Objective To identify genes of lipopolysaccharide (LPS) -induced acute lung injury (ALI) in mice base on bioinformatics and machine learning. Methods The acute lung injury dataset (GSE2411, GSE111241 and GSE18341) were download from the Gene Expression Database (GEO). Differential gene expression analysis was conducted. Gene ontology (GO) analysis, KEGG pathway analysis, GSEA enrichment analysis and protein-protein interaction analysis (PPI) network analysis were performed. LASSO-COX regression analysis and Support Vector Machine Expression Elimination (SVM-RFE) was utilized to identify key biomarkers. Receiver operator characteristic curve was used to evaluate the diagnostic ability. Validation was performed in GSE18341. Finally, CIBERSORT was used to analyze the composition of immune cells, and immunocorrelation analysis of biomarkers was performed. Results A total of 29 intersection DEGs were obtained after the intersection of GSE2411 and GSE111241 differentially expressed genes. Enrichment analysis showed that differential genes were mainly involved in interleukin-17, cytokine - cytokine receptor interaction, tumor necrosis factor and NOD-like receptor signaling pathways. Machine learning combined with PPI identified Gpx2 and Ifi44 were key biomarkers. Gpx2 is a marker of ferroptosis and Ifi44 is an type I interferon-induced protein, both of which are involved in immune regulation. Immunocorrelation analysis showed that Gpx2 and Ifi44 were highly correlated with Neutrophils, TH17 and M1 macrophage cells. Conclusion Gpx2 and Ifi44 have potential immunomodulatory abilities, and may be potential biomarkers for predicting and treating ALI in mince.
Objective To investigate the risk factors of early allograft dysfunction (EAD) following C-Ⅱ donation after cardiac death (DCD) liver transplantation. Methods The data of 46 donors and recipients of C-ⅡDCD liver transplantation between March 2012 and August 2015 were retrospectively analyzed. The baseline data such as democracy, death cause, donor warm ischemic time (DWIT) and cold ischemic time (CIT) in EAD group and the non-EAD group (control group) was compared, and whether these factors were risk factors of EAD was investigated by univariate and multivariate analyses. Statistical cut-off values for significant factors of the unfavorable analysis were defined by receiver operating characteristics (ROC) analysis. The 6-month and 1-year graft survival rate were compared. Results The EAD group had a longer DWIT compared with the group [(17.6±4.7) and (12.7±6.2) minutes, P=0.009]; meanwhile, the EAD group had a longer CIT compared with the control group [(13.7±4.7) and (11.0±3.5) hours, P=0.020]. The other factors in both groups showed no statistical significance (P>0.05). The ROC curve revealed the cut-off values of DWIT and CIT were 17.50 minutes [area under the curve (AUC)=0.713, P=0.020] and 9.85 hours (AUC=0.723, P=0.015), respectively. The multivariate logistic regression analysis showed the DWIT [odds ratios (OR)=1.340, 95% confidence interval (CI)(1.042, 1.654), P=0.008] and CIT [OR=1.396, 95% CI (1.075, 1.698), P=0.015] were all independent risk factors of EAD. The 6-month and 1-year graft survival rate of the EAD group and the control group was 85.7% vs. 92.3% (P=0.607) and 71.4% vs. 84.6% (P=0.587), respectively. Conclusions EAD may occured in C-Ⅱ donors with DWIT≥17.50 minutes or CIT≥9.85 hours in DCD liver transplantation. The livers can be used as a resource for clinical use and also have a good outcome.
ObjectiveTo construct a rapid screening tool for the donor of heart dead organ donation (donation after circulatory death, DCD) in the background of novel coronavirus (SARS-CoV-2) infection.MethodsBased on literature analysis and core group discussion, two rounds of expert consultation were carried out by Delphi method to establish dimension and index.ResultsThe screening tool included 3 dimensions, including epidemiological history, hospital exposure history, and clinical manifestations, with 15 entries. The mean of the two rounds of expert authority coefficient was 0.757 and 0.768, and the effective recovery rate of the expert consultation questionnaire was 88% and 100%, respectively. The second round dimension and index coordination coefficients was 0.417 and 0.319, respectively. The content validity of the questionnaire was 0.91.ConclusionsThe DCD liver transplant donor's new rapid screening tool for SARS-CoV-2 infection is scientific and reliable. During the epidemic period, the DCD liver transplant donor risk screening tool is of great significance to the prevention and control of liver transplantation risk.
Objective To study the neural mechanism of hypotension or shock state in acute cholangitis in severe type (ACST) and its value of clinical application. Methods A technique of blocking abdominal splanchnic nervi via right adipose capsule of kidney was carried out on 28 patients by injecting 1% lidocaine before urgent operation. Results After blocking the relevant nervi, hypotension or shock state in 23 patients were improved significantly (Ｐ＜0.05). The death rate was lower (14.3%) after having performed biliary decompressions with laparotomy. Conclusion Patients′ hypotension or shock state at the early phase of ACST is the result of neural reflex in which the splanchnic nervi is its afferent pathway. Blocking the relevant nervi before urgent operation, the valuable opportunity of emergency treatment can be obtainded and the complication and death rate are reduced significantly.
目的:调查我院腹膜透析患者死亡和转HD治疗的原因及相关影响因素。方法: 收集腹膜透析患者在我院死亡14例,转HD治疗 2 6例;查阅40例患者在我院的完整病历资料,调查其死亡及转HD治疗的原因及感染病原菌、营养等指标。结果: 14例腹膜透析死亡患者主要原因为肺部感染合并心脑血管疾病及消化道出血,均占(29%,4/14)。643%(9 / 14)的死亡患者HBlt;90 g/L,ALBlt;30 g/l;71.4%(10 / 14)的腹膜透析死亡患者合并钙磷失调。 26例腹膜透析患者转HD的首要原因和次要原因分别为腹透相关性腹膜炎(50%,13/26)和透析液引流不畅(42%,11/26)。72.7%透析液引流不畅的腹透患者经影像学诊断漂管,27.3%患者为拔管手术证实网膜堵塞管口。结论: 1.肺部感染性疾病合并合并心脑血管系统及消化系统,为腹膜透析患者死亡的主要原因,与全身营养状况不良,钙磷失调有关。 2. 腹膜透析相关性腹膜炎仍为腹膜透析患者退出转HD治疗的主要原因。 3.因透析液引流不畅而拔管为转HD治疗的第二位原因,漂管和网膜阻塞管口为透析液引流不畅的原因。
Objective To explore the predictive value of simplified acute physiological score Ⅱ (SAPS-Ⅱ) combined with lactate clearance rates (LCR) at different moments for mortality in sepsis patients. Methods A total of 188 patients with sepsis admitted in the hospital from April 2020 to February 2023 were selected, who were evaluated using the SAPS-Ⅱ scale. Spectrophotometry was used to detect blood lactate at baseline, after 6h, 12h, 24h, and 48h, then the LCR after 6h, 12h, 24h, and 48h were calculated. The patients were divided into a survival group (n=139) and a death group (n=37) based on 28 day outcome. Logistic regression analysis was used to explore the risk factors of sepsis death, and the efficacy of SAPS-Ⅱ scores combined with LCR at different moments in predicting patient death was analyzed using receiver operating characteristic (ROC) curve. Results Twelve patients fell off, and 37 died in the remaining 176 patients, the mortality rate was 21.02%. The age, temperature, random blood glucose, blood urea nitrogen, serum creatinine, and SAPS- Ⅱ scores in the death group were significantly higher than those in the survival group (P<0.05), while platelet count and LCR at all moments were significantly lower than those in the survival group (P<0.05). The LCR of the death group continued to decrease with time. The trend of changes in the survival group were opposite, and the differences in the two groups between each two moments were statistically significant (P<0.05). The SAPS-Ⅱ scores and LCR at all moments were risk factors for patient death (P<0.05). The SAPS-Ⅱ score and LCR at all moments had predictive value for patient death, and the area under ROC curve of the combined prediction was 0.921 (95%CI 0.825 - 1.000), which was higher than the individual prediction and LCR at each moment combined with SAPS II score prediction (P<0.05). Conclusion The SAPS-Ⅱ scores and LCR at different moments are all related to death of sepsis patients, and the combined prediction of death by the above indicators is highly effective.