%×DVT prevention + 13.61%×severity of patient condition. This evidence-based quality scoring system will help in assessing the key elements of quality management and establish a foundation for further optimization of the quality control indicator system.
Humans
;
China/epidemiology*
;
Cross Infection/epidemiology*
;
Intensive Care Units/statistics & numerical data*
;
Quality Control
;
Quality Indicators, Health Care/statistics & numerical data*
;
Sepsis/therapy*
;
East Asian People/statistics & numerical data*