Objective Develop a prediction model for full-term neonatal mortality and conduct internal validation.Methods 86 full-term newborns who died in the pediatric department of Xuzhou Central Hospital from January 1,2015 to December 31,2023 were selected.According to the sample estimation method,135 full-term infants who were hospitalized during the same period were randomly selected as the control group.Clinical data such as maternal and child birth history,blood routine within 24hours after birth,coagulation function,arterial carbon dioxide pressure(PaCO2),and serum total bilirubin were collected.Using single factor analysis,stepwise regres-sion,and multiple Logistic regression analysis to screen possible predictive factors and establish a predictive model.The receiver operating characteristic(ROC)curve was used to evaluate the discriminative power of the model,and Hosmer Lemeshow was used to test the calibra-tion of the evaluation model.Bootstrap method was used for internal validation.Results Amniotic fluid contamination(OR=3.818,95％CI:1.009-14.447,P=0.048),coagulation dysfunction(OR=12.981,95％CI 3.732-45.152,P＜0.001),gynecological inflamma-tory diseases(OR=7.203,95％CI:1.216-42.659,P=0.03),mechanical ventilation(OR=54.451,95％CI:12.913-229.619,P＜0.001),PCO2(OR=1.131,95％CI:1.055-1.212,P=0.001),and serum lactate(OR=4.540,95％CI:2.561-8.046,P＜0.001)are independent influencing factors of full-term infant mortality,which can predict the occurrence of neonatal mortality in full-term infants(sensitivity 75.8％,specificity 87.0％,AUC=0.814).The Hosmer Lemeshow test showed that the model had good consis-tency with the actual occurrence probability of full-term neonatal mortality in clinical practice(x2=3.787,P=0.876).After internal validation by Bootstrap,the model had good discrimination(AUC=0.849).Conclusion A predictive model for mortality risk factors can be established based on maternal pregnancy history and clinical data within 24hours after full-term birth,which helps to make clinical decisions in advance.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

At present,with the development of new diagnostic technologies,the detection rate of aortic dissection has been increasing year by year,but its mortality rate still remains high.Cardiovascular disease is a chronic inflammato-ry disease,and vascular inflammation plays a major role in the progression of aortic dissection.Therefore,this article sys-tematically describes the specific roles and mechanisms of inflammatory cells,inflammatory factors,and inflammasomes in the development of aortic dissection.

At present,with the development of new diagnostic technologies,the detection rate of aortic dissection has been increasing year by year,but its mortality rate still remains high.Cardiovascular disease is a chronic inflammato-ry disease,and vascular inflammation plays a major role in the progression of aortic dissection.Therefore,this article sys-tematically describes the specific roles and mechanisms of inflammatory cells,inflammatory factors,and inflammasomes in the development of aortic dissection.

Objective Develop a prediction model for full-term neonatal mortality and conduct internal validation.Methods 86 full-term newborns who died in the pediatric department of Xuzhou Central Hospital from January 1,2015 to December 31,2023 were selected.According to the sample estimation method,135 full-term infants who were hospitalized during the same period were randomly selected as the control group.Clinical data such as maternal and child birth history,blood routine within 24hours after birth,coagulation function,arterial carbon dioxide pressure(PaCO2),and serum total bilirubin were collected.Using single factor analysis,stepwise regres-sion,and multiple Logistic regression analysis to screen possible predictive factors and establish a predictive model.The receiver operating characteristic(ROC)curve was used to evaluate the discriminative power of the model,and Hosmer Lemeshow was used to test the calibra-tion of the evaluation model.Bootstrap method was used for internal validation.Results Amniotic fluid contamination(OR=3.818,95％CI:1.009-14.447,P=0.048),coagulation dysfunction(OR=12.981,95％CI 3.732-45.152,P＜0.001),gynecological inflamma-tory diseases(OR=7.203,95％CI:1.216-42.659,P=0.03),mechanical ventilation(OR=54.451,95％CI:12.913-229.619,P＜0.001),PCO2(OR=1.131,95％CI:1.055-1.212,P=0.001),and serum lactate(OR=4.540,95％CI:2.561-8.046,P＜0.001)are independent influencing factors of full-term infant mortality,which can predict the occurrence of neonatal mortality in full-term infants(sensitivity 75.8％,specificity 87.0％,AUC=0.814).The Hosmer Lemeshow test showed that the model had good consis-tency with the actual occurrence probability of full-term neonatal mortality in clinical practice(x2=3.787,P=0.876).After internal validation by Bootstrap,the model had good discrimination(AUC=0.849).Conclusion A predictive model for mortality risk factors can be established based on maternal pregnancy history and clinical data within 24hours after full-term birth,which helps to make clinical decisions in advance.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:Construct a combined detection model of miR-202-5p and interleukin-6 (IL-6) and explore its diagnostic value for acute myocardial infarction (AMI).Methods:Clinical data of 202 patients with coronary atherosclerotic heart disease (CHD) who were admitted to the Department of Cardiology and Emergency Department of Hebei People's Hospital from August 2020 to August 2022 were retrospectively analyzed, including 106 AMI patients and 96 non AMI patients. The clinical characteristics and blood levels of miR-202-5p and IL-6 were compared between the two groups, T-test was used for inter group comparison of measurement data that conforms to normal distribution, non parametric rank sum test was used for inter group comparison of measurement data that does not conform to normal distribution, and χ2 test was used for inter group comparison of count data. Binary Logistic regression model was used to determine the independent influencing factors of AMI, and a combined diagnostic model was constructed according to the analysis results, the diagnostic efficacy of miR-202-5p, IL-6 and combined detection for AMI was evaluated by ROC curve, and the clinical diagnostic effect was observed. Results:The expression levels of serum total cholesterol (4.40 (3.71, 5.00) mmol/L), low density lipoprotein cholesterol (2.99 (2.39,3.47) mmol/L), lipoprotein a (276.80 (182.58,390.13) mg/L), interleukin-4(IL-4)(2.69(2.29,3.16) μg/L), IL-6(89.82(68.26,107.16) μg/L) in AMI group were significantly higher than those of non-AMI group (4.04 (3.12, 4.73) mmol/L, 2.75 (2.15, 3.21) mmol/L, 213.45 (146.73, 348.80) mg/L, 2.46 (1.92, 3.01)] μg/L, 45.89 (32.38, 62.83) μg/L, while miR-202-5p(0.33 (0.27,0.38)) was lower than that in the non-AMI group (0.51 (0.36,0.68)), ( H values were 4 167.50, 4 234.00, 4 262.50, 4 228.00, 1 513.00, and 2 098.50, respectively; P values were 0.027, 0.040, 0.047, 0.038, <0.001, <0.001, respectively). Multivariate binary logistic regression analysis showed that high levels of IL-6 and low levels of miR-202-5p were independent risk factors for AMI. The joint diagnostic model of IL-6 and miR-202-5p was Logit (P)=-1.046-5.236 × miR-202-5p+0.051 × IL-6, with probability value P as the diagnostic indicator and P=0.45 as the diagnostic threshold. ROC curve results showed that the area under curve (AUC) of IL-6 and miR-202-5p were 0.851 and 0.794, respectively, while the AUC of the combined diagnosis model was 0.894, indicating that the diagnosis accuracy was higher than that of a single index. Compared with isolated detection, the sensitivity, specificity and Kappa value of the IL-6+miR-202-5p collaborative test for AMI prediction were increased, especially the diagnosis results were close to a high degree of agreement with the actual results ( Kappa=0.732). Conclusion:High levels of IL-6 and low levels of miR-202-5p are independent influencing factors for AMI, and the combined diagnosis model of the two has clinical application value.

Objective To investigate the mechanism of Ganmao Qingre Pills(GQP)against lung injury based on network pharmacology,molecular docking and in vivo experiments.Methods The potential targets of GQP in the treatment of lung injury were screened through traditional Chinese medicine systems pharmacology database and analysis platform(TCM-SP)and Genecards.A"Chinese medicine-active ingredients-targets"network was constructed using Cytoscape 3.9.0 software,then gene ontology(GO)function and Kyoto encyclopaedia of genes and genomes(KEGG)pathway enrichment analysis for potential targets were conducted using a bioinformatics cloud platform.We established a protein-protein interaction(PPI)network,which was intersected with"Chinese medicine-active ingredients-targets"network to obtain core targets.The molecular docking between key target proteins and active ingredients was performed.The effect of GQP on these key target proteins was verified by using a mouse model of lung injury.Results A total of 707 targets for the treatment of lung injury by GQP were identified,corresponding to 107 active ingredients in 11 Chinese medicines.It was found that GQP might regulate targets such as PTGS1,AR,and ACHE through active ingredients including stigmasterol,luteolin,and acacetin using the"Chinese medicine-active ingredients-targets"network analysis.Core targets such as SRC,EGFR,and STAT3 were discovered by using the PPI network.Key target proteins,including CDK1,CDK2,EGFR,ESR1 and SRC,were screened through the intersection analysis of the PPI network and"Chinese medicine-active ingredients-targets"network.Molecular docking study showed that stigmasterol,luteolin and acacetin had good binding effects with CDK1,CDK2,EGFR,ESR1,and SRC,respectively.In vivo experiments revealed that GQP dose-dependently attenuated lung injury and inflammatory infiltration,reduced the release of pro-inflammatory factors TNF-α,IL-1β and IL-6,increased the expression of CDK1 and CDK2,and decreased the expression of EGFR,ESR1 and SRC in lung injury mice.Conclusion The therapeutic effect of GQP against lung injury may be achieved through interaction of key active ingredients(stigmasterol,luteolin,and acacetin)and key target proteins(CDK1,CDK2,EGFR,ESR1,SRC),and regulation of key signaling pathways such as neuroactive ligand-receptor interactions,cancer pathways,and calcium signaling pathways.

Objective:To evaluate the effect of preemptive analgesia with ibuprofen on postoperative pain following single posterior tooth implantation, aiming to provide a clinical reference for its application.Methods:A multicenter, randomized, double-blind, placebo-controlled parallel-group trial was conducted. A total of 82 participants were included in the trial, meeting the eligibility criteria from April 2022 to April 2024 at the Capital Medical University School of Stomatology (40 cases), Beijing TianTan Hospital, Capital Medical University (22 cases), Beijing Chao-Yang Hospital, Capital Medical University (20 cases). Participants were randomly assigned in a 1∶1 ratio to either the ibuprofen group or the control group, with each group comprising 41 individuals. Participants in the ibuprofen group received 300 mg of sustained-release ibuprofen capsules orally 15 min before surgery, while the control group received a placebo. Both groups received the same postoperative analgesic regimen for 3 days. Pain scores were assessed using the numerical rating scale at 30 min, 4 h, 6 h, 8 h, 24 h, 48 h, and 72 h postoperatively, and the additional use of analgesic medication was recorded from days 4 to 6 postoperatively.Results:A total of 82 participants were initially enrolled in the study, with 7 dropouts (4 from the control group and 3 from the ibuprofen group), resulting in 75 participants (37 in the control group and 38 in the ibuprofen group) completing the trial. There were no reports of adverse events such as nausea or vomiting among the participants. The ibuprofen group exhibited significantly lower pain scores at 4 h, 6 h and 8 h [1.0 (0.0, 2.0), 1.0 (0.0, 2.0), 1.5 (0.0, 3.0) ] postoperatively compared to the control group 4 h, 6 h and 8 h [2.0 (1.0, 3.0), 3.0 (1.5, 4.0), 2.0 (1.0, 4.0)] ( Z=-1.99, P=0.047; Z=-3.01, P=0.003; Z=-2.10, P=0.036). The proportions of patients requiring additional analgesic medication between days 4 and 6 post-surgery were 18.4% (7/38) in the ibuprofen group and 27.0% (10/37) in the control group, with no significant difference (χ 2=0.79, P=0.373). The median additional medication usage postoperatively was [0.0 (0.0, 0.0) pills] in the ibuprofen group and [0.0 (0.0, 1.0) pills] in the control group, with no significant difference ( Z=-0.78, P=0.439). Conclusions:Preemptive analgesia with ibuprofen effectively reduces postoperative pain following tooth implantation, representing a safe and effective perioperative pain management strategy.

Objective: To investigate the influencing factors of lumbar disc herniation (LDH) among elderly patients with osteoporosis (OP), so as to provide the basis for early prevention of LDH in OP patients. Methods: The patients aged 60 years and above with OP who were treated in the clinic of Beijing Jishuitan Hospital from December 2022 to December 2023 were recruited as the study subjects. The data of demographic and clinical information were collected through the hospital medical record system. LDH was diagnosed according to the LDH Diagnosis and Treatment Guidelines. Factors affecting LDH among elderly patients with OP were identified using a multivariable logistic regression model. Results: A total of 500 patients with OP were included, with 188 males (37.60%) and 312 females (62.40%). The mean age was (69.05±3.28) years, and the course of OP was (6.37±2.11) years. There were 196 patients living alone, accounting for 39.20%. LDH among elderly patients with OP were detected in 78 cases, accourcing for 15.60%. Multivariable logistic regression analysis showed that the patients who were at ages of 70 years and above (OR=1.465, 95%CI: 1.197-1.793), lived alone (OR=1.777, 95%CI: 1.093-2.889), had a history of fracture (OR=1.799, 95%CI: 1.070-3.023) and scored higher in quality of life (OR=1.405, 95%CI: 1.230-1.605) were at higher risks of LDH, while the patients who had a history of taking calcium supplements (OR=0.562, 95%CI: 0.345-0.915) were at lower risks of LDH. Conclusion Age, living situation, history of fracture, history of taking calcium supplements and quality of life were influencing factors for LDH among elderly patients with OP.