Objective To investigate mortality risk factors and characterize pathogen distribution and antimicrobial resistance patterns in intensive care unit(ICU)patients with suspected infection following surgery.Methods A total of 65 hospitals in 16 provinces in China from July 1,2021,to December 31,2022.Clinical data were collected for surgical patients transferred to the ICU with suspected infection.Data included demographics[sex,age,underlying conditions(hypertension,diabetes,cardiovascular/cerebrovascular disease,hematologic disease)],surgical site,infection site,microbiological results with susceptibility testing,drug resistance and acute physiology and chronic health evaluationⅡ(APACHEⅡ)scores and the length of hospital stays.Patients were stratified by prognosis into death group and survial group,by drug resistance status into resistant and non-resistant groups.Univariate and multivariate Logistic regression identified risk factors for mortality and antimicrobial resistance.Draw the receiver operator characteristic curve(ROC curve)to evaluate the predictive value of each risk factor for patient prognosis and drug resistance occurrence.Results A total of 677 patients with suspected postoperative infection in the ICU were enrolled.There were 96 deaths and 591 survivors.① Analysis of risk factors affecting prognosis:univariate analysis showed that compared with the survival group,the patients in the had a higher APACHEⅡscore,the proportion of patients with previous cerebrovascular disease,surgery sites in the abdomen,chest,brain,pelvis,limbs,other areas,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,Gram-positive bacterial infection(Candida),fungal infection,multi-drug resistant bacterial infection was higher,and the length of hospital stay was shorter(all P<0.05).Multivariate Logistic regression analysis identified higher APACHEⅡscore[odds ratio(OR)=1.15,95%confidence interval(95%CI)was 1.11-1.20],pulmonary infection(OR=4.07,95%CI was 2.05-8.11),bloodstream infection(OR=2.61,95%CI was 1.52-4.51),and urinary tract infection(OR=2.20,95%CI was 1.01-4.42)were independent risk factors for prognosis(all P<0.05).The ROC curve analysis showed that the death risk prediction model established based on the above independent risk factors had certain predictive value for the prognosis of ICU postoperative patients with suspected infection,area under the curve(AUC)=0.820,95%CI was 0.770-0.860,P<0.05.②Regarding antimicrobial resistance:250 patients developed resistance and 427 did not.Univariate analysis showed compared with the non-resistant group,the APACHEⅡscore,the proportion of patients with cerebrovascular diseases,hematological diseases,surgeries at chest,brain,limbs,other sites,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,intracranial infection,Gram-negative bacillus infection,and Gram-positive cocci infection(Staphylococcus epidermidis,Staphylococcus aureus,Enterococcus faecalis),and the mortality rate in the resistant group were significantly higher,the proportion of patients with surgeries at abdominal cavity,pelvic cavity and abdominal cavity infection were significantly lower,and the length of hospital stay was significantly longer(all P<0.05).Multivariate Logistic regression analysis bloodstream infection(OR=4.00,95%CI was 2.22-7.19),urinary tract infection(OR=3.25,95%CI was 1.47-7.17),Klebsiella pneumoniae infection(OR=2.23,95%CI was 11.22-44.02),Acinetobacter baumannii infection(OR=48.12,95%CI was 20.10-115.17),Pseudomonas aeruginosa infection(OR=34.06,95%CI was 13.00-89.25),Escherichia coli infection(OR=24.97,95%CI was 10.55-59.13),Stenotrophomonas maltophilia infection(OR=19.04,95%CI was 3.30-109.96),and Staphylococcus aureus infection(OR=13.48,95%CI was 4.57-39.78)were independent risk factors for resistance(all P<0.01).The ROC curve analysis showed that the predictive model for drug resistance established based on the above independent risk factors had certain predictive value for drug resistance in adult patients with suspected infections after surgery in the ICU.The AUC=0.920,95%CI was 0.890-0.940,P<0.05.Conclusion Higher APACHEⅡscores and the presence of pulmonary,bloodstream,or urinary tract infections were associated with increased mortality in ICU patients with suspected postoperative infection.Patients with bloodstream or urinary tract infections,or infections caused by Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,Escherichia coli,Stenotrophomonas maltophilia,or Staphylococcus aureus,had significantly higher odds of developing antimicrobial resistance.

Objective:To investigate the risk of hospital death in patients with traumatic hemorrhagic shock combined with multiple organ dysfunction syndrome(MODS)predicted by discriminant analysis.Methods:This study was a single-center retrospective study. From January 2013 to May 2023, patients with traumatic hemorrhagic shock complicated with MODS admitted to Peking University People's Hospital were selected as the research objects. According to the in-hospital survival, the patients were divided into survival group (205 cases) and death group (29 cases). The general condition, injury assessment, laboratory indexes, complications and clinical scores of the two groups were compared. Wilks's Lambda stepwise discriminant analysis was used to establish a discriminant model for in-hospital death in patients with traumatic hemorrhagic shock combined with MODS. the Receiver operating characteristic curve (ROC) was drawn and the Area under the curve (AUC) was calculated. The cross-validation method was used to evaluate the accuracy of the prediction results of the established model.Results:There was a statistical difference between the survival group and the death group in terms of the main bleeding site (limbs), the time from injury to hospital admission, temperature, platelet count, prothrombin time, activated partial thrombin time, fibrinogen, albumin, serum creatinine, estimated glomerular filtration rate, uric acid, cardiac troponin I, procalcitonin, base excess, lactate to albumin ratio, glucose to albumin ratio, acute respiratory distress syndrome, acute kidney injury, acute myocardial injury, traumatic induced coagulopathy, ISS, APACHEⅡ score and SOFA scores. There are four indicators entering the final discrimination model: Prothrombin time, ISS score, estimated glomerular filtration rate, lactate to albumin ratio. The AUC for predicting the risk of death in patients with traumatic hemorrhagic shock combined with MODS was 0.791, and the 95% CI was 0.671 to 0.911. Conclusions:The established discriminant model is highly accurate in predicting the risk of hospital death in patients with traumatic hemorrhagic shock complicated with MODS. Prothrombin time, ISS score, estimated glomerular filtration rate and lactate to albumin ratio were associated with an increased risk of death from traumatic hemorrhagic shock with MODS.

OBJECTIVE: To explore the feasibility of establishing a temporary trauma team led by trauma experts in primary hospitals for disaster medical rescue. METHODS: In the coal mine flooding accident in Xiaoyi City, Shanxi Province on December 15, 2021, according to the local emergency plan and the characteristics of the accident, the trauma experts trained the medical staff from the local primary hospital on advanced trauma life support (ATLS) and damage control surgery (DCS) in the short time interval between the occurrence of the mine disaster and the admission of medical staff to the disaster scene. A temporary trauma team composed of trauma experts, ATLS team, and DCS team was formed to provide early diagnosis and treatment for survivors before and in the hospital. RESULTS: The miners were found on the 36th hour of the disaster. All 22 miners were male, and 2 died underground. Another 20 people were rescued 39－43 hours after the disaster, with a median age of 48 years (34-57 years). All the survivors suffered from hypothermia, dehydration, maceration of feet and other injuries. There were 18 cases of acute inhalation tracheobronchitis, 14 cases of electrolyte acid-base disturbance, 6 cases of trunk contusion, 1 case of psoas major hematoma, and 1 case of lower extremity hematoma. Deep vein thrombosis was in 4 cases. The ATLS team focused on injury assessment, rewarming and rehydration within 50－60 minutes before admission, and completed auxiliary examinations within 2 hours after admission to clarify the diagnosis. The DCS team evaluated 6 patients with mechanical blunt trunk injury and excluded the indication of emergency surgery. The trauma experts conducted the whole process of supervision and quality control of disaster rescue. The positive rate of capillary refill test in the all survivors at the third hour of admission was significantly lower than that immediately after being rescued (75.0% vs. 15.0%, P=0.000 3), and they were discharged 4－7 days after admission. CONCLUSION Under the leadership of trauma experts and relying on the medical staff of primary hospitals, it is feasible to establish and train a temporary trauma team with ATLS and DCS functions to participate in the medical rescue of disasters, which is in line with the current national conditions of China.
Humans ; Adult ; Middle Aged ; Male ; Rescue Work/organization & administration* ; China ; Disasters ; Patient Care Team/organization & administration* ; Wounds and Injuries/therapy* ; Advanced Trauma Life Support Care/organization & administration* ; Disaster Planning/organization & administration* ; Emergency Medical Services/organization & administration*

Objective To investigate mortality risk factors and characterize pathogen distribution and antimicrobial resistance patterns in intensive care unit(ICU)patients with suspected infection following surgery.Methods A total of 65 hospitals in 16 provinces in China from July 1,2021,to December 31,2022.Clinical data were collected for surgical patients transferred to the ICU with suspected infection.Data included demographics[sex,age,underlying conditions(hypertension,diabetes,cardiovascular/cerebrovascular disease,hematologic disease)],surgical site,infection site,microbiological results with susceptibility testing,drug resistance and acute physiology and chronic health evaluationⅡ(APACHEⅡ)scores and the length of hospital stays.Patients were stratified by prognosis into death group and survial group,by drug resistance status into resistant and non-resistant groups.Univariate and multivariate Logistic regression identified risk factors for mortality and antimicrobial resistance.Draw the receiver operator characteristic curve(ROC curve)to evaluate the predictive value of each risk factor for patient prognosis and drug resistance occurrence.Results A total of 677 patients with suspected postoperative infection in the ICU were enrolled.There were 96 deaths and 591 survivors.① Analysis of risk factors affecting prognosis:univariate analysis showed that compared with the survival group,the patients in the had a higher APACHEⅡscore,the proportion of patients with previous cerebrovascular disease,surgery sites in the abdomen,chest,brain,pelvis,limbs,other areas,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,Gram-positive bacterial infection(Candida),fungal infection,multi-drug resistant bacterial infection was higher,and the length of hospital stay was shorter(all P<0.05).Multivariate Logistic regression analysis identified higher APACHEⅡscore[odds ratio(OR)=1.15,95%confidence interval(95%CI)was 1.11-1.20],pulmonary infection(OR=4.07,95%CI was 2.05-8.11),bloodstream infection(OR=2.61,95%CI was 1.52-4.51),and urinary tract infection(OR=2.20,95%CI was 1.01-4.42)were independent risk factors for prognosis(all P<0.05).The ROC curve analysis showed that the death risk prediction model established based on the above independent risk factors had certain predictive value for the prognosis of ICU postoperative patients with suspected infection,area under the curve(AUC)=0.820,95%CI was 0.770-0.860,P<0.05.②Regarding antimicrobial resistance:250 patients developed resistance and 427 did not.Univariate analysis showed compared with the non-resistant group,the APACHEⅡscore,the proportion of patients with cerebrovascular diseases,hematological diseases,surgeries at chest,brain,limbs,other sites,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,intracranial infection,Gram-negative bacillus infection,and Gram-positive cocci infection(Staphylococcus epidermidis,Staphylococcus aureus,Enterococcus faecalis),and the mortality rate in the resistant group were significantly higher,the proportion of patients with surgeries at abdominal cavity,pelvic cavity and abdominal cavity infection were significantly lower,and the length of hospital stay was significantly longer(all P<0.05).Multivariate Logistic regression analysis bloodstream infection(OR=4.00,95%CI was 2.22-7.19),urinary tract infection(OR=3.25,95%CI was 1.47-7.17),Klebsiella pneumoniae infection(OR=2.23,95%CI was 11.22-44.02),Acinetobacter baumannii infection(OR=48.12,95%CI was 20.10-115.17),Pseudomonas aeruginosa infection(OR=34.06,95%CI was 13.00-89.25),Escherichia coli infection(OR=24.97,95%CI was 10.55-59.13),Stenotrophomonas maltophilia infection(OR=19.04,95%CI was 3.30-109.96),and Staphylococcus aureus infection(OR=13.48,95%CI was 4.57-39.78)were independent risk factors for resistance(all P<0.01).The ROC curve analysis showed that the predictive model for drug resistance established based on the above independent risk factors had certain predictive value for drug resistance in adult patients with suspected infections after surgery in the ICU.The AUC=0.920,95%CI was 0.890-0.940,P<0.05.Conclusion Higher APACHEⅡscores and the presence of pulmonary,bloodstream,or urinary tract infections were associated with increased mortality in ICU patients with suspected postoperative infection.Patients with bloodstream or urinary tract infections,or infections caused by Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,Escherichia coli,Stenotrophomonas maltophilia,or Staphylococcus aureus,had significantly higher odds of developing antimicrobial resistance.

Objective:To investigate the risk factors of acute respiratory distress syndrome(ARDS)after traumatic hemorrhagic shock.Methods:This was a retrospective cohort study of 314 patients with traumatic hemorrhagic shock at Trauma Medicine Center,Peking University People's Hospital from De-cember 2012 to August 2021,including 152 male patients and 162 female patients,with a median age of 63.00(49.75-82.00)years.The demographic data,past medical history,injury assessment,vital signs,laboratory examination and other indicators of these patients during hospitalization were recorded.These patients were divided into two groups,ARDS group(n=89)and non-ARDS group(n=225)ac-cording to whether there was ARDS within 7 d of admission.Risk factors for ARDS were identified using Logistic regression.The C-statistic expressed as a percentage[area under curve(AUC)of the receiver operating characteristic(ROC)curve]was used to assess the discrimination of the model.Results:The incidence of ARDS after traumatic hemorrhagic shock was 28.34％.Finally,Logistic regression model showed that the independent risk factors of ARDS after traumatic hemorrhagic shock included male,histo-ry of coronary heart disease,high acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score,road traffic accident and elevated troponin Ⅰ.The OR and 95％confidence intervals(CI)were 4.01(95％CI:1.75-9.20),5.22(95％CI:1.29-21.08),1.07(95％CI:1.02-1.57),2.53(95％CI:1.21-5.28),and 1.26(95％CI:1.02-1.57),respectively;the P values were 0.001,0.020,0.009,0.014,and 0.034,respectively.The ROC curve was used to analyze the value of each risk factor in predicting ARDS.It was found that the AUC for predicting ARDS after traumatic hemor-rhagic shock was 0.59(95％CI:0.51-0.68)formale,0.55(95％CI:0.46-0.64)for history of coronary heart disease,0.65(95％CI:0.57-0.73)for APACHE Ⅱ score,0.58(95％CI:0.50-0.67)for road traffic accident,and 0.73(95％CI:0.66-0.80)for elevated troponin Ⅰ,with an overall predictive value of 0.81(95％CI:0.74-0.88).Conclusion:The incidence of ARDS in pa-tients with traumatic hemorrhagic shock is high,and male,history of coronary heart disease,high APACHE Ⅱ score,road traffic accident and elevated troponin Ⅰ are independent risk factors for ARDS after traumatic hemorrhagic shock.Timely monitoring these indicators is conducive to early detection and treatment of ARDS after traumatic hemorrhagic shock.

Objective:To analyze and summarize the medical security situation of the snowmobile,sled,and steel frame snowmobile tracks at the National Sliding Centre,and to provide experience for future event hosting and medical security work for mass ice and snow sports.Methods:Retrospective analysis of injuries and treatment of athletes participating in the International Training Week and World Cup for Ski,Sled,and Steel Frame Ski from October to November 2021(hereinafter referred to as"Inter-national Training Week"),as well as the Ski,Sled,and Steel Frame Ski events at the Beijing Winter Olympics in February 2022(hereinafter referred to as the"Beijing Winter Olympics").We referred to and drew on the"Medical Security Standards for Winter Snow Sports"to develop specific classification standards for analyzing injured areas,types of injuries,and accident locations.Results:A total of 743 athletes participated in the International Training Week and the Beijing Winter Olympics.During the com-petition,there were 58 incidents of overturning,prying,and collision,of which 28(28 athletes)were in-jured,accounting for 48.3％of the total accidents and 3.8％of the total number of athletes.Among them,there were 9 males(32.1％)and 19 females(67.9％),with an average age of(26.3±4.7)years.Among the 28 injured athletes,20 cases(71.4％)received on-site treatment for Class Ⅰ injuries,while 8 cases(28.6％)had more severe injuries,including Class Ⅱ injuries(7 cases)and Class Ⅲ injuries(1 case),which were referred to designated hospitals for further treatment.Among the 28 injured athletes,3 cases(10.7％)experienced multiple injuries,including 2 cases of 2 injuries and 1 case of 3 injuries.The most common injuries were in the ankle and toes(10/32,31.3％).Out of 28 injured athletes,one(3.6％)experienced two types of injuries simultaneously,with joint and/or ligament injuries being the most common(11/29,37.9％).The most accident prone point on the track was the ninth curve(18/58,31.0％).Conclusion:Through the analysis and summary of medical security work,it can provide better experience and reference for the future development of snowmobile,sled,and steel frame snowmobile sports in China,making the National Snowy and Ski Center truly a sustainable Olympic heritage.

Objective:To investigate the use of discriminant analysis to predict the risk of nosocomial mortality in patients with traumatic hemorrhagic shock.Methods:The clinical data of 238 patients with traumatic hemorrhagic shock admitted to Peking University People's Hospital from Sep 2013 to Aug 2020 were retrospectively analyzed. Patients were divided into survival group (214 cases) and death group (24 cases). Stepwise discriminant analysis was used to establish a discriminant model.Results:The difference of history of stroke (9.8% vs. 25.0%), main site of bleeding (extremities)(58.9% vs. 29.2%), APACHEⅡ score (16.4±5.1 vs. 23.2±6.1), blood lactic acid [2.1(1.1-3.5) mmol/L vs. 4.9(2.0-13.4) mmol/L] and surgery (92.5% vs. 58.3%) between the two groups was all statistically significant (all P<0.05). Finally, There are five indicators that entered the discriminant model: history of stroke, main site of bleeding (extremities), blood lactic acid, APACHE Ⅱ score and surgery. The area under the ROC curve for predicting the risk of mortality in patients with traumatic hemorrhagic shock was 0.857, 95% CI 0.754-0.959. Conclusions:The established discriminant model has a high accuracy in predicting the risk of in-hospital mortality in patients with traumatic hemorrhagic shock.

Objective:To establish a rat model of volume-controlled hemorrhage and observe the pathophysiological changes that ensued.Methods:Sprague Dawley (SD) rats were subjected to femoral arterial cannulation and hemorrhage for 40% or 50% of total volume. The hemodynamics data and arterial blood gas were collected, and survival after hemorrhage was monitored for 24 hours ( n=8/group). Then lung, liver, intestine and kidney were collected for HE staining after 40% hemorrhage at 4, 8 and 12 hours ( n=6/group). Results:Mean arterial pressure of 40% and 50% blood loss group decreased significantly from (90±5)mmHg and (93±4)mmHg to (40±4)mmHg and (34±4)mmHg ( P<0.05). Heart rate of 40% and 50% blood loss group increased significantly from (330±35) bpm and (336±32) bpm to (478±36) bpm and (490±21) bpm ( P<0.05). Hemoglobin and pH decreased significantly following hemorrhage, while lactate increased. The survival rate of 50% blood loss group was just 12.5% and 40% blood loss group was 100% ( P<0.05). Compared with sham group, the most significant injury was observed in lung and small intestine after 4 hours, in liver after 8 hours and in kidney after 12 hours following hemorrhage. Conclusion:This study established a stable and repeatable volume-controlled hemorrhagic shock model in rat.

Objectives:To analyze the effect of cytokine-like protein 1 (CYTL1) on the pro-inflammatory functions of neutrophils in septic mice.Methods:C57BL/6 mice were randomly (random number)divided into the sepsis group and control group, with 6-12 mice in each group. A septic mouse model was established by the procedure of cecal ligation and puncture (CLP). Neutrophils were isolated from peripheral venous blood 8 h after the procedures according to the density gradient centrifugation method, and the neutrophils were treated with CYTL1 recombinant protein. The Boyden chemotaxis assays were used to detect the activity of CYTL1. fMLF and interleukin-8 were used as positive controls. Phagocytosis was determined by confocal microscopy or on a FACSVerse. Reactive oxygen species generation in neutrophils were monitored with the commercial CellROX Green fluorescent probe.Results:Compared with the control group, CYTL1 showed strong chemotactic activity on neutrophils of septic mice [(10.0 ± 2) vs (66.3 ± 4), t=-21.6, P <0.0001]. CYTL1 has stronger chemotactic activity than IL-8 [(66.3 ± 4.0) vs (21.7 ± 6.5), t = 10.1, P = 0.001]. But the chemotactic activity of fMLF and CYTL1 changed little on neutrophils of septic mice [(66.3 ± 4.0) vs (86.0 ± 13.5), t=-2.4, P = 0.073]. CYTL1 could augment the uptake of E.coli by neutrophils compared with the sepsis group [(7.35 ± 1.66) vs (2.84 ± 0.62), t = 4.4, P = 0.012]. The number of E.coli particles swallowed intracellular by a single cell significantly increased upon the stimulation of CYTL1. CYTL1 could also enhance the intracellular reactive oxygen species production of neutrophils of septic mice [(84340.1 ± 5353.5) vs (351018.7 ± 72291.7), t = 6.4, P = 0.003]. Conclusions:CYTL1 can prompt the pro-inflammatory functions of neutrophils in septic mice. In the early phase of bacterial infection, this protein may play an important role in regulating the inflammation.

The National Health Commission recently has released a notice about further promoting the trauma rescue and treatment in China, which includes four main contents as follows: ( 1 ) to strengthen the establishment of regional trauma rescue and treatment system based on trauma center;(2) to lift the specialized medical service ability related to trauma rescue and treatment; ( 3 ) to further develop the radiant and stimulating role of National Trauma Medical Centre and National Regional Trauma Medical Center;(4) to enhance the trauma-related professional training and public health education. In this article, we interpret the third aspect regarding medical quality control and maintenance of trauma treatment, providing reference for better understanding the specific requirements of the document.