Objective:Cardiac arrest (CA) represents a significant public health challenge, posing a substantial threat to individual health and survival. To enhance the survival rates of patients experiencing out-of-hospital cardiac arrest (OHCA), Baoan District in Shenzhen City has undertaken exploratory initiatives and practical interventions, yielding promising preliminary outcomes.Methods:1.Innovate emergency medical services by developing a "four-circle integration" system that connects to the hospital. This system encompasses the social emergency medical system, the out-of-hospital emergency medical system, the in-hospital emergency medical service system, and the intensive care treatment system. 2.Develop a comprehensive model for the construction of a social emergency medical training system, characterized by party leadership, government oversight, departmental coordination, professional guidance, technological support, and community involvement, termed the "Baonan Model." Additionally, establish evaluation criteria to assess the effectiveness of the social emergency medical training system in Baonan District; 3. Develop a cardiac arrest registration system and a social emergency medical training management system for Baonan District; 4. Enhance the proficiency in treatment techniques and the quality of cardiopulmonary resuscitation among emergency medical professionals; 5. Strengthen and advance the development of a "five-minute social rescue network" to address the critical "emergency window period." .Result:In Baonan District, 9.18% of the public is trained in emergency medical skills. The bystander CPR rate for OHCA is 26.11%, AED use is at 4.78%, the 30-day survival rate is 6.31%, and the discharge survival rate is 4.44%.Conclusion:The implementation of the aforementioned measures can substantially enhance the survival rate of patients experiencing OHCA at the time of discharge.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective To investigate the effects of different ventilation strategies on intraocular pressure (IOP) and intracranial pressure in patients undergoing spinal surgery in the prone position under general anesthesia. Methods Seventy-two patients undergoing prone spinal surgery under general anesthesia between November, 2022 and June, 2023 were equally randomized into two groups to receive routine ventilation (with Vt of 8mL/kg, Fr of 12-15/min, and etCO2 maintained at 35-40 mmHg) or small tidal volume hyperventilation (Vt of 6 mL/kg, Fr of18-20/min, and etCO2 maintained at 30-35 mmHg) during the surgery. IOP of both eyes (measured with a handheld tonometer), optic nerve sheath diameter (ONSD;measured at 3 mm behind the eyeball with bedside real-time ultrasound), circulatory and respiratory parameters of the patients were recorded before anesthesia (T0), immediately after anesthesia induction (T1), immediately after prone positioning (T2), at 2 h during operation (T3), immediately after supine positioning after surgery (T4) and 30 min after the operation (T5). Results Compared with those at T1, IOP and ONSD in both groups increased significantly at T3 and T4 (P<0.05). IOP was significantly lower in hyperventilation group than in routine ventilation group at T3 and T4 (P<0.05), and ONSD was significantly lower in hyperventilation group at T4 (P<0.05). IOP was positively correlated with the length of operative time (r=0.779, P<0.001) and inversely with intraoperative etCO2 at T3 (r=-0.248, P<0.001) and T4 (r=-0.251, P<0.001). ONSD was correlated only with operation time (r=0.561, P<0.05) and not with IOP (r=0.178, P>0.05 at T3;r=0.165, P>0.05 at T4). Conclusion Small tidal volume hyperventilation can relieve the increase of IOP and ONSD during prone spinal surgery under general anesthesia.

Objective To investigate the effects of different ventilation strategies on intraocular pressure (IOP) and intracranial pressure in patients undergoing spinal surgery in the prone position under general anesthesia. Methods Seventy-two patients undergoing prone spinal surgery under general anesthesia between November, 2022 and June, 2023 were equally randomized into two groups to receive routine ventilation (with Vt of 8mL/kg, Fr of 12-15/min, and etCO2 maintained at 35-40 mmHg) or small tidal volume hyperventilation (Vt of 6 mL/kg, Fr of18-20/min, and etCO2 maintained at 30-35 mmHg) during the surgery. IOP of both eyes (measured with a handheld tonometer), optic nerve sheath diameter (ONSD;measured at 3 mm behind the eyeball with bedside real-time ultrasound), circulatory and respiratory parameters of the patients were recorded before anesthesia (T0), immediately after anesthesia induction (T1), immediately after prone positioning (T2), at 2 h during operation (T3), immediately after supine positioning after surgery (T4) and 30 min after the operation (T5). Results Compared with those at T1, IOP and ONSD in both groups increased significantly at T3 and T4 (P<0.05). IOP was significantly lower in hyperventilation group than in routine ventilation group at T3 and T4 (P<0.05), and ONSD was significantly lower in hyperventilation group at T4 (P<0.05). IOP was positively correlated with the length of operative time (r=0.779, P<0.001) and inversely with intraoperative etCO2 at T3 (r=-0.248, P<0.001) and T4 (r=-0.251, P<0.001). ONSD was correlated only with operation time (r=0.561, P<0.05) and not with IOP (r=0.178, P>0.05 at T3;r=0.165, P>0.05 at T4). Conclusion Small tidal volume hyperventilation can relieve the increase of IOP and ONSD during prone spinal surgery under general anesthesia.

Objective:To investigate the effects of silicon photomutipliers (SiPM) detector and Bayesian penalized likelihood (BPL) reconstruction algorithm on semiquantitative parameters of 18F-FDG PET/CT and diagnostic efficiency for solitary pulmonary nodules/masses compared with traditional photomultiplier tube (PMT) and ordered subsets expectation maximization (OSEM). Methods:From March 2020 to January 2022, 118 patients (76 males, 42 females, age (63.0±10.1) years) newly diagnosed with solitary pulmonary nodules/masses in First Hospital of Shanxi Medical University were prospectively enrolled and underwent 18F-FDG PET/CT imaging with two different PET/CT scanners successively. The images were divided into PMT+ OSEM, SiPM+ OSEM and SiPM+ BPL groups according to PET detector and reconstruction algorithms. The SUV max, SUV mean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of pulmonary nodules/masses were measured, then signal-to-noise ratio (SNR) and signal-to-background ratio (SBR) were calculated. One-way analysis of variance and Kruskal-Wallis rank sum test were performed to compare differences of above parameters among groups. ROC curve analysis was used to analyze the optimal threshold of SUV max for the differential diagnosis of pulmonary nodules/masses and AUCs were obtained. Results:There were 83 malignant nodules and 35 benign nodules. The image quality of SiPM+ BPL group (4.23±0.64) was better than that of SiPM+ OSEM group (3.57±0.50) or PMT+ OSEM group (3.58±0.51; F=54.85, P<0.001). There were significant differences in SUV max (7.57(3.86, 15.61) vs 4.95(2.22, 10.48)), SUV mean (4.43(2.28, 9.12) vs 2.84(1.21, 5.71)), MTV (3.54(1.57, 7.67) vs 5.09(2.83, 11.79)), SNR (28.12(12.55, 54.38) vs 20.16(8.29, 41.45)) and SBR (4.03(1.83, 7.75) vs 2.32(0.96, 5.03)) between SiPM+ BPL and SiPM+ OSEM groups ( H values: 16.63-37.05, all P<0.001). The optimal threshold values of SUV max in SiPM+ BPL, SiPM+ OSEM and PMT+ OSEM were 3.31, 2.21, 2.05 with AUCs of 0.686, 0.689, 0.615 for nodules < 2 cm, and were 10.29, 6.49, 4.33 with AUCs of 0.775, 0.782, 0.774 for nodules/masses ≥2 cm. Conclusions:Image quality and parameters of pulmonary nodules/masses are mainly affected by the reconstruction algorithms. BPL can improve SUV max, SUV mean, SBR and SNR, but reduce MTV without significant effect on liver parameters. SiPM+ BPL has a higher diagnostic threshold of SUV max than SiPM+ OSEM and PMT+ OSEM.

This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter study was performed by collecting blood cell analysis data of Beijing Chaoyang Hospital and the First Hospital of Hebei Medical University from 2020 to 2021. Machine learning techniques, including support vector machine, decision tree, naïve Bayes, random forest and multi-layer perceptron were explored to establish a prediction model of depression. The results showed that based on the blood cell analysis results of healthy controls and depression group, the accuracy of prediction model reached as high as 0.99, F1 was 0.975. Receiver operating characteristic curve area and average accuracy were 0.985 and 0.967, respectively. Platelet parameters contributed mostly to depression prediction model. While, to random forest differential diagnosis model based on the data from depression and anxiety groups, prediction accuracy reached 0.68 and AUC 0.622. Age, platelet parameters, and average volume of red blood cells contributed the most to the model. In conclusion, the study researched on the prediction model of depression by exploring blood cell analysis parameters, revealing that machine learning models were more objective in the evaluation of mental illness.
Humans ; Depression ; Bayes Theorem ; Machine Learning ; Support Vector Machine ; Blood Cell Count

Objective:To investigate the value of derived neutrophil-to-lymphocyte ratio (dNLR) in predicting the prognosis of extensive-stage small cell lung cancer (ES-SCLC) patients treated with the first-line atezolizumab immunotherapy and chemotherapy.Methods:From the Project Data Sphere platform, the clinical data and laboratory test data of 53 ES-SCLC patients who received the first-line atezolizumab immunotherapy and chemotherapy in the global multicenter phase Ⅱ prospective study NCT03041311 from February 2017 to February 2022 were collected. The Contal-O'Quigley method was used to calculate the optimal cut-off value of baseline dNLR for determining the overall survival (OS) of patients. The dNLR higher than or equal to the optimal cut-off value was defined as high dNLR, and less than the optimal cut-off value was defined as low dNLR. According to optimal cut-off value, the dNLR levels at baseline and after 4 cycles of chemotherapy were determined, and dynamic dNLR grouping was performed (low risk: low dNLR at baseline and after 4 cycles of chemotherapy; intermediate risk: high dNLR at baseline or after 4 cycles of chemotherapy; high risk: high dNLR at baseline and after 4 cycles of chemotherapy). The differences in clinicopathological features between the baseline high dNLR group and low dNLR group were analyzed. Kaplan-Meier method was used to draw the OS and progression-free survival (PFS) curves, and log-rank test was used to compare the differences between the two groups. Univariate Cox proportional hazards model was used to analyze the influencing factors of OS and PFS. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the predictive value of baseline dNLR grouping and dynamic dNLR grouping for 1-year OS rate in ES-SCLC patients receiving the first-line atezolizumab immunotherapy and chemotherapy.Results:Among the 53 patients, 34 (64.20%) were male and 19 (35.80%) were female; 27 (50.90%) were < 65 years old and 26 (49.10%) were ≥65 years old. The optimal cut-off value of baseline dNLR for determining the OS was 1.79. There were 17 cases in low dNLR group and 36 cases in high dNLR group at baseline. The proportion of patients with elevated serum lactate dehydrogenase (LDH) in the baseline high dNLR group was higher than that in the baseline low dNLR group [58.33% (21/36) vs. 17.65% (3/17), χ2 = 7.72, P = 0.005]. The 1-year OS rates of the baseline high and low dNLR groups were 44.0% and 81.9%, and the 1-year PFS rates were 2.5% and 17.6%. The differences in OS and PFS between the two groups were statistically significant (both P < 0.05). There were 38 patients with complete dynamic dNLR data, including 9 cases of low-risk, 19 cases of medium-risk and 10 cases of high-risk, and the 1-year OS rates of the three groups were 90.0%, 67.5% and 33.3%, the difference in OS between the three groups was statistically significant ( P = 0.011). Univariate Cox regression analysis showed that baseline dNLR (low dNLR vs. high dNLR) was the influencing factor for OS of patients ( HR = 0.163, 95% CI 0.057-0.469, P = 0.001) and PFS ( HR = 0.505, 95% CI 0.268-0.952, P = 0.035). Time-dependent ROC curve analysis showed that the area under the curve (AUC) of baseline dNLR grouping and dynamic dNLR grouping for predicting 1-year OS rate of ES-SCLC patients receiving the first-line atezolizumab combined with chemotherapy was 0.674 (95% CI 0.575-0.887) and 0.731 (95% CI 0.529-0.765). Conclusions:Baseline and dynamic dNLR grouping may be effective markers for predicting the prognosis of ES-SCLC patients receiving the first-line atezolizumab immunotherapy and chemotherapy.

This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter study was performed by collecting blood cell analysis data of Beijing Chaoyang Hospital and the First Hospital of Hebei Medical University from 2020 to 2021. Machine learning techniques, including support vector machine, decision tree, naïve Bayes, random forest and multi-layer perceptron were explored to establish a prediction model of depression. The results showed that based on the blood cell analysis results of healthy controls and depression group, the accuracy of prediction model reached as high as 0.99, F1 was 0.975. Receiver operating characteristic curve area and average accuracy were 0.985 and 0.967, respectively. Platelet parameters contributed mostly to depression prediction model. While, to random forest differential diagnosis model based on the data from depression and anxiety groups, prediction accuracy reached 0.68 and AUC 0.622. Age, platelet parameters, and average volume of red blood cells contributed the most to the model. In conclusion, the study researched on the prediction model of depression by exploring blood cell analysis parameters, revealing that machine learning models were more objective in the evaluation of mental illness.
Humans ; Depression ; Bayes Theorem ; Machine Learning ; Support Vector Machine ; Blood Cell Count

【Objective】 To assess three severe acute respiratorysyndrome coronavirus 2 (SARS-CoV-2) enzyme linked immunosorbent assays (ELISA) and one pseudotype lentivirus-based neutralization test (ppNAT) in detecting the convalescent plasma antibody levles from COVID-19. 【Methods】 30 COVID-19 convalescent plasma samples were screened for antibodies against SARS-CoV-2 using three kinds of SARS-CoV-2 ELISA reagents and one ppNAT test in Shenzhen. The controls consisted of plasma samples from 32 healthy blood donors in February 2019. The diagnostic efficacy analysis of various SARS-CoV-2 ELISA reagents was performed using real-time fluorescent Polymerase Chain Reaction (RT-PCR). We also analyzed correlation between different immunological reagents and the age, gender, hospitalization, and severity of illness. 【Results】 The positive yielding rate of ppNAT and three kinds of IgG ELISA was higher than that of IgM ELISA. The positive yielding rates of three kinds of IgG ELISA were 100%(30/30), 93.33%(28/30), and 96.67%(29/30) respectively, while the yielding rates in control group were all 0. The positive yielding rate of three IgM ELISAs were 93.33%(28/30), 70%(21/30)and 46.67% (14/30). All the cases from negative control group were negative for IgG and IgM. Pearson correlation coefficient was calculated; there was a strong correlation between ELISA reagent 2 IgG and ELISA reagent 3 IgG (r=0.765, P<0.01). The correlation between ppNAT, ELISA reagent 3 IgG and the age of recovered patients was 0.422 and 0.385, respectively (P<0.05), while no significant correlation was found between the duration of hospitalization, severity of illness, gender and antibody signal/cutoff (S/CO) (P>0.05). 【Conclusion】 In the convalescent plasma with nucleic acid confirmed covid-19, the yielding rates of different IgM antibodies varied greatly. Antibody levels were influenced by age to some extent.

Objective:To explore the status and obstacle factors of exercise in elderly maintenance hemodialysis (MHD) patients, so as to provide a clinical evidence for exercise guidance and targeted intervention in elderly maintenance hemodialysispatients.Methods:A mixed method of consistent parallel design was adopted. A total of 180 elderly MHD patients in two ClassⅢ hospitals of Kunshan in December 2021 were enrolled using convenience sampling method and investigated by questionnaire. The statas of exercise and exercise self-efficacy were researched. Objective sampling method was used to interview 17 elderly MHD patients with semi-structured interviews. The obstacle factors of exercise were investigated.Results:A total of 180 valid questionnaires were collected in the quantitative study. The highest metabolicequivalent of leisure time physical activity was 1 188 MET-min/w, the lowest was 0 MET-min/w, and the median was 396 MET-min/w. Pearson correlation analysis showed that there was a positive correlation between exercise self-efficacy and physical activity in elderly MHD patients ( P<0.05). Qualitative study extracted 3 themes and 9 subthemes, including lack of exercise knowledge, low self-efficacy, family and social environment resource limitation. Conclusions:Elderly MHD patients lack ideal exercise state. In clinical practice, medical staff should popularize exercise knowledge, improve patients' exercise self-efficacy, carry out family support education, increase social support, and select suitable exercise methods and develop individualized exercise programs according to patients' disease characteristics, so as to improve their exercise status.