Objective:To explore the risk factors of sepsis in patients with multiple trauma and construct a nomogram prediction model.Methods:The data of patients with multiple injuries admitted to the emergency intensive care unit (EICU) of the General Hospital of Ningxia Medical University from January 2021 to April 2022 were respectively collected. Inclusion criteria: (1) meet the diagnostic criteria for multiple injuries; (2) the time from injury to admission ≤ 24 hours; (3) age>18 years old; (4) all examination or rescue measures were approved by the patient or the patient's family; (5) the patient's clinical data were complete. The patients were divided into sepsis group and non-sepsis group according to the definition of Sepsis 3.0 at the 28-day of EICU hospitalization. The receiver operating characteristic curve was drawn. Logistic regression analysis was applied to determine the independent predictors for sepsis, and the nomogram was constructed.Results:A total of 291 patients were included, including 102 in the sepsis group and 189 in the non-sepsis group. Multivariate logistic analysis revealed that age, acute physiology and chronic health status score (APACHE) Ⅱ, Glasgow Coma Scale (GCS), injury severity score (ISS), sequential organ failure assessment (SOFA) within 24 hours after admission, blood transfusion frequency, the application of norepinephrine, mechanical ventilation, pathogenic culture results, and history of diabetes were independent factors influencing the occurrence of sepsis. A nomogram model was constructed by combining these variables (AUC=0.913, 95% CI: 0.847-0.942), and the model had a good fitting calibration curve. Conclusions:The nomogram constructed by age, APACHE-Ⅱ, GCS score, SOFA score, ISS score, number of blood transfusions, mechanical ventilation, norepinephrine drug use, pathogenic culture and diabetes has a good predictive value for sepsis in patients with multiple trauma in the later stage, which is worth promoting.

Objective sampling method was used to conduct a questionnaire survey on outpatients in two hospitals in Guangdong province in order to evaluate patients’ satisfaction with the quality of medical service. This paper explored the factors that affect patients’ evaluation of medical service quality, and found that patients’ age was negatively correlated with the evaluation of medical service quality. It is suggested that the establishment of friendly medical institutions should be carried out according to the national policy. At the same time, the management mechanism of hospital should be improved, the number of medical service centers for "efficient" should be increased, and the medical service personnel should be regularly trained; carry out medical knowledge education in community, improve the popularization of personal medical knowledge and close the cognitive gap between doctors and patients.

Objective To research the procedure for creating an animal model of mitral regurgitation by implanting a device through the apical artificial chordae tendineae, and to assess the stability and dependability of the device. Methods Twelve large white swines were employed in the experiments. Through a tiny hole in the apex of the heart, the artificial chordae tendineae of the mitral valve was inserted under the guidance of transcardiac ultrasonography. Before, immediately after, and one and three months after surgery, cardiac ultrasonography signs were noted. Results All models were successfully established. During the operation and the follow-up, no swines died. Immediately after surgery, the mitral valve experienced moderate regurgitation. Compared with preoperation, there was a variable increase in the amount of regurgitation and the values of heart diameters at a 3-month follow-up (P<0.05). Conclusion In off-pump, the technique of pulling the mitral valve leaflets with chordae tendineae implanted transapically under ultrasound guidance can stably and consistently create an animal model of mitral regurgitation.

Objective:To establish and validate a prediction model for the risk of major upper gastrointestinal bleeding in patients with varices of liver cirrhosis.Method:This study retrospectively collected the clinical data of patients with esophageal and gastric variceal bleeding who were admitted to the emergency department of Ningxia Medical University General Hospital from October 2019 to October 2022. The patients were divided into modeling group and validation group according to the ratio of 7:3 by random number table method. The observation index was whether the upper gastrointestinal bleeding occurred within 24 hours after admission. The predictors in the logistic regression model were used to construct a prediction model for the risk of major upper gastrointestinal bleeding in patients with varices with liver cirrhosis, and the area under the receiver operating characteristic curve (AUC), the correction curve and the decision curve were analyzed to evaluate the discriminatory ability, accuracy and clinical utility of the prediction model.Results:A total of 305 patients were included, including 215 and 90 in the modeling and validation groups, respectively, and the clinical data of the two groups were comparable. Multivariate logistic regression showed that systolic blood pressure ( OR=0.918, 95% CI: 0.860-0.980, P=0.010), MAP(ASH) score ( OR=1.993, 95% CI: 1.017-3.907, P=0.045), Child-Pugh score ( OR=1.999, 95% CI: 1.139-3.510, P=0.016) and model for end-stage liver disease (MELD) ( OR=1.398, 95% CI: 1.037-1.886, P=0.028) were independent influencing factors for the occurrence of upper gastrointestinal bleeding in patients with liver cirrhosis varices. The AUC of the prediction model in the modeling group was 0.936 (95% CI: 0.895-0.976), and that of the prediction model in the validation group was 0.891 (95% CI: 0.807-0.975), the prediction model had good identification, calibration, and clinical application value. Conclusions:Systolic blood pressure, MAP (ASH) score, Child-Pugh score, and prediction models constructed by end-stage liver disease models are helpful for early prediction of the risk of upper gastrointestinal bleeding in patients with cirrhosis varices in the emergency department.

Objective:To explore the prognostic factors of elderly patients with community-acquired pneumonia-related sepsis and to construct a prediction model.Methods:The clinical data of elderly patients with community-acquired pneumonia-associated sepsis from October 2020 to October 2022 in the General Hospital of Ningxia Medical University from October 2020 to October 2022 were retrospectively included, and the clinical data of the two groups were divided into the modeling population and the validation population in the ratio of 7:3 by random number table method, and the clinical data of the two groups were compared. According to the 30-day outcomes of admission, the patients were divided into survival group and death group, and the independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-related sepsis were screened out by LASSO regression and multivariate logistic regression analysis, and the nomogram prediction model was constructed by R software. The area under the curve (AUC), calibration curve and decision curve of the receiver operating characteristic curve were used to validate the nomogram prediction model in the modeling population and the validation population to judge its discrimination, calibration and clinical practicability.Results:A total of 472 patients were included, with 331 and 141 models and validations, respectively, indicating that the clinical data were comparable between the modeled and validated populations. LASSO regression and multivariate logistic regression analysis showed that pneumonia severity index (PSI) score and sequential organ failure assessment (SOFA) score were independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-associated sepsis. The AUC of the modeled population prediction model was 0.984 (95% CI: 0.975-0.994), and the AUC of the validated population prediction model was 0.961 (95% CI: 0.926-0.996). The nomogram prediction model has good discrimination, calibration and clinical practicability in both the modeled and validated populations. Conclusions:The nomogram prediction model established in the study has high accuracy for early identification and risk of sepsis in elderly patients with CAP and can guide for clinicians to formulate personalized interventions.

Objective:To establish a predictive model of acute physiological and chronic health status score (APACHEⅡ) and the British Thoracic Society modified pneumonia score (CURB-65) score on the prognosis of patients with emergency severe pneumonia complicated with acute respiratory distress syndrome (ARDS) and to evaluate the predictive effect.Methods:The relevant clinical data of patients with severe pneumonia combined with ARDS admitted to the Emergency Intensive Care Unit (EICU) of General Hospital of Ningxia Medical University from January 2017 to December 2021 were retrospectively collected, and different logistic regression models were established. On this basis, three prediction models (model 1: APACHE Ⅱ score, model 2: CURB-65 score, Model 3: APACHE Ⅱ score combined with CURB-65 score) were established and the accuracy of the prediction model was evaluated by repeating 50 times of 10-fold cross-validations. The efficacy of the prediction model was evaluated by C statistics, Kendall's tau-a rank correlation coefficient, R2, Brier score, calibration curve, net reclassification index (NRI), composite discriminant improvement index (IDI) and decision curve (DCA).Results:The study eventually included 108 patients, including 81 males and 27 females, with mean age (57.92 ± 16.56) years. Forty-eight patients survived and 60 patients died. The age of the death group was older, and APACHEⅡ score and CURB-65 score of the death group were all greater than those in the survival group, and the differences were statistically significant ( P<0.05). Different logistic regression models showed that the OR value of model 1 was 1.12 (95% CI: 1.06 -1.20), that of model 2 was 2.21 (95% CI: 1.43 - 3.40), and that of model 3 was 1.10 (95% CI: 1.03 - 1.18) and 1.95 (95% CI: 1.24 - 3.07). The average accuracy of model 1, model 2, and model 3 were 0.68±0.14, 0.66±0.11, and 0.72±0.13, respectively. The C statistic, Kendall's Tau-a rank correlation coefficient, R2 and Bril score of model 3 were better than those of model 1 and model 2, and the different models fit well ( P<0.05). The calibration curve results of 500 resampling showed that the calibration degree of model 2 was better than that of model 1 and model 3, and the predictive ability of model 3 was improved compared with model 1, and the IDI was increased by 0.08 ( P<0.01). Compared with model 2, the reclassification ability of cases and the comprehensive discrimination ability of model 3 were improved ( P<0.01). The decision curves of different models showed that the net benefit of model 3 was higher than that of single model 1 and model 2 when the prediction probability was about 25% to 55%, while the benefits of model 1, model 2 and model 3 in other probability prediction intervals were basically equal. Conclusions:Both APACHE Ⅱ score and CURB-65 score have certain predictive power for prognosis of patients with emergency severe pneumonia and ARDS, and their combination has the best prediction effect. CURB-65 score has fewer parameters, and its prognostic benefit in emergency patients with severe pneumonia complicated with ARDS is basically equivalent to APACHE Ⅱ score, which may be more suitable for the prognosis evaluation of emergency patients with severe pneumonia complicated with ARDS.

METTL3 and METTL14 are two components that form the core heterodimer of the main RNA m6A methyltransferase complex (MTC) that installs m6A. Surprisingly, depletion of METTL3 or METTL14 displayed distinct effects on stemness maintenance of mouse embryonic stem cell (mESC). While comparable global hypo-methylation in RNA m6A was observed in Mettl3 or Mettl14 knockout mESCs, respectively. Mettl14 knockout led to a globally decreased nascent RNA synthesis, whereas Mettl3 depletion resulted in transcription upregulation, suggesting that METTL14 might possess an m6A-independent role in gene regulation. We found that METTL14 colocalizes with the repressive H3K27me3 modification. Mechanistically, METTL14, but not METTL3, binds H3K27me3 and recruits KDM6B to induce H3K27me3 demethylation independent of METTL3. Depletion of METTL14 thus led to a global increase in H3K27me3 level along with a global gene suppression. The effects of METTL14 on regulation of H3K27me3 is essential for the transition from self-renewal to differentiation of mESCs. This work reveals a regulatory mechanism on heterochromatin by METTL14 in a manner distinct from METTL3 and independently of m6A, and critically impacts transcriptional regulation, stemness maintenance, and differentiation of mESCs.
Animals ; Mice ; Methylation ; Chromatin ; Histones/metabolism* ; RNA, Messenger/genetics* ; Methyltransferases/metabolism* ; RNA/metabolism*

Objective    To summarize the early outcomes of totally thoracoscopic minimally invasive aortic valve replacement (AVR) and double valve replacement (DVR). Methods    The clinical data of patients who underwent totally thoracoscopic minimally invasive AVR or DVR in Guangdong Provincial People’s Hospital from April 2020 to January 2021 were retrospectively analyzed. The patients were divided into an AVR group and a DVR group according to the surgical method, and the clinical data of the two groups were compared. Results    Finally 22 patients were enrolled, including 14 males and 8 females with an average age of 50.0±11.2 years at operation. Eight patients were degenerative disease, 8 were rheumatic heart disease combined with valvular disease, and 6 were bicuspid aortic valve. Out of the 22 patients, 16 underwent AVR alone, and 6 underwent DVR. All patients completed the operation successfully, and there was no death. Perivalvular leakage during surgery occurred in 2 patients. The average cardiopulmonary bypass time was 187.0±39.9 minutes, and aortic cross-clamping time was 117.0 (99.0, 158.0) minutes. Duration of mechanical ventilation and intensive care unit stay was 9.5 (4.8, 18.3) hours and 41.0 (34.0, 64.0) hours, respectively. The volume of chest drainage at the first 24 hours after surgery was 214.0±124.6 mL, and the postoperative hospital stay was 5.5 (4.0, 8.3) days. The cardiopulmonary bypass time and aortic cross-clamping time in the DVR group were longer than those in the AVR group, and the volume of chest drainage at 24 hours after surgery was more than that in the AVR group, with a statistical difference (P<0.05). Echocardiography before hospital discharge showed paravalvular leakage in 1 patient. There was no death during follow-up of 5.9±3.0 months. Conclusion    The early outcome of totally thoracoscopic minimally invasive AVR and DVR is satisfactory, and the approach of surgery is worth exploring.

Objective    To investigate the predictive value of right atrial myocardial fibrosis in the prognosis of isolated tricuspid regurgitation surgery after left heart valve surgery. Methods    The patients who underwent tricuspid valvuloplasty by the same operator in Guangdong Provincial People's Hospital from April 2016 to August 2021 due to long-term isolated severe tricuspid regurgitation after left heart valve surgery were included in the study. According to the degree of right atrial myocardial fibrosis, the patients were divided into three groups: a mild group, a moderate group, and a severe group. The clinical data of these patients were compared and analyzed. Results    A total of 75 patients were enrolled, including 16 males and 59 females with an average age of 57.0±8.4 years. There were 30 patients in the mild group, 29 patients in the moderate group and 16 patients in the severe group. In terms of the preoperative data, there were statistical differences in cardiac function grade, right atrial diameter, tricuspid incompetence area among the three groups (P<0.05). In terms of the postoperative data, there were statistical differences among the three groups in the cardiopulmonary bypass time, mechanical ventilation time, ICU monitoring time, complication rate and mortality (P<0.05). Further pairwise comparison showed that, compared with the mild group, the severe group had longer mechanical ventilation time (P=0.024), longer ICU monitoring time (P=0.003) and higher incidence of postoperative complications (P=0.024), while the moderate group had no statistical difference in all aspects (P>0.05); compared with the moderate group, the severe group had longer ICU monitoring time (P=0.021) and higher incidence of complications (P=0.006). Conclusion    The early outcome of tricuspid valvuloplasty in patients with isolated tricuspid regurgitation after left heart valve surgery with severe right atrial myocardial fibrosis is worse than that in the patients with mild and moderate fibrosis, suggesting that the degree of myocardial fibrosis in the right atrium can be a predictor of the effect of tricuspid regurgitation surgery and a judgement indicator of the surgery timing.

Objective:To explore the prognostic risk factors of patients with multiple injuries and establish a nomogram prediction model.Methods:The clinical data of 291 patients with multiple injuries admitted to the Emergency Intensive Care Unit (EICU) of General Hospital of Ningxia Medical University were collected, including sex, age, open injury, norepinephrine use, mechanical ventilation, time to hospital after injury, distance to hospital, relative lymphocyte value, platelet count, lactic acid, injury severity score (ISS), acute physiology and chronic health evaluationⅡ (APACHE Ⅱ), Glasgow coma scale (GCS), number of blood transfusions, number of operations, and previous history of diabetes, hypertension and smoking within 24 h after admission. According to whether the condition worsened during the hospitalization of EICU, the patients were divided into the deterioration group and improvement group. SPSS26.0 software was used for statistical analysis of the data, univariate and multivariate analysis were used to screen the factors affecting the prognosis of patients with multiple injuries, receiver operating characteristic (ROC) curve and forest chart were drawn, and the influencing factors in binary Logistic regression model were used to make the nomogram.Results:Mechanical ventilation, norepinephrine use, age, relative lymphocyte value, lactic acid, APACHE-II score, GCS score, and number of operations were significant for predicting the prognosis of patients with multiple injuries ( P<0.05). The independent influencing factors obtained by binary Logistic regression model were age, lactic acid, APACHE-Ⅱ score and number of operations. ROC curve analysis showed that the area under the curve was the largest in multi-factor combined prediction, followed by APACHE-Ⅱ score. The diagnostic cut-off value of each index was as follows: age >58 years old, relative lymphocyte value≤ 8.62%, lactic acid >1.72, APACHE-Ⅱ score >16, GCS score≤ 6, and number of operations≤ 0. The R software was used to establish a nomogram of the influencing factors in the binary Logistic regression model, which had good predictive value. Conclusions:The nomogram constructed by age, relative lymphocyte value, lactic acid, APACHE-Ⅱ score, GCS score, number of operations, mechanical ventilation, and norepinephrine use has a good predictive value for the prognosis of patients with multiple injuries, and is worthy of promotion..