1.Evaluation and treatment of altered mental status patients in the emergency department
Haiyu XIAO ; Hongbao ZHU ; Tengda XU ; Huadong ZHU ; Shubin GUO ; Zhong WANG ; Xuezhong YU
Chinese Journal of Emergency Medicine 2013;22(2):169-175
Objective To provide a framework for understanding the need for a structured assessment of altered mental status (AMS) to better understand underlying causes of the mental status changes in adults and therefore potentially improve diagnostic skills and eventually management.Methods This is a prospective cohort observational study.We recruited consecutive adult patients with undifferentiated AMS at a single center tertiary care academic emergency department over 24 months.Demographical,clinical presentations,assessment approaches,cause factors,emergency treatments and outcomes were collected prospectively.Results One thousand nine hundred and thirty-four patients with AMS were recruited,this number of patients represented 5% of the total ED census.Out of 1934 patients,1026 (53.1%) were male,908 (46.9%) were female.Mean age was (51.95 ± 15.71) years.Etiologic factors included neurological (n =641,35.0%),pharmacologic & toxicologic (n =421,23.0%),systemic and organic (n =266,14.5%),infectious (n =167; 9.1%),endocrine/metabolic (n =145,7.9%),psychiatric (n =71,3.9%),traumatic (n =38,2.1%),gynecologic and obstetric (n =35,1.9%).Total mortality rate was 8.1% (n =156).The death rate was higher in elderly patients (≥ 60) than that in younger patients (10.8% vs.6.9%,P =0.003).Conclusions The patient with AMS poses a challenge to physicians in ED.The most frequently encountered diagnostic category causing AMS were primary CNS disorders,intoxication,organ system dysfunction and endocrine/metabolic diseases.Fatality rate is very high.Prompt evaluation and treatment are essential to decrease the morbidity and mortality associated with this condition.
2.Down-regulation of Gankyrin Inhibits Gastric Cancer Cell Proliferation via Regulating β-Catenin/Cyclin D1 Signaling Pathway
Jie PAN ; Weimin WANG ; Weilong CAI ; Hongbao XU ; Chunfan HAN ; Fuchu QIAN
Chinese Journal of Gastroenterology 2016;21(5):282-286
Background:Gankyrin is an ankyrin repeat oncoprotein overexpressed and involved in the tumorigenesis and progression of various cancers. Aims:To investigate the effect and underlying mechanism of down-regulation of gankyrin expression on proliferation of gastric cancer cells. Methods:Lentivirus vector carrying gankyrin-targeted siRNA was transfected into human gastric cancer cell line MKN28. Cell proliferation,cell cycle distribution and β-catenin/ cyclin D1 signaling pathway was analyzed by MTT assay,flow cytometry and Western blotting,respectively,in gankyrin-silenced MKN28 cells and control cells. Results:The transfection efficiency of lentivirus vector was more than 90% ,and the protein expression of gankyrin in gankyrin siRNA transfected MKN28 cells was significantly repressed( P ﹤ 0. 01). Compared with cells transfected with control lentivirus and cells without transfection,MKN28 cells transfected with gankyrin siRNA showed markedly repressed cell growth after 3-day-culture;the proportion of cells in cell cycle G1 phase was significantly increased,and that in S phase was significantly decreased;down-regulated expression of β-catenin and cyclin D1 was observed(P all ﹤ 0. 01). Conclusions:Down-regulation of gankyrin expression in gastric cancer cells may induce cell cycle G1 phase arrest and inhibit cell proliferation by suppressing β-catenin/ cyclin D1 signaling pathway. Gankyrin might be a promising novel target for targeted therapy of gastric cancer.
3.Risk factors for surgical site infectious in postoperative elderly gastric cancer patients
Hongbao XU ; Weilong CAI ; Weimin WANG ; Jie PAN ; Mingjie ZHANG ; Chunfan HAN ; Qiang YAN
Chinese Journal of General Surgery 2018;33(4):276-279
Objective To investigate the risk factors of surgical site infection (SSI) related complications after radical gastrectomy for gastric cancer in elderly patients.Methods The clinical data of 410 elderly patients with gastric cancer who underwent radical gastrectomy was retrospectively collected from 2009 to 2016.Univariate and multivariate analysis were performed to investigate the risk factors of SSI related complications,and the impact of SSI on short-term prognosis.Results SSI developed in 50 out of 410 elderly patients who underwent radical gastrectomy for gastric cancer,including 19 incisional infections and 31 organ lacuna infections.The corresponding incidence was 12.2%,4.6% and 7.6%,respectively.By univariate analysis,age > 75 (x2 =5.315,P =0.021),preoperative anemia (x2 =3.983,P =0.046),NRS 2002 ≥ 3 (x2 =4.785,P =0.029),diabetes (x2 =5.895,P =0.015),preoperative obstruction (x2 =5.250,P =0.022),undifferentiated carcinoma (x2 =4.448,P =0.035),cardiac carcinoma (x2 =5.265,P =0.022) and combined organs resection (x2 =4.165,P =0.041) were associated with SSI.Multivariate analysis showed that advanced age (OR =2.422,P =0.016),diabetes (OR =2.524,P =0.026),preoperative obstruction (OR =2.098,P =0.047) and high NRS 2002 score (OR =1.969,P =0.043) were independent risk factors for SSI.Conclusion The independent risk factors of SSI for elderly gastric cancer patients are advanced age,diabetes,preoperative obstruction and high NRS 2002 score.
4.Construction of an early prediction model for post cardiopulmonary resuscitation-acute kidney injury based on machine learning
Jinxiang WANG ; Luogang HUA ; Daming LI ; Hongbao GUO ; Heng JIN ; Guowu XU
Chinese Journal of Nephrology 2024;40(11):875-881
Objective:To construct an early prediction model for post cardiopulmonary resuscitation-acute kidney injury (PCPR-AKI) by machine learning and provide a basis for early identification of acute kidney injury (AKI) high-risk patients and accurate treatment.Methods:It was a single-center retrospective study. The clinical data of patients admitted to Tianjin Medical University General Hospital after cardiopulmonary resuscitation following cardiac arrest from January 1, 2016 to October 31, 2023 were collected. The end-point event of the study was defined as AKI occurring within 48 hours after cardiopulmonary resuscitation. The patients were divided into AKI group and non-AKI group according to the AKI diagnostic criteria, and the differences of baseline clinical data between the two groups were compared. The patients who met the inclusion criteria were randomly (using the train_test_split function, set the random seeds to 1, 2, and 3) divided into training and validation sets at a ratio of 7∶3. Random forest (RF), support vector machine, decision tree, extreme gradient boosting and light gradient boosting machine algorithm were used to develop the early prediction model of PCPR-AKI. The receiver-operating characteristic curve and decision curve analysis were used to evaluate the performance and clinical practicality of the predictive models, and the importance of variables in the optimal model was screened and ranked.Results:A total of 547 patients were enrolled, with age of 66 (59, 70) years old and 282 males (51.6%). There were 238 patients (43.5%) having incidence of AKI within 48 hours after cardiopulmonary resuscitation. In the AKI group, 182 patients (76.5%) were in stage 1, 47 patients (19.7%) were in stage 2, and 9 patients (3.8%) were in stage 3. There were statistically significant differences in the age, time to reach resuscitation of spontaneous circulation, time from cardiac arrest to starting cardiopulmonary resuscitation, proportion of initial defibrillation rhythm, proportion of electric defibrillation, proportion of mechanical ventilation, adrenaline dosage, sodium bicarbonate dosage, proportion of coronary heart disease, proportion of hypertension, proportion of diabetes, serum creatinine, blood urea nitrogen, blood lactic acid, blood potassium, brain natriuretic peptide, troponin, D-dimer, neuron specific enolase, and 24 hours urine volume after cardiopulmonary resuscitation between AKI group and non-AKI group (all P<0.05). Among the five machine learning algorithms, RF model achieved the best performance and clinical practicality, with area under the curve of 0.875, sensitivity of 0.863, specificity of 0.956, and accuracy rate of 90.7%. In the variable importance ranking of RF model, the top 10 variables were as follows: time to reach resuscitation of spontaneous circulation, time from cardiac arrest to starting cardiopulmonary resuscitation, initial defibrillable rhythm, serum creatinine, mechanical ventilation, blood lactate acid, adrenaline dosage, brain natriuretic peptide, D-dimer and age. Conclusions:An early predictive model for PCPR-AKI is successfully constructed based on machine learning. RF model has the best predictive performance. According to the importance of the variables, it can provide clinical strategies for early identification and precise intervention for PCPR-AKI.
5.Study on the Intervention Effects of Huangqi Injection on Leukopenia Model Mice Based on LC-MS Metabolomics
Teng LIU ; Jinfang XU ; Xiaolin LU ; Hongbao HOU ; Zhenyu LI ; Tingli QU ; Zhengbao ZHAO
China Pharmacy 2020;31(21):2627-2633
OBJECTIVE:To study the intervention effects of Huan gqi injecti on on leucopenia model mice. METHODS : Kunming mice were randomly divided into normal group ,model group and drug group ,with 8 mice in each group. Model group and drug group were given intraperitoneal injection of cyclophosphamide to induce leukopenia model. Normal group was given intraperitoneal injection of equal volume of sterile water. After modeling successfully ,normal group and model group were given intraperitoneal injection of equal volume of sterile water ;drug group was given intraperitoneal injection of Huangqi injection 0.04 mL/10 g,once a day ,for consecutive 7 d. Based on the detection of blood routine indexes (leukocyte,lymphocyte,neutrophil, monocyte count )of mice in each group ,the metabolites in serum were analyzed by LC-MS. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA),orthogonal partial least squares-discriminant analysis (OPLS-DA),HMDB, METLIN, KEGG and other databases as well as related literatures were used to identify the differential metabolites. The metabolic pathways of differential metabolites were analyzed with MetPA online tools ,and the correlation of blood routine indexes and differential metabolites were analyzed on the basis of Pearson correlation coefficient. RESULTS: Compared with normal group , blood rountine indexes of model group were decreased significantly (P< 0.01). Compared with model group ,above blood r ountine indexes of drug group were all increased siginificantly (P<0.01). LC-MS chromatogram of serum samples in normal group and model group were significantly different ,and LC-MS metabonomics data of serum samples in drug group were similar to those of normal group. Multivariate statistical analysis and correlated database analysis revealed that compared with normal group ,serum contents of 17 metabolites as L-isoleucine,eicosapentaenoic acid were increased significantly in model group ,while the contents of 4 metabolites as spermidine were decreased significantly (P<0.05 or P<0.01). Compared with model group ,Huangqi injection could reverse the serum contents of 9 metabolites in mice ,such as citric acid ,L-proline,acetylcarnitine,L-isoleucine, L-phenylalanine,sphingosine-1-phosphate,lysophosphatidylinositol,eicosapentaenoic acid and linoleic acid (P<0.05 or P< 0.01),which were associated with linoleic acid metabolism ,biosynthesis of phenylalanine ,tyrosine and tryptophan ,and phenylalanine metabolism (metabolism pathway influential values were all higher than 0.1). Correlation analysis showed that there was a significant correlation between blood routine indexes and the contents of D-sphingosine,linoleic acid and citric acid in model group(the absolute values of r were generally greater than 0.5). CONCLUSIONS :Huangqi injection can increase the counts of leukocytes,lymphocytes,neutrophils and monocytes in leucopenia model mice. The increase of leukocytes may be related to linoleic acid metabolism ,biosynthesis of phenylalanine ,tyrosine and tryptophan ,and phenylalanine metabolism.