OBJECTIVETo investigate the application of microsurgical technique in the replantation of amputated ear.

METHODS7 cases of amputated ears were analyzed from June 2009 to April 2015 in our department. We used microsurgical technique to anastomose about five vessels and nerves. The blood supply of auricle was restored within three to six hours. All subjects underwent treatments including anti-freezing, anti-spasm and anti-infection treatment after the emergency surgery.

RESULTS7 amputated ears were all survived after replantation. The patients were followed up for one month to six months ( average for 28 months). The appearances of survived ears body were fully recovered without any significant atrophy or pigmentation. The sensory function of ears recovered to normal after 1 year.

CONCLUSIONSThe application of microsurgical technique in the replantation of amputated ear can expect the high success rate of ear replantation. However, skilled and high-quality anastomosis technique of small vascular are required.

Amputation, Traumatic ; surgery ; Anastomosis, Surgical ; methods ; Ear Deformities, Acquired ; surgery ; Ear, External ; blood supply ; innervation ; Graft Survival ; Humans ; Microsurgery ; methods ; Replantation ; methods

Objective:To explore the predictive value of red blood cell count (RBC), fibrinogen (FBG) combined with platelet count (PLT)for risk stratification of acute pulmonary embolism (PE).Methods:Patients admitted to Beijing Chaoyang Hospital from January 2013 to October 2019 and diagnosed with acute PE were retrospectively collected. According to the risk stratification criteria for PE, the patients were divided into the high/medium risk group and low risk group. The demographic characteristics, previous medical history, parameters of RBC and PLT, and FBG of the two groups were compared.Results:Totally 696 patients were selected in the study, of them, 193 patients were in the high/medium risk group and 503 in the low risk group. RBC and hematocrit (HCT) in the high/medium risk group were significantly higher than those in the low risk group, but FBG and PLT in the high/medium risk group were significantly lower than those in the low risk group (all P<0.05). There was no significant difference in age, gender, previous medical history, hemoglobin (HGB), HCT, mean corpuscular volume (MCV), mean corpuscular hemogloin (MCHC), red blood cell distribution width (RDW), platelet distribution width (PDW), mean platelet volume (MPV), and platelet large cell rate (P-LCR) between the two groups. Logistic regression analysis showed that RBC, PLT and FBG were independent influencing factors for risk stratification of acute PE. RBC was positively correlated with risk stratification, while PLT and FBG were negatively correlated. The area under the ROC curve (AUC) of RBC, PLT and FBG were 0.552 (95% CI: 0.514-0.589), 0.591 (95% CI: 0.554-0.628), and 0.565 (95% CI: 0.527-0.602), with the cut-off value of 4.57 ×10 12/L,182 ×10 9/L and 322.8 mg/dL, respectively. Conclusions:RBC, FBG combined with PLT have clinical predictive value for risk stratification of acute PE.

Objective To investigate the perioperative complications and therapeutic effects of balloon-assisted coiling (BAC) and stent-assisted coiling (SAC) in patients with ruptured intracranial aneurysms in the acute phase. Methods Totally 91 patients with 91 intracranial ruptured aneurysms were treated with BAC or SAC in our hospital between January 2014 and December 2016. Among them, 37 patients were treated with BAC and 54 patients with SAC respectively. Of the two groups, the position distribution and shape of aneurysms, and the complications after procedures and the therapeutic effects were summarized and evaluated retrospectively using chi-square test. Results The width of the aneurysm neck was narrower in the BAC-treated group compared to the SAC-treated group (3.31±1.63 mm vs. 4.35±2.10 mm, P=0.01). The aneurysm body/neck ratio (B/N) was lower in the BAC-treated group than in the SAC-treated group (1.64 ± 0.46 vs. 1.35±0.66, P=0.025). The recurrence rate was higher in the BAC-treated group than that in the SAC-treated group (18.9％ vs. 0.9％, P=0.005). There was no statistical difference in perioperative complication in both the BAC-treated group and SAC-treated group. However, 2 patients died due to the relative postoperative intracranial bleeding in the SAC-treated group. Better outcomes (Modified Rankin Score, mRS, 0-2) were achieved in the BAC-treated group compared to the SAC-treated group (94.6％ vs. 88.9％, P=0.028) at the follow-up visit. Conclusions These findings suggested that there is no difference between the BAC-treated group and the SAC-treated group in the risk of complication. BAC can achieve a better prognosis,but it is more prone to relapse. The SAC method was more appropriate for wider neck aneurysms. It was also an option to coiling the aneurysm in BAC in acute phase firstly, followed by additional treatment in SAC during the follow-up period.

Objective:To analyze the types and functions of CD34 + cells in full-thickness skin defect wounds of normal mice and diabetic mice by single-cell RNA sequencing. Methods:This study was an experimental study. The CD34 + cell lineage tracing mouse was produced, and the visualization of CD34 + cells under the fluorescent condition was realized. Six male CD34 + cell lineage tracing mice aged 7-8 weeks (designated as diabetic group) were intraperitoneally injected with streptozotocin to establish a diabetic model, and full-thickness skin defect wounds were prepared on their backs when they reached 13 weeks old. Another 6 male CD34 + cell lineage tracing mice aged 13 weeks (designated as control group) were also subjected to full-thickness skin defect wounds on their backs. On post-injury day (PID) 4, wound tissue was collected from 3 mice in control group and 2 mice in diabetic group, and digested to prepare single-cell suspensions. CD34 + cells were screened using fluorescence-activated cell sorting, followed by single-cell RNA sequencing. The Seurat 4.0.2 program in the R programming language was utilized for dimensionality reduction, visualization, and cell clustering analysis of CD34 + cell types, and to screen and annotate the marker genes for each CD34 + cell subpopulation. Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) enrichment analysis was performed to analyze the differentially expressed genes (DEGs) of CD34 + fibroblasts (Fbs), smooth muscle cells (SMCs), keratinocytes (KCs), and chondrocyte-like cells (CLCs) in the wound tissue of two groups of mice for exploring cellular functions. Results:On PID 4, CD34 + cells in the wound tissue of both groups of mice were consisted of 7 cell types, specifically endothelial cells, Fbs, KCs, macrophages, T cells, SMCs, and CLCs. Among these, Fbs were further classified into 5 subpopulations. Compared with those in control group, the proportions of CD34 + endothelial cells, Fbs subpopulation 1, Fbs subpopulation 4, KCs, and CLCs in the wound tissue of mice were increased in diabetic group, while the proportions of CD34 + Fbs subpopulation 2, Fbs subpopulation 3, and SMCs were decreased. The marker genes for annotating CD34 + CLCs, endothelial cells, Fbs subpopulation 1, Fbs subpopulation 2, Fbs subpopulation 3, Fbs subpopulation 4, Fbs subpopulation 5, KCs, macrophages, SMCs, and T cells were respectively metastasis-associated lung adenocarcinoma transcript 1, fatty acid binding protein 4, Gremlin 1, complement component 4B, H19 imprinted maternally expressed transcript, Dickkopf Wnt signaling pathway inhibitor 2, fibromodulin, keratin 5, CD74 molecule, regulator of G protein signaling 5, and inducible T-cell co-stimulator molecule. KEGG and GO enrichment analysis revealed that, compared with those in control group, DEGs with significant differential expression (SDE) in CD34 + Fbs from the wound tissue of mice in diabetic group on PID 4 were significantly enriched in terms related to inflammatory response, extracellular matrix (ECM) organization, regulation of cell proliferation, and aging (with Pvalues all <0.05), DEGs with SDE in CD34 + SMCs were significantly enriched in terms related to cell migration, apoptotic process, positive regulation of transcription, and phagosome (with P values all <0.05), DEGs with SDE in CD34 + KCs were significantly enriched in terms related to mitochondrial function, transcription, and neurodegenerative diseases (with P values all <0.05), and DEGs with SDE in CD34 + CLCs were significantly enriched in terms related to rhythm regulation, ECM, and viral infection (with P values all <0.05). Conclusions:CD34 + cells display high heterogeneity in the healing process of full-thickness skin defect wounds in both normal mice and diabetic mice. The significantly enriched functions of DEGs with SDE in CD34 + cell subpopulations in the wound tissue of the two mouse groups are closely related to the wound healing process.

Objective: To observe the impact and clinical outcome of intra-aortic balloon pump(IABP) use in patients underwent percutaneous coronary intervention (PCI). Methods: From January 2013 to December 2013, 10 724 consecutive patients undergoing PCI were enrolled.After 2 years′ follow-up, the incidence of major adverse cardiovascular and cerebrovascular events such as death, myocardial infarction, stent thrombosis, revascularization, recurrent stroke were recorded, propensity score was used to match baseline data, and the clinical outcomes in patients with IABP and non-IABP were compared. Results: The overall use of IABP was 1.3%(143/10 724), clinical and angiographic risks were significantly higher in IABP group than non-IABP group.The rate of cardiac shock was significantly higher (9.8%(14/143) vs. 0.2%(16/10 581), P<0.01) and left ventricular ejection fraction was significantly lower (54.3%±11.0% vs. 62.9%±7.2%, P<0.01) in the IABP group than in the non-IABP group.Patients in IABP group had a significantly higher rate of left main or triple-vessel disease (P<0.01), and their SYNTAX score, target lesion number, stent number were also significantly higher compared with non-IABP patients (all P<0.01). During the 2-year follow-up, all-cause mortality was significantly higher in IABP group than in non-IABP group (10.5%(15/142) vs. 1.1%(116/10 581), P<0.001). Multivariable analyses indicated that IABP was associated with increased mortality (HR=3.51, 95%CI 1.71-7.17, P=0.001). However, after propensity score matched analyses (137 pairs), IABP use was no longer an independent predictor of all-cause mortality (HR=2.09, 95%CI 0.72-6.13, P=0.177). Conclusions In this single large center of coronary heart disease in China, the IABP usage was about 1.3%.Propensity score matched analyses showed that during the 2 years′ follow-up, adverse effect including similar long-term mortality is similar between PCI patients with or without IABP after adjusting for confounders.

Objective: To investigate the clinical value of Bayesian network in predicting survival of patients with advanced gallbladder cancer(GBC)who underwent curative intent surgery. Methods: The clinical data of patients with advanced GBC who underwent curative intent surgery in 9 institutions from January 2010 to December 2015 were analyzed retrospectively.A median survival time model based on a tree augmented naïve Bayes algorithm was established by Bayesia Lab software.The survival time, number of metastatic lymph nodes(NMLN), T stage, pathological grade, margin, jaundice, liver invasion, age, sex and tumor morphology were included in this model.Confusion matrix, the receiver operating characteristic curve and area under the curve were used to evaluate the accuracy of the model.A priori statistical analysis of these 10 variables and a posterior analysis(survival time as the target variable, the remaining factors as the attribute variables)was performed.The importance rankings of each variable was calculated with the polymorphic Birnbaum importance calculation based on the posterior analysis results.The survival probability forecast table was constructed based on the top 4 prognosis factors. The survival curve was drawn by the Kaplan-Meier method, and differences in survival curves were compared using the Log-rank test. Results: A total of 316 patients were enrolled, including 109 males and 207 females.The ratio of male to female was 1.0∶1.9, the age was (62.0±10.8)years.There was 298 cases(94.3%) R0 resection and 18 cases(5.7%) R1 resection.T staging: 287 cases(90.8%) T3 and 29 cases(9.2%) T4.The median survival time(MST) was 23.77 months, and the 1, 3, 5-year survival rates were 67.4%, 40.8%, 32.0%, respectively.For the Bayesian model, the number of correctly predicted cases was 121(≤23.77 months) and 115(>23.77 months) respectively, leading to a 74.86% accuracy of this model.The prior probability of survival time was 0.503 2(≤23.77 months) and 0.496 8(>23.77 months), the importance ranking showed that NMLN(0.366 6), margin(0.350 1), T stage(0.319 2) and pathological grade(0.258 9) were the top 4 prognosis factors influencing the postoperative MST.These four factors were taken as observation variables to get the probability of patients in different survival periods.Basing on these results, a survival prediction score system including NMLN, margin, T stage and pathological grade was designed, the median survival time(month) of 4-9 points were 66.8, 42.4, 26.0, 9.0, 7.5 and 2.3, respectively, there was a statistically significant difference in the different points(P<0.01). Conclusions The survival prediction model of GBC based on Bayesian network has high accuracy.NMLN, margin, T staging and pathological grade are the top 4 risk factors affecting the survival of patients with advanced GBC who underwent curative resection.The survival prediction score system based on these four factors could be used to predict the survival and to guide the decision making of patients with advanced GBC.

Objective:To explore the clinical value of arterial partial pressure of carbon dioxide (PaCO 2) combined with Wells score in predicting acute pulmonary embolism (PE). Methods:Patients with suspected acute PE admitted to Emergency Department of Beijing Chaoyang Hospital, Capital Medical University from January 1, 2016 to August 31, 2021 were screened. Patients with positive computed tomography pulmonary angiography (CTPA) results were classified as the PE group, and those with negative CTPA results were classified as the non-PE group. Demographic characteristics, symptoms, vital signs, underlying diseases, risk factors for venous thrombosis, arterial blood gas analysis and Wells scores were statistically analyzed and compared between the two groups, and the clinical efficacy of PaCO 2 combined with Wells score in predicting acute PE was evaluated. Results:A total of 1 869 patients with suspected acute PE were screened, and 1 492 patients were finally selected. There were 537 cases in the PE group and 955 cases in the non-PE group. The frequency of chest pain, dyspnea, unilateral lower limb edema, history of PE or deep venous thrombosis, history of surgery or immobilization within 3 months, history of fracture within 3 months, active malignant tumor, elevated Wells score and reduced PaCO 2 in the PE group was significantly higher than that in the non-PE group (all P< 0.05). The area under receiver operating characteristic (ROC) curve (AUC) of Wells score was 0.784 (95% CI: 0.758-0.810), and the sensitivity and specificity of predicting acute pulmonary embolism were 61.64% and 88.48%, respectively. The AUC of reduced PaCO 2 was 0.679 (95% CI: 0.651-0.707), and the sensitivity and specificity of predicting acute pulmonary embolism were 79.89% and 55.92%, respectively. The AUC of reduced PaCO 2 combined with Wells score was 0.837 (95% CI: 0.816-0.858), and the sensitivity and specificity of predicting acute pulmonary embolism were 74.12% and 77.07%, respectively. The AUC of reduced PaCO 2 combined with Wells score was significantly greater than the AUC of Wells score ( P<0.001) and the AUC of reduced PaCO 2 ( P<0.001). Conclusions:The efficacy of PaCO 2 reduction combined with Wells score in predicting acute PE was superior to that of either of them alone. This was a beneficial supplement to the screening of patients with acute PE, and would also help reduce the abuse of CTPA in the emergency department.

Objective:To examine a survival prognostic model applicable for patients with intrahepatic cholangiocarcinoma (ICC) based on Bayesian network.Methods:The clinical and pathological data of ICC patients who underwent curative intent resection in ten Chinese hepatobiliary surgery centers from January 2010 to December 2018 were collected.A total of 516 patients were included in the study. There were 266 males and 250 females.The median age( M( Q R)) was 58(14) years.One hundred and sixteen cases (22.5%) with intrahepatic bile duct stones,and 143 cases (27.7%) with chronic viral hepatitis.The Kaplan-Meier method was used for survival analysis.The univariate and multivariate analysis were implemented respectively using the Log-rank test and Cox proportional hazard model.One-year survival prediction models based on tree augmented naive Bayesian (TAN) and na?ve Bayesian algorithm were established by Bayesialab software according to different variables,a nomogram model was also developed based on the independent predictors.The receiver operating characteristic curve and the area under curve (AUC) were used to evaluate the prediction effect of the models. Results:The overall median survival time was 25.0 months,and the 1-,3-and 5-year cumulative survival rates was 76.6%,37.9%,and 21.0%,respectively.Univariate analysis showed that gender,preoperative jaundice,pathological differentiation,vascular invasion,microvascular invasion,liver capsule invasion,T staging,N staging,margin,intrahepatic bile duct stones,carcinoembryonic antigen,and CA19-9 affected the prognosis(χ 2=5.858-54.974, all P<0.05).The Cox multivariate model showed that gender,pathological differentiation,liver capsule invasion, T stage,N stage,intrahepatic bile duct stones,and CA19-9 were the independent predictive factors(all P<0.05). The AUC of the TAN model based on all 19 clinicopathological factors was 74.5%,and the AUC of the TAN model based on the 12 prognostic factors derived from univariate analysis was 74.0%,the AUC of the na?ve Bayesian model based on 7 independent prognostic risk factors was 79.5%,the AUC and C-index of the nomogram survival prediction model based on 7 independent prognostic risk factors were 78.8% and 0.73,respectively. Conclusion:The Bayesian network model may provide a relatively accurate prognostic prediction for ICC patients after curative intent resection and performed superior to the nomogram model.

Objective:To establish a 14-day prognosis model for emergency patients with acute ischemic cerebral stroke and evaluate its predictive efficacy.Methods:A prospective cohort study was conducted. Patients with acute ischemic stroke admitted to the emergency department of Beijing Bo’ai Hospital within 72 hours of onset from October 2018 to December 2020 were enrolled. Univariate and multivariate logistic regression analysis were used to screen the risk factors of poor prognosis. The ROC curve was drawn to determine the cut-off value of continuous variables and discretise data with reference to clinical practice. The corresponding scores were set up according to the β regression coefficient of each variable, and the clinical scale prediction model of short-term prognosis of acute cerebral infarction was established. Patients with ischemic stroke in the hospital from January to December 2021 were selected as the internal validation, to verify the constructed predictive model.Results:A total of 321 patients were included in the study, including 223 in the training set and 98 in the internal validation set. Multivariate logistic regression analysis showed that age, hypersensitive C-reactive protein, prealbumin (PA), infarct volume, Frailty Screening Questionnaire (FSQ) and National Institute of Health Stroke Scale (NIHSS) were independent risk factors for poor short-term prognosis of acute cerebral infarction. The total score of the clinical prediction scoring system for short-term prognosis of acute cerebral infarction in the emergency department was 15 points, including age ≥74 years (1 point), PA ≤373 mg/L (2 points), large artery atherosclerosis (1 point), cardiogenic embolism (2 points), infarct volume ≥ 2.18 cm 3 (2 points), FSQ ≥3 points (1 point), NIHSS ≥4 points (6 points); The area under the ROC curve (AUC) of the scoring system for predicting short-term poor prognosis of acute cerebral infarction was 0.927 (95% CI: 0.894-0.960). The optimal cut-off value was ≥5 points, and the sensitivity and specificity were 0.770 and 0.976, respectively. In the internal validation set, the scoring system had similar predictive value for poor outcomes (AUC=0.892, 95% CI:0.827-0.957). Conclusion:The scoring system for short-term prognosis prediction of acute ischemic cerebral infarction has good diagnostic efficacy, and could guide clinicians to judge the prognosis of emergency patients in the early stage.

Objective:To examine a survival prognostic model applicable for patients with intrahepatic cholangiocarcinoma (ICC) based on Bayesian network.Methods:The clinical and pathological data of ICC patients who underwent curative intent resection in ten Chinese hepatobiliary surgery centers from January 2010 to December 2018 were collected.A total of 516 patients were included in the study. There were 266 males and 250 females.The median age( M( Q R)) was 58(14) years.One hundred and sixteen cases (22.5%) with intrahepatic bile duct stones,and 143 cases (27.7%) with chronic viral hepatitis.The Kaplan-Meier method was used for survival analysis.The univariate and multivariate analysis were implemented respectively using the Log-rank test and Cox proportional hazard model.One-year survival prediction models based on tree augmented naive Bayesian (TAN) and na?ve Bayesian algorithm were established by Bayesialab software according to different variables,a nomogram model was also developed based on the independent predictors.The receiver operating characteristic curve and the area under curve (AUC) were used to evaluate the prediction effect of the models. Results:The overall median survival time was 25.0 months,and the 1-,3-and 5-year cumulative survival rates was 76.6%,37.9%,and 21.0%,respectively.Univariate analysis showed that gender,preoperative jaundice,pathological differentiation,vascular invasion,microvascular invasion,liver capsule invasion,T staging,N staging,margin,intrahepatic bile duct stones,carcinoembryonic antigen,and CA19-9 affected the prognosis(χ 2=5.858-54.974, all P<0.05).The Cox multivariate model showed that gender,pathological differentiation,liver capsule invasion, T stage,N stage,intrahepatic bile duct stones,and CA19-9 were the independent predictive factors(all P<0.05). The AUC of the TAN model based on all 19 clinicopathological factors was 74.5%,and the AUC of the TAN model based on the 12 prognostic factors derived from univariate analysis was 74.0%,the AUC of the na?ve Bayesian model based on 7 independent prognostic risk factors was 79.5%,the AUC and C-index of the nomogram survival prediction model based on 7 independent prognostic risk factors were 78.8% and 0.73,respectively. Conclusion:The Bayesian network model may provide a relatively accurate prognostic prediction for ICC patients after curative intent resection and performed superior to the nomogram model.