BACKGROUND:A pathophysiological feature of septic organ failure is endothelial dysfunction in sepsis(EDS).The physiological and pathological mechanism of sepsis is considered to be vascular leakage caused by endothelial dysfunction.These pathological changes lead to systemic organ injury.However,an analysis using bibliometric methods has not yet been conducted in the field of EDS.This study was conducted to provide an overview of knowledge structure and research trends in the field of EDS. METHODS:Based on previous research,a literature search was performed in the Web of Science Core Collection(WoSCC)for publications associated with EDS published between the year 2003 and 2023.Various types of data from the publications,such as citation frequency,authorship,keywords and highly cited articles,were extracted.The"Create Citation Report"feature in the WoSCC was employed to calculate the Hirsch index(h-index)and average citations per item(ACI)of authors,institutions,and countries.To conduct bibliometric and visualization analyses,three bibliometric tools were used,including R-bibliometrix,CiteSpace(co-citation analysis of references),and VOSviewer(co-authorship analysis of institutions,co-authorship analysis of authors,co-occurrence analysis of keywords). RESULTS:After excluding invalid records,the study finaly included 4,536 publications with 135,386 citations.Most of these publications originated in the USA,China,Germany,Canada,and Japan.Harvard University emerged as the most prolific institution,while professor Jong-Sup Bae and his research team at Kyungpook National University emerged as authors with the greatest influence.The"protein C","tissue factor","thrombin","glycocalyx","acute kidney injury","syndecan-1"and"biomarker"were identified as prominent areas of research.Future research may focus on molecular mechanisms(such as as vascular endothelial[VE]-cadherin regulation)and therapeutic interventions to enhance endothelial repair and function. CONCLUSION:Our findings show a growing interest in EDS research.Key areas for future research include signaling pathways,molecular mechanisms,endothelial repair,and interactions between endothelial cells and other cell types in sepsis.

Objective To investigate the effects of α7 nicotinic acetylcholine receptor(nAChR)agonist on β3-adrenoceptor agonist-induced impairment of white fat homeostasis and beige adipose formation and heat production in obese mice.Methods Forty obese C57BL/6J mice were randomized into high-fat feeding group,β3-adrenoceptor agonist-treated model group,α7 nAChR agonist group,and α7 nAChR inhibitor group(n=10),with another 10 mice with normal feeding as the blank control group.White adipose tissue from the epididymis of the mice were sampled for HE staining of the adipocytes.The expression levels of TNF-α,IL-1β,IL-10 and TGF-β in the white adipose tissue were determined by ELISA,and the mRNA levels of iNOS,Arg1,UCP-1,PRDM-16 and PGC-1α were detected using RT-qPCR.Western blotting was performed to detect the expression levels of NF-κB P65,p-JAK2,p-STAT3 in the white adipose tissue.Results Compared with those in the blank control group,the mice with high-fat feeding showed significantly increased body weight,more fat vacuoles in the white adipose tissue,increased volume of lipid droplets in the adipocytes,upregulated iNOS mRNA expression and protein expression of TNF-α and IL-1β,and lowered expression of Arg-1 mRNA and IL-10 and TGF-β proteins(P<0.01).Treatment with α7 nAChR significantly reduced mRNA levels of PRDM-16,PGC-1α and UCP-1,lowered TNF-α and IL-1β expressions,increased IL-10 and TGF-β expressions,and reduced M1/M2 macrophage ratio in the white adipose tissues(P<0.05 or 0.01).Conclusion Activation of α7 nAchR improves white adipose tissue homeostasis impairment induced by β3 agonist,promotes transformation of M1 to M2 macrophages,reduces inflammatory response in white adipose tissue,and promote beige adipogenesis and thermogenesis in obese mice.

Objective To investigate the effects of α7 nicotinic acetylcholine receptor(nAChR)agonist on β3-adrenoceptor agonist-induced impairment of white fat homeostasis and beige adipose formation and heat production in obese mice.Methods Forty obese C57BL/6J mice were randomized into high-fat feeding group,β3-adrenoceptor agonist-treated model group,α7 nAChR agonist group,and α7 nAChR inhibitor group(n=10),with another 10 mice with normal feeding as the blank control group.White adipose tissue from the epididymis of the mice were sampled for HE staining of the adipocytes.The expression levels of TNF-α,IL-1β,IL-10 and TGF-β in the white adipose tissue were determined by ELISA,and the mRNA levels of iNOS,Arg1,UCP-1,PRDM-16 and PGC-1α were detected using RT-qPCR.Western blotting was performed to detect the expression levels of NF-κB P65,p-JAK2,p-STAT3 in the white adipose tissue.Results Compared with those in the blank control group,the mice with high-fat feeding showed significantly increased body weight,more fat vacuoles in the white adipose tissue,increased volume of lipid droplets in the adipocytes,upregulated iNOS mRNA expression and protein expression of TNF-α and IL-1β,and lowered expression of Arg-1 mRNA and IL-10 and TGF-β proteins(P<0.01).Treatment with α7 nAChR significantly reduced mRNA levels of PRDM-16,PGC-1α and UCP-1,lowered TNF-α and IL-1β expressions,increased IL-10 and TGF-β expressions,and reduced M1/M2 macrophage ratio in the white adipose tissues(P<0.05 or 0.01).Conclusion Activation of α7 nAchR improves white adipose tissue homeostasis impairment induced by β3 agonist,promotes transformation of M1 to M2 macrophages,reduces inflammatory response in white adipose tissue,and promote beige adipogenesis and thermogenesis in obese mice.

Objective:To evaluate the predictive value of mechanical power (MP) on the risk of in-hospital mortality in critical ill patients in emergency department.Methods:A total of 105 critical ill patients with invasive mechanical ventilation in the Department of Emergency of Second Affiliated Hospital of Guangzhou Medical University between December 1, 2017 and October 31, 2020 were retrospectively analyzed. Based on the clinical prognosis, the patients were divided into the in-hospital survival group (80 patients) and the in-hospital death group (25 patients). The clinical data and ventilator parameters were recorded, and the MP of the two groups was calculated in order to assess the predictive efficacy of MP on in-hospital death.Results:Compared to the in-hospital death group, the oxygenation index PaO 2/FiO 2 was significantly higher (271 mmHg vs. 217 mmHg, P=0.020) and blood lactate (1.59 mmol/L vs. 2.56 mmol/L, P<0.001) and procalcitonin (0.31 ng/mL vs. 3.55 ng/mL, P=0.028), minute ventilation (7.03 L/min vs.8.32 mmol/L, P=0.013), MP (14.37 J/min vs. 16.12 J/min, P=0.041), SOFA score (5 vs. 8, P=0.001) and APACHE II score (16 vs. 22, P=0.041) were significantly lower in the in-hospital survival group. Multivariate Logistic regression analysis showed that PaO 2/FiO 2( OR=1.015, P=0.044), MP ( OR=1.813, P=0.039) and SOFA score( OR=2.651, P=0.010) were independent risk factors for predicting hospital mortality in patients with mechanical ventilation. The areas under the ROC curves (AUC) were 0.62, 0.63 and 0.75, respectively. Moreover, the MP combined with SOFA score for predicting in-hospital death was significantly higher than that of MP alone (0.77 vs. 0.63, P<0.05). Conclusions:MP is associated with in-hospital death in patients with invasive mechanical ventilation in emergency department. MP combined with SOFA score can enhance its predictive efficacy

OBJECTIVE: To explore clinical rules based on the big data of the emergency department of the Second Affiliated Hospital of Guangzhou Medical University, and to establish an integrated platform for clinical research in emergency, which was finally applied to clinical practice. METHODS: Based on the hospital information system (HIS), laboratory information system (LIS), emergency specialty system, picture archiving and communication systems (PACS) and electronic medical record system of the Second Affiliated Hospital of Guangzhou Medical University, the structural and unstructured information of patients in the emergency department from March 2019 to April 2022 was extracted. By means of extraction and fusion, normalization and desensitization quality control, the database was established. In addition, data were extracted from the database for adult patients with pre screening triage level III and below who underwent emergency visits from March 2019 to April 2022, such as demographic characteristics, vital signs during pre screening triage, diagnosis and treatment characteristics, diagnosis and grading, time indicators, and outcome indicators, independent risk factors for poor prognosis in patients were analyzed. RESULTS: (1) The data of 338 681 patients in the emergency department of the Second Affiliated Hospital of Guangzhou Medical University from March 2019 to April 2022 were extracted, including 15 modules, such as demographic information, triage information, visit information, green pass and rescue information, diagnosis information, medical record information, laboratory examination overview, laboratory information, examination information, microbiological information, medication information, treatment information, hospitalization information, chest pain management and stroke management. The database ensured data visualization and operability. (2) Total 140 868 patients with pre-examination and triage level III and below were recruited from the emergency department database. The gender, age, type of admission to the hospital, pulse, blood pressure, Glasgow coma scale (GCS) and other indicators of the patients were included. Taking emergency admission to operating room, emergency admission to intervention room, emergency admission to intensive care unit (ICU) or emergency death as poor prognosis, the poor prognosis prediction model for patients with pre-examination and triage level III and below was constructed. The receiver operator characteristic curve and forest map results showed that the model had good predictive efficiency and could be used in clinical practice to reduce the risk of insufficient emergency pre-examination and triage. CONCLUSIONS The establishment of high-quality clinical database based on big data in emergency department is conducive to mining the clinical value of big data, assisting clinical decision-making, and improving the quality of clinical diagnosis and treatment.
Adult ; Humans ; Big Data ; Emergency Service, Hospital ; Triage/methods* ; Intensive Care Units ; Hospitalization ; Retrospective Studies

Abstract: Objective To analyze the resistance and spatial distribution of Mycobacterium tuberculosis (MTB) to six commonly used anti-tuberculosis drugs in Qinghai Province from 2016 to 2019, so as to provide a reference for tuberculosis treatment and drug-resistant tuberculosis control. Methods A total of 1 182 identified strains of Mycobacterium tuberculosis in Qinghai Province from 2016 to 2019 were collected, and 6 anti-tuberculosis drugs were subjected to drug susceptibility tests and strain confirmed by the proportional method. By means of ArcMap10.7 and SaTScan10.1 software, map visualization, spatial autocorrelation analysis and spatial scanning of MTB drug resistance were performed to identify MTB drug resistance clusters in Qinghai Province. Results From 2016 to 2019, the total drug resistance (TDR) rate of 1 182 Mycobacterium tuberculosis strains in Qinghai Province was 23.77% (281/1 182), with a mono-resistance (MR) rate of 11.08% (131/1 182), a poly-resistance (PDR) rate of 3.89% (46/1 182), a multi-drug resistance (MDR) rate of 8.80% (104/1 182), and an extensive drug resistance (XDR) rate of 0.85% (10/1 182). The rates of MDR, XDR and TDR all showed a decreasing trend year by year (P<0.01). The drug resistance spectrum displayed 21 combinations. The TDR rate and MDR rate in the retreatment patients were higher than those of the initial treated patients, and the difference was statistically significant (χ2 TDR=22.784, χ2MDR=45.082, P<0.01). In terms of demographic characteristics, the TDR rate in males was higher than that in females, and the middle-aged group was higher than other age groups, and the differences were statistically significant (χ2=7.541, 10.825, P<0.05). The results of global spatial autocorrelation analysis showed that there was no statistical significance in the autocorrelation and obvious spatial clustering of MTB drug resistance in Qinghai Province from 2016 to 2019 (P>0.05), which indicated a random distribution. The results of spatiotemporal scanning showed that there was a kind of clustering area, but the clustering effect was not significant (P>0.05), indicating a random distribution. Conclusions The TDR of MTB in Qinghai Province from 2016 to 2019 showed a downward trend year by year. In comparison with the national average, the rate of multi-drug resistance and extensive drug resistance was still high, and most of the multi-drug resistance resulted from rifampicin and isoniazid. The drugresistant population mainly consisted of retreatment, males, and young and middle-aged pop

Objective:To study the value of autoregressive integrated moving average (ARIMA) and autoregressive (AR) models in predicting the daily number of ambulances in prehospital emergency medical services demand in Guangzhou.Methods:Matlab simulation software was used to analyze the emergency dispatching departure records in Guangzhou from January 1, 2021 to December 31, 2021. A time series for the number of ambulances per day was calculated. After identifying the time series prediction model, ARIMA(1,1,1), AR(4) and AR(7) models were obtained. These models were used to predict the number of ambulances per day. ARIMA(1,1,1) model divided the time series into the training set and test set. Prony method was used for parameter calculation, and the demands of number of ambulances of the next few months were forecasted. AR(4) and AR(7) models used uniformity coefficient to forecast the demands of number of ambulances on that very day.Results:ARIMA(1,1,1), AR(4) and AR(7) can effectively predict the number of ambulances per day. The prediction fitting error of ARIMA (1,1,1) decreased with the extension of prediction time. The mean absolute percentage error (MAPE) of forecast results of daily vehicle output of emergency dispatching within two months was less than 6% and the predicted results were almost within the 95% confidence interval. The residual analysis of the model verified that the model was significantly effective.Conclusions:ARIMA model can make a long-term within two months and effective prediction fitting of the daily vehicle output of emergency dispatching, and AR model can make a short-term and effective prediction of the daily vehicle output of emergency dispatching.

Objective:To evaluate the value and efficacy of microscope-assisted minimally invasive anterior lumbar discectomy and zero-profile fusion (ALDF) for lumbar degenerative diseases.Methods:Anterior lumbar distractors were designed to maintain the distraction of intervertebral space and expose the posterior edge of the intervertebral space. From June 2018 to December 2020, 41 cases of lumbar degenerative diseases were treated with this operation, including 19 men and 22 women, aged 29-71 years old (average 42.1 years old). All patients had intractable low back pain. Imaging examination showed lumbar disc degeneration with narrow intervertebral space, including disc herniation with Modic changes in 7 cases, spinal stenosis with instability in 16 cases and spondylolisthesis in 18 cases. The involved levels included L 2,3 in 1 case, L 3,4 in 3 cases, L 2-L 4 in 1 case, L 4,5 in 17 cases and L 5S 1 in 19 cases. An incision was taken that was pararectus for L 2-L 4 and transverse for L 4-S 1, with the intervertebral disc exposed via extraperitoneal approach. The intervertebral space was released and distracted after discectomy in intervertebral space, and self-made distractors were used to maintain the space. Under microscope, the herniation, posterior annulus and osteophyte were removed for sufficient decompression, with a suitable self-anchoring cage implanted into the intervertebral space. The visual analogue score (VAS), Oswestry dysfunction index (ODI), intervertebral space height, lordosis angle and spondylolisthesis rate were evaluated. Results:Operations were performed successfully in all the patients. The operation time was 70-120 min with an average of 90 min, and the intraoperative blood loss was 15-70 ml with an average of 30 ml. No severe complication such as nerve or blood vessel injury occurred. The patients were followed up for 12 to 36 months, with an average of 18 months. At the last follow-up, VAS decreased from 6.4±2.3 to 1.1±0.9, and ODI decreased from 44.9%±16.9% to 5.8%±4.7%. Intervertebral space height recovered from 7.2±2.8 mm to 12.1±2.1 mm and lordosis angle recovered from 6.9°±4.8° to 10.1°±4.6°. X-ray showed significant recovery of intervertebral space height, lordosis angle and spondylolisthesis rate, with obvious interbody fusion and no displacement of cage. For 18 patients of spondylolisthesis, the slippage recovered from 16.6%±9.3% to 7.6%±5.3%, with an average improvement of 54.2%.Conclusion:Microscope-assisted minimally invasive ALDF can provide sufficient decompression and zero-profile fusion for lumbar degenerative diseases with satisfactory results during short-term follow-up.

Objective:To estimate in-hospital mortality after knee replacement (KR) and to assess its trend and risk factors in China.Methods:We included patients undergoing KR in the Hospital Quality Monitoring System in China (2013-2019) to estimate in-hospital mortality after KR and assessed relation of patient's and hospital's characteristics (year of surgery, age, gender, marital status, primary indication, Charlson comorbidity index, geographic location, hospital type, hospital volume of KR, and surgery type) to in-hospital mortality using multivariable Poisson regression.Results:The annual amount of KR has increased from 20 307 in 2013 to 35 757 in 2019, and has maintained an upward trend for 7 years. The mean age of patients having KR increased from 64.9 years in 2013 to 66.6 years in 2019. Of the total 218 923 KRs, 63 deaths (0.29‰) occurred within 30 days before discharging. Older age was associated with higher in-hospital mortality ( P for trend <0.001). Male gender had higher incidence of in-hospital mortality compared with female [relative risk (RR), 2.5; 95% CI: 1.5, 4.1]. Single marital status was associated with higher, albeit non-statistically significant, in-hospital mortality than married patients (RR, 2.1; 95% CI: 0.9, 4.6). Higher Charlson comorbidity index was associated with increased risk of in-hospital mortality ( P for trend <0.001). Risk of in-hospital mortality decreased with more hospital-year knee replacement surgeries ( P for trend <0.001). In-hospital mortality varied by geographic regions, with the lowest mortality in East region (0.16‰), followed by South-West (0.31‰), South-Central (0.31‰), North region (0.33‰), North-West (0.54‰) and North-East (0.59‰). Conclusion:In-hospital mortality after KR in China was relatively low. Older age, male gender, higher Charlson comorbidity index and lower hospital-year knee replacement surgeries were risk factors for in-hospital mortality. The mortality varied greatly according to the geographic location of hospital.

Objective:To analyze the sepsis related long non-coding RNA (lncRNA) and mRNA expression profiles based on Gene Expression Omnibus (GEO) datasets and bioinformatic analysis, and to analyze the sepsis-associated competing endogenous RNA (ceRNA) network based on microRNA (miRNA) database.Methods:The sepsis-related lncRNA dataset was downloaded from the GEO database, and the differential expression analysis was conducted by Bioconductor on the sepsis dataset to obtain differentially expressed lncRNA (DElncRNA) and differentially expressed mRNA (DEmRNA), and cluster heat map was drawn. miRNA combined with DElncRNA were predicted by miRcode. mRNA targeted by miRNA was simultaneously met by three databases: TargetScan, miRDB, and mirTarBase. The interaction relationship of lncRNA-miRNA-mRNA was obtained. The regulatory network visualization software CytoScape was used to draw ceRNA networks. DEmRNA in the ceRNA networks were imported into the Search Tool for the Retrieval of Interacting Genes Database (STRING) online database to draw the protein-protein interaction (PPI) map. The gene ontology (GO) function annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEmRNA were performed.Results:Dataset GSE89376 and GSE145227 were found from GEO database. Difference analysis showed there were 14 DElncRNA and 359 DEmRNA in the elderly group of GSE89376; 8 DElncRNA and 153 DEmRNA in the adult group of GSE89376; 1 232 DElncRNA and 1 224 DEmRNA in the children group of GSE145227. Clustering heatmap showed that there were significant differences in the expression of lncRNA and mRNA between the sepsis group and the control group. The ceRNA networks were constructed with miRNA. Several DElncRNA and multiple DEmRNA participated in the ceRNA network of sepsis. The PPI diagram demonstrated that several genes encoding proteins interacted with each other and form a multi-node interaction network with multiple genes encoding proteins. Functional annotation and enrichment analysis demonstrated that there might be a crosstalk mechanism on functionally related genes such as nuclear receptor activity, ligand-activated transcription factor activity, and steroid hormone receptor activity, and played a role in the occurrence and development of diseases through forkhead box transcription factor O (FoxO) signaling pathway, Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathway, p53 signaling pathway, and phosphateidylinositol 3-kinase (PI3K)/Akt signaling pathway.Conclusion:Through sepsis-related lncRNA-miRNA-mRNA ceRNA network and combining with KEGG pathway analysis, there were several lncRNA and mRNA participating in the ceRNA network related sepsis, which played an important role in several signal pathways.