Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

Objective: To investigate the association of sleep and circadian rhythm disruption indicators (including chronotype, sleep duration, and social jetlag) with co-occurring depressive and anxiety symptoms among primary and secondary school students, so as to provide a reference for promoting their mental health. Methods: In October 2023, a total of 15 944 primary and secondary school students were recruited from Nanjing, using a stratified cluster random sampling method. The Morning and Evening Questionnaire-5, Center for Epidemiological Studies Depression, and Generalized Anxiety Disorder-7 were used for the survey. Chi-square test was employed for intergroup comparisons, and Logistic regression model was applied to analyze the independent and joint effects of sleep related factors on comorbid symptoms of depressive and anxiety among primary and middle school students. Results: The prevalence of co-occurring depressive and anxiety symptoms among primary and secondary school students in Nanjing was 16.9%. After adjusting for covariates, Logistic regression analysis revealed significant independent associations between evening chronotype ( OR=6.55, 95%CI =5.59-7.68), insufficient sleep duration ( OR=3.05, 95%CI =2.60-3.59), and social jetlag ≥2 h ( OR= 2.09 , 95%CI =1.85-2.37) with comorbid symptoms of depressive and anxiety among students (all P <0.05). Concurrent of evening chronotype and insufficient sleep ( OR=7.54, 95%CI =3.55-16.01), as well as evening chronotype and social jetlag ≥2 h ( OR=4.18, 95%CI =3.01-5.81), were associated with an increased risk of co-occurring depressive and anxiety symptoms (both P < 0.05 ). In the female and high school student subgroups, the combination of evening chronotype and insufficient sleep or social jetlag ≥2 h showed stronger joint effects on co-occurring depressive and anxiety symptoms [ OR (95% CI )=8.46(3.25-22.04) and 15.90(3.66-69.08); 7.87(4.90-12.65) and 4.85(3.10-7.59), respectively; all P <0.05]. Conclusions Evening chronotype, insufficient sleep, and social jetlag≥2 h may serve as risk factors for comorbid symptoms of depressive and anxiety in school aged populations. Paying attention to the coexistence of multiple sleep related risk factors may help mitigate the occurrence of emotional disorders in this demographic.

Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

Obesity is a very common public health problem.It is a chronic metabolic disease of multi-factorial origin with limited treatment options.Weight loss surgery is considered to be the most effective treatment option for obesity,which can reduce the body weight and improve metabolism.About 60％of obese patients have abnormal changes in blood lipid levels,and dyslipidemia is considered to be an independent risk factor for the development of atherosclerosis-related diseases.Weight loss surgery can significantly improve the serum lipid profile of obese patients and reduce the risk of cardiovascular disease,but its specific mecha-nism is still inconclusive.This paper introduces the possible mechanism of lipid metabolism changes from the aspects of the mass change of visceral tissues,adipokine changes,insulin sensitivity improvement,gastrointes-tinal hormones and intestinal flora,bile acid metabolism pathway,vitamins and trace elements.It is expected to further clarify the lipid-lowering mechanism of weight loss surgery in the future and provide a new way for the treatment of dyslipidemia.

Objective:To summarize the midterm to long-term outcomes and experiences of endovascular treatment (ET) of spontaneous isolated superior mesenteric artery dissection (SISMAD).Methods:The clinical data of 31 SISMAD patients from Jan 2011 to Dec 2019 treated with ET was retrospectively analyzed.Results:Successful ET was achieved in 29 patients with a technical success rate of 93.5%. A total of 36 self-expandable bare stents were planted in 28 patients and plain old balloon angioplastry (POBA) was performed in 1 patient. Abdominal pain disappeared within 24 hours in 89.3% of the patients after stenting. The rate of perioperative complication was 3.2%. There was no SMA dissection rupture bleeding, nor perioperative death occurred. The mean follow-up time was 53.5 (range, 6 to 110) months. There was no dissecting aneurysm formation, no SMA rupture and bleeding, and no stent rupture during the follow-up. The post ET 1-year, 3-year, and 5-year free from reintervention rate were 100%, 100%, and 91.7%, respectively.Conclusions:ET for SISMAD is safe and effective with satisfactory perioperative and midterm to long-term outcomes.

Objective:To examine the factors influencing the false lumen remodeling of abdominal aortic segment in the midterm and longterm after thoracic endovascular aortic repair (TEVAR).Methods:The data of patients with type B aortic dissection diagnosed and underwent TEVAR at the Department of Vascular and Endovascular Surgery, the First Medical Center, People′s Liberation Army General Hospital, from November 2009 to November 2019 were analyzed retrospectively. Patients of acute or subacute long segment dissection with residual tears of abdominal but no thoracic segment and follow-up for more than one year were enrolled. Patients with operation-related complications, and dissection caused by trauma and Marfan syndrome were excluded. A total of 51 patients were enrolled, including 45 males and 6 females, with an age of (49.4±10.6) years (range: 31 to 72 years). The patients included in the analysis were divided into stable and enlarged group. The criteria for inclusion in the enlarged group were any of the following: (1) the maximum growth rate of the abdominal segment false lumen was ≥3 mm/year; (2) the maximum diameter of the abdominal aorta was ≥50 mm; (3) the diameter of the abdominal segment false lumen increased more than 10 mm. χ 2 test, t-test and nonparametric test were used for univariate analysis. The variables with P≤0.1 were included in the Logistic multivariate stepwise regression to analyze the independent correlation factors, and the receiver operating characteristic (ROC) curve was used to calculate the cut-off value of the quantitative data. Results:All patients were divided into stable group ( n=30) and enlarged group ( n=21). The follow-up time of all patients was 42(29) months (range: 12 to 115 months). There were no significant differences in baseline characteristics, endovascular treatment characteristics and postoperative medication between the two groups ( P>0.05). Compared with stable group,the number of residual tears around visceral arteries was more (2(1) vs. 1(1), Z=-2.829, P=0.005) and the number of lumbar arteries originating from false lumen was more (5(6) vs. 3(5), Z=-2.025, P=0.043) early after TEVAR in enlarged group. The number of residual tears around visceral arteries ( OR=3.966, 95% CI: 1.552 to 10.131, P=0.004) was found to be the independent influence factor for the poor remodeling of the abdominal false lumen in multivariate Logistic regression analysis. ROC curve analysis showed that the cut-off value of the number of residual tears around visceral arteries was 2 at least (area under curve: 0.718). Conclusion:The incidence of poor remodeling of the abdominal false lumen after TEVAR was high. The number of residual tears around visceral arteries (≥2) could be independent influence factor to predict the poor remodeling of abdominal false lumen, and the follow-up of such patients should be strengthened in clinic.

Objective:To examine the factors influencing the false lumen remodeling of abdominal aortic segment in the midterm and longterm after thoracic endovascular aortic repair (TEVAR).Methods:The data of patients with type B aortic dissection diagnosed and underwent TEVAR at the Department of Vascular and Endovascular Surgery, the First Medical Center, People′s Liberation Army General Hospital, from November 2009 to November 2019 were analyzed retrospectively. Patients of acute or subacute long segment dissection with residual tears of abdominal but no thoracic segment and follow-up for more than one year were enrolled. Patients with operation-related complications, and dissection caused by trauma and Marfan syndrome were excluded. A total of 51 patients were enrolled, including 45 males and 6 females, with an age of (49.4±10.6) years (range: 31 to 72 years). The patients included in the analysis were divided into stable and enlarged group. The criteria for inclusion in the enlarged group were any of the following: (1) the maximum growth rate of the abdominal segment false lumen was ≥3 mm/year; (2) the maximum diameter of the abdominal aorta was ≥50 mm; (3) the diameter of the abdominal segment false lumen increased more than 10 mm. χ 2 test, t-test and nonparametric test were used for univariate analysis. The variables with P≤0.1 were included in the Logistic multivariate stepwise regression to analyze the independent correlation factors, and the receiver operating characteristic (ROC) curve was used to calculate the cut-off value of the quantitative data. Results:All patients were divided into stable group ( n=30) and enlarged group ( n=21). The follow-up time of all patients was 42(29) months (range: 12 to 115 months). There were no significant differences in baseline characteristics, endovascular treatment characteristics and postoperative medication between the two groups ( P>0.05). Compared with stable group,the number of residual tears around visceral arteries was more (2(1) vs. 1(1), Z=-2.829, P=0.005) and the number of lumbar arteries originating from false lumen was more (5(6) vs. 3(5), Z=-2.025, P=0.043) early after TEVAR in enlarged group. The number of residual tears around visceral arteries ( OR=3.966, 95% CI: 1.552 to 10.131, P=0.004) was found to be the independent influence factor for the poor remodeling of the abdominal false lumen in multivariate Logistic regression analysis. ROC curve analysis showed that the cut-off value of the number of residual tears around visceral arteries was 2 at least (area under curve: 0.718). Conclusion:The incidence of poor remodeling of the abdominal false lumen after TEVAR was high. The number of residual tears around visceral arteries (≥2) could be independent influence factor to predict the poor remodeling of abdominal false lumen, and the follow-up of such patients should be strengthened in clinic.