1.Development of X-ray shelter in S95-100
Meisheng SHI ; Ruimin XIE ; Lucheng YAO
Chinese Medical Equipment Journal 2004;0(08):-
From the aspects of the selections of the devices, the design of the shelter, the internal layout and the protection against X-ray, this paper mainly discusses the development of X-ray shelter in S950-100. A series of experiments show that this shelter can meet the requirements of the tactical and technological indexes and the medical service. This shelter also proves reliable and advanced.
2.Relationships between tau and brain atrophy in Alzheimer′s disease based on 18F-THK5317 PET/MR
Liping FU ; Xiaojun ZHANG ; Teng XIE ; Ruimin WANG ; Fang YI ; Jinming ZHANG ; Luning WANG ; Hengge XIE ; Baixuan XU ; Jiahe TIAN
Chinese Journal of Nuclear Medicine and Molecular Imaging 2021;41(6):321-326
Objective:To investigate the neuroimaging relationship between tau protein deposition and brain atrophy, and assess their relationships with cognitive decline in Alzheimer′s disease (AD) patients.Methods:From April 2017 to October 2019, 26 AD patients (12 males, 14 females, age (70.7±12.2) years) and 19 cognitively normal controls (CN; 9 males, 10 females, age (65.6±8.1) years) in Chinese PLA General Hospital were retrospectively enrolled. All subjects received (S)-6-[(3- 18F-fluoro-2-hydroxy)propoxy]-2-(4-methylaminophenyl)quinoline ( 18F-THK5317) PET/MR and the standardized uptake value ratio (SUVR) and gray matter volume (GMV) were measured. General linear model (GLM) was used to evaluate the differences of SUVR and GMV between two groups. Pearson correlation analysis was used to assess the relationships between SUVR and GMV, and relationships of SUVR and GMV with Mini-Mental State Examination (MMSE) scores in AD patients. Results:Compared with CN, the AD patients showed significantly increased 18F-THK5317 retention in lateral temporal, frontal, posterior cingulated/precuneus and occipital cortex with significant differences of SUVR between two groups (2.18±0.54 vs 1.78±0.09, 2.13±0.50 vs 1.82±0.06, 2.03±0.45 vs 1.69±0.08, 2.18±0.57 vs 1.76±0.10, t values: 2.58-6.57, all P<0.001). The AD patients also showed decreased GMV in medial temporal, posterior cingulated/precuneus and orbitofrontal cortex ( t values: 3.67-8.85, all P<0.001). In AD patients, SUVR was negatively associated with GMV in bilateral lateral temporal cortex, pre-frontal cortex and orbital frontal cortex ( r values: from -0.52 to -0.43, all P<0.05). Both SUVR ( r=-0.599, P=0.001) and GMV ( r=0.443, P=0.023) were significantly correlated with MMSE scores in AD patients. Conclusion:AD patients have neocortical 18F-THK5317 abnormal uptake and GMV reduction, which are significantly correlated with cognitive decline.
3. Association between the JAG2 gene polymorphism and the occurrence of nonsyndromic cleft lip with or without cleft palate in northwest Chinese population
Jie LEI ; Xi SHEN ; Boshi BI ; Sixuan ZHAO ; Ruimin LIU ; Xiaodong XIE
Chinese Journal of Medical Genetics 2020;37(1):75-79
Objective:
To assess the association of
4.Development of acute kidney injury prognostic model for critically ill patients based on MIMIC-Ⅲ database
Min LI ; Huyong YANG ; Weiwei YANG ; Baohua WEI ; Yuming ZHANG ; Ruimin XIE ; Pei CHU
Chinese Critical Care Medicine 2021;33(8):949-954
Objective:To investigate the risk factors affecting the prognosis of patients with acute kidney injury (AKI) in the intensive care unit (ICU) based on the Medical Information Mart for Intensive Care Ⅲ (MIMIC-Ⅲ) database, and to establish a prognostic model for AKI.Methods:Patients (aged ≥ 18 years) with acute renal failure, admitted to the ICU for the first time, and had complete hospital records (the RIFLE diagnostic criteria were used in the database, and the diagnosis was expressed as AKI in this article) were screened from MIMIC-Ⅲ database according to diagnostic codes. Patients were divided into two groups based on survival state at discharge, and the general information, underlying diseases, injury factors, vital signs and laboratory indicators within 24 hours after AKI, related intervention and prognostic indicators were analyzed. Univariate and multivariate Logistic regression analysis were used to determine the risk factors affecting mortality in patients with AKI and established a prediction model. The receiver operator characteristic curve (ROC curve) was used to analyze the predictive value of the prediction model for the prognosis of AKI patients.Results:There were 4 554 patients with AKI included and 862 died, with mortality of 18.93%. Univariate Logistic regression analysis was performed for factors that might be associated with death in AKI patients, and the results showed that age, hypertension, lymphoma, metastatic carcinoma, vancomycin, aspirin, coagulation abnormalities, cardiac arrest, sepsis or septic shock, invasive mechanical ventilation, white blood cell count (WBC), platelet count (PLT), K +, blood urea nitrogen (BUN), total bilirubin (TBil), renal replacement therapy (RRT) and length of stay (LOS) were independent risk factors [odds ratio ( OR) and 95% confidence interval (95% CI) were 1.002 (1.001-1.003), 0.764 (0.618-0.819), 1.749 (1.112-2.752), 2.606 (1.968-3.451), 1.779 (1.529-2.071), 0.689 (0.563-0.842), 1.871 (1.590-2.201), 2.468 (1.209-5.036), 2.610 (2.226-3.060), 2.154 (1.853-2.505), 1.105 (1.009-1.021), 0.998 (0.997-0.998), 1.132 (1.057-1.212), 1.008 (1.006-1.011), 1.061 (1.049-1.073), 2.142 (1.793-2.997), 0.805 (0.778-1.113), all P < 0.05]. Further binary Logistic regression analysis showed that lymphoma, metastatic cancer, vancomycin, cardiac arrest, sepsis or septic shock, coagulation dysfunction, invasive mechanical ventilation, increased BUN, increased TBil, increased or decreased blood K + and increased WBC were independent risk factors for death [β values were 0.636, 1.005, 0.207, 0.894, 0.787, 0.346, 0.686, 0.006, 0.051, 0.085, and 0.009; OR and 95% CI were 1.889 (1.177-3.031), 2.733 (2.027-3.683), 1.229 (1.040-1.453), 2.445 (1.165-5.133), 2.197 (1.850-2.610), 1.413 (1.183-1.689), 1.987 (1.688-2.338), 1.006 (1.003-1.009), 1.052 (1.039-1.065), 1.089 (1.008-1.176), and 1.009 (1.004-1.015), respectively, all P < 0.05]. The Hosmer-Lemeshow test showed that the AKI prognostic model was able to fit the observed data well ( P = 0.604). ROC curve analysis showed that the area under ROC curve (AUC) of the AKI prognostic model was 0.716 (95% CI was 0.697-0.735), when the cut-off value was 0.320, the sensitivity was 71.9%, the specificity was 60.1%, the positive likelihood ratio was 1.80, and the negative likelihood ratio was 0.47. Conclusion:The prognostic prediction model of AKI in critically ill patients established and based on the MIMIC-Ⅲ database may have practical significance for prognostic risk assessment of AKI and later intervention.