1.Value of HBP in diagnosis of catheter-related infections in maintenance hemodialysis patients
Cong LIN ; Xiaoqing HU ; Junxi WANG
International Journal of Laboratory Medicine 2017;38(13):1776-1778
Objective To investigate the diagnostic value of Heparin-binding protein (HBP) in maintenance hemodialysis patients in catheter-related infections.Methods 75 patients with maintenance hemodialysis were enrolled in the study and divided into observation group(n=45,with catheter-related infections) and control group(n=45,without catheter-related infections).The serum HBP,procalcitonin (PCT) and C-reactive protein (CRP) levels were detected.The values in diagnostic of catheter-related infections and Gram-negative bacterial infections were analyzed by receiver operating characteristic(ROC) curve.Results There were 34 cases of patients infected by Gram-positive bacterial with the rate of 75.6% and 11 cases of patients infected by Gram-negative bacterial with rate of 24.4%.The serum HBP,PCT and CRP levels in observation group were significantly higher than those in control group and the serum HBP,PCT levels of patients infected by Gram-negative bacterial were higher than those of patients infected by Gram-positive bacterial (P<0.05).The area under curves of HBP,PCT,CRP in diagnosis of catheter-related infections were 0.955,0.890,0.871 with sensitivity of 86.7%,88.9%,62.2% and specificity of 93.3%,73.3%,93.3%.The value of HBP in diagnosis of Gram-negative bacteria infections was better than PCT and CRP.The area under ROC was 0.818 and the cut off value was HBP>27.52 μg/L with sensitivity of 100.0% and specificity of 61.8%.Conclusion Serum HBP,PCT and CRP may be the effective indicators for diagnosis of catheter-related infections,and the HBP has important reference value for diagnosis of Gram-negative bacterial infections.
2.Analysis of causes of epilepsy in 5572 cases
Xiangshu HU ; Hua LI ; Fangming DIAO ; Lingxia FEI ; Wei ZHANG ; Zhongjie CHEN ; Peiqi ZHANG ; Junxi CHEN ; Qinghua TAN ; Qiao CHEN ; Xinyan WU ; Jinhua ZHOU ; Dan ZHU ; Dinglie SHEN
Chinese Journal of Neurology 2012;45(4):244-248
Objective To explore the common causes of epilepsy and the etiologic characteristics in different age groups of patients with epilepsy.Methods A retrospective survey was made in 5572 epilepsy patients in Epileptic Center of Guangdong 999 Brain Hospital from January 2003 to December 2009.According to the diagnostic criteria published in 2005 from ILAE,all the diagnoses of 5572 cases were made by epileptic specialists.Based on history,cranial MRI or CT and pathologic data,causes of epilepsy were classified into idiopathic,symptomatic and cryptogenic epilepsy.The cases of symptomatic epilepsy were further arranged into different categories in different age grades,such as head trauma,perinatal injuries,infection in central nervous system, cerebral vascular disease, brain tumor, disorders of cortical development,neurocutaneous syndrome and others.The cases with febrile seizures and family history were collected,and positive ratio of febrile seizures and family history were contrasted in different categories of cases by Kruskal-Wallis test ( nonparametric test ).Results In 5572 cases,66 were idiopathic,2834 symptomatic,2672 cryptogenic,and the ratio of these causes was 1%,51%,48% respectively.Among 2834 cases of symptomatic epilepsy,822 were head trauma,497 were perinatal injuries,360 were infection in central nervous system,249 were brain tumor,150 were cerebral vascular disease,135 were disorders of cortical development,62 were neurocutaneous syndrome and 559 were others. In brief,head trauma,perinatal injuries,infection in central nervous system,brain tumor and cerebral vascular disease were top 5 causes of symptomatic epilepsy. Hippocampal sclerosis was found in 744 cases in those of eryptogenic epilepsy.The importance of febrile seizures( idiopathic:15.2% ( 10/66 ),symptomatic:6.5% ( 185/2834 ),cryptogenic:9.4% ( 250/2672 ) ; x2 =181.393,P =0.000 ) and family history ( idiopathic:83.3% ( 55/66 ),symptomatic:1.1% (31/2834),cryptogenic:0.4% (12/2672) ; x2 =68.354,P =0.000) was statistically different in different causes of epilepsy.Febrile seizures was the most frequent in cases with hippocampal sclerosis than those with other causes,and family history was the most frequent in neurocutaneous syndrome in symptomatic cases.Perinatal injurics was thc first causc in cases of infancy and childhood,head trauma was the top one in those of juvenile and adulthood,and cerebral vascular disease was the main cause in senile cases. Conclusions In the whole epileptic cases of 5572, 1% was idiopathic,51% was symptomatic,and 48% cryptogenic. The main causes of them were head trauma,perinatal injuries,infection in central nervous system,brain tumor,and cerebral vascular disease.
3.Analysis of clinical characteristics and related influencing factors of patients with early-onset gout
Lihui CHEN ; Si CHEN ; Fengjing LIU ; Zhumeng HU ; Ying HAN ; Mian WU ; Yiwen MA ; Junxi LU ; Haibing CHEN
Chinese Journal of Endocrinology and Metabolism 2020;36(9):767-772
Objective:To investigate the clinical features and influencing factors of early-onset gout.Methods:Male patients with gout admitted to Department of Endocrinology and Metabolism were recruited from 2015 to 2018. Patients with gout onset before age 30 were defined as the " early-onset" group, and those with onset at 30~60 years were defined as the "late-onset" group. Clinical characteristics were compared between two groups. Factors associated with early-onset gout were analyzed.Results:A total of 1 243 male patients were enrolled in this study; 480 individuals were in the early-onset, and 763 in the late-onset groups. Compared with the late-onset group, patients with early-onset gout had higher consumption rates of sugar-sweetened beverage(28.0% vs 15.0%, P=0.001), a higher homeostasis model assessment for insulin resistance level(3.78±2.93 vs 3.10±2.39, P<0.01), and larger proportions of family histories of diabetes(30.8% vs 20.4%, P<0.01)and hypertension(51.2% vs 42.6%, P=0.003). Logistic regression analysis showed that factors associated with early-onset gout were drinking sugar-sweetened beverage( P=0.012), family history of diabetes( P=0.037). Conclusion:Early-onset gout was associated with a family history of diabetes. Patients with family histories of diabetes are more likely to have early-onset gout, which may be associated with a common genetic basis.
4.AIDS discrimination in junior college students and the effect of AIDS knowledge on discrimination
Chinese Journal of School Health 2020;41(2):209-212
Objective:
To analyze the situation of AIDS knowledge and discrimination among freshmen in Chengdu city, and to explore possible effects of AIDS knowledge on discrimination.
Methods:
A cluster random sampling was employed to investigate 1 053 college students from 11 universities in Chengdu about their HIV/AIDS knowledge and discrimination. The scores of AIDS knowledge and discrimination of students with different characteristics were analyzed, and the influence path of AIDS knowledge on AIDS discrimination were further analyzed based on different peer relationships.
Results:
The total scores of AIDS knowledge was negatively correlated to AIDS discrimination( r s =-0.13, P <0.01). After adjusting for confounding factors, the total score of AIDS knowledge was associated with the total score of AIDS discrimination( β =-0.12, P <0.01). AIDS knowledge played a role in AIDS discrimination in intimate, general and unfamiliar peer relationships, with standardized path coefficients of -0.20, -0.24 and -0.18 respectively( P <0.01).
Conclusion
AIDS knowledge are correlated with discrimination among freshmen under different peer relationships. More anti-AIDS discrimination courses should be added to AIDS education to reduce the students’ fear and stigma of HIV/AIDS patients and related risk groups.
5.Application of three-dimensional computed tomography-bronchography and angiography combined with indocyanine green reverse staining in video-assisted thoracic segmentectomy
Junxi HU ; Xianglong GAO ; Hao KONG ; Yusheng SHU
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2022;29(10):1290-1295
Objective To evaluate the security and clinical value of the combination of three-dimensional computed tomography-bronchography and angiography (3D-CTBA) and indocyanine green (ICG) staining in video-assisted thoracic surgery (VATS) segmentectomy. Methods The clinical data of 125 patients who received VATS segmentectomy from January 2020 to January 2021 in our hospital were retrospectively analyzed. There were 40 (32.0%) males and 85 (68.0%) females with an average age of 54.8±11.1 years. Results The procedure was almost identical to the preoperative simulation. All intersegment planes were displayed successfully by ICG reverse staining method. There was no allergic patient. A total of 130 pathological specimens were obtained from the 125 patients. The mean operation time was 126.8±41.9 min, the time of first appearance of fluorescence was 22.7±4.9 s, the mean mark time was 65.6±20.3 s, the median blood loss was 20.0 (10.0-400.0) mL, the postoperative hospital stay was 5.6 (4.0-28.0) d, and the postoperative retention of chest tube time was 3.2 (2.0-25.0) d. Pathological results showed that microinvasive adenocarcinoma was the most common type (38.5%, 50/130), followed by invasive adenocarcinoma (36.9%, 48/130); there were 3 metastatic tumors (3/130, 2.3%). Conclusion The combination of 3D-CTBA and ICG reverse staining is proved to be a safe, necessary and feasible method. It solves the difficult work encountered in the procedure of segmentectomy, and it is worth popularizing and applying in clinic.
6.The impact of lung nodule centerline and related parameters on the prognosis of non-small cell lung cancer patients with surgery based on the NLST database
Xianglong GAO ; Junxi HU ; Xiaoyao WENG ; Shaowen YAO ; Shichun LU
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2022;29(09):1148-1155
Objective To evaluate the predictive performance of the geometric characteristics, centerline (CL) of pulmonary nodules for prognosis in patients with surgically treatment in the National Lung Screening Trial (NLST). Methods CT images of 178 patients who underwent surgical treatment and were diagnosed with non-small cell lung cancer (NSCLC) in the low-dose CT (LDCT) cohort from the NLST image database were selected, including 99 males and 79 females, with a median age of 64 (59, 68) years. CT images were processed using commercial software Mimics 21.0 to record the volume, surface area, CL and the area perpendicular to the centerline of pulmonary nodules. Receiver operating characteristic (ROC) curve was used to compare the predictive performance of LD, AD and CL on prognosis. Univariate Cox regression was used to explore the influencing factors for postoperative disease-free survival (DFS) and overall survival (OS), and meaningful independent variables were included in the multivariate Cox regression to construct the prediction model. Results The area under the curve (AUC) of CL for postoperative recurrence and death were 0.650 and 0.719, better than LD (0.596, 0.623) and AD (0.600, 0.631). Multivariate Cox proportional risk regression analysis showed that pulmonary nodule volume (P=0.010), the maximum area perpendicular to the centerline (MApc)(P=0.028) and lymph node metastasis (P<0.001) were independent risk factors for DFS. Meanwhile, age (P=0.010), CL (P=0.043), lymph node metastasis (P<0.001), MApc (P=0.022) and the average area perpendicular to the centerline (AApc) (P=0.016) were independently associated with OS. Conclusion For the postoperative outcomes of NSCLC patients in the LDCT cohort of the NLST, the CL of the pulmonary nodule prediction performance for prognosis is superior to the LD and AD, CL can effectively predict the risk stratification and prognosis of lung cancer, and spheroid tumors have a better prognosis.
7.Application of machine learning models to survival risk stratification after radical surgery for thoracic squamous esophageal cancer
Jinye XU ; Jianghui ZHOU ; Shengwei LIU ; Liangliang CHEN ; Junxi HU ; Xiaolin WANG ; Yusheng SHU
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2022;29(12):1574-1579
Objective To explore the application value of machine learning models in predicting postoperative survival of patients with thoracic squamous esophageal cancer. Methods The clinical data of 369 patients with thoracic esophageal squamous carcinoma who underwent radical esophageal cancer surgery at the Department of Thoracic Surgery of Northern Jiangsu People's Hospital from January 2014 to September 2015 were retrospectively analyzed. There were 279 (75.6%) males and 90 (24.4%) females aged 41-78 years. The patients were randomly divided into a training set (259 patients) and a test set (110 patients) with a ratio of 7 : 3. Variable screening was performed by selecting the best subset of
features. Six machine learning models were constructed on this basis and validated in an independent test set. The performance of the models' predictions was evaluated by area under the curve (AUC), accuracy and logarithmic loss, and the fit of the models was reflected by calibration curves. The best model was selected as the final model. Risk stratification was performed using X-tile, and survival analysis was performed using the Kaplan-Meier method with log-rank test. Results The 5-year postoperative survival rate of the patients was 67.5%. All clinicopathological characteristics of patients between the two groups in the training and test sets were not statistically different (P>0.05). A total of seven variables, including hypertension, history of smoking, history of alcohol consumption, degree of tissue differentiation, pN stage, vascular invasion and nerve invasion, were included for modelling. The AUC values for each model in the independent test set were: decision tree (AUC=0.796), support vector machine (AUC=0.829), random forest (AUC=0.831), logistic regression (AUC=0.838), gradient boosting machine (AUC=0.846), and XGBoost (AUC=0.853). The XGBoost model was finally selected as the best model, and risk stratification was performed on the training and test sets. Patients in the training and test sets were divided into a low risk group, an intermediate risk group and a high risk group, respectively. In both data sets, the differences in surgical prognosis among three groups were statistically significant (P<0.001). Conclusion Machine learning models have high value in predicting postoperative prognosis of thoracic squamous esophageal cancer. The XGBoost model outperforms common machine learning methods in predicting 5-year survival of patients with thoracic squamous esophageal cancer, and it has high utility and reliability.