Objective: To analyze the association between poor sleep characteristics and the coexistence of negative emotions and overweight/obesity among college students, so as to provide a scientific basis for improving their physical and mental health. Methods: From November to December 2023, a convenience sampling method was used to survey 6 600 college students from nine universities in Jiangxi, Hunan, and Hubei provinces. The Depression Anxiety and Stress Scale-21 (DASS-21), Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and physical examinations were employed to assess negative emotions, poor sleep characteristics, and overweight/obesity. Chi square test and Logistic regression were used to analyze the impact of poor sleep characteristics on the coexistence of negative emotions and overweight/obesity. Results: The coexistence rates of different categories of negative emotions (depression, anxiety, stress) and overweight/obesity were 6.1% ( n= 405), 8.0% ( n =529), and 3.3% ( n =217), respectively. Gender, grade level, major, maternal education level, annual family income, physical activity level, only child status, and carbonated beverage consumption were statistically associated with the coexistence rates of different categories of negative emotions and overweight/obesity ( χ 2=4.01-35.18, all P <0.05). Logistic regression analysis showed that after adjusting for gender, grade level, major, only child status, maternal education level, annual family income, physical activity level, and carbonated beverage consumption, poor sleep characteristics were significantly associated with an increased risk of the coexistence of negative emotions and overweight/obesity ( OR =1.41-6.65); moderate and poor sleep quality levels were significantly associated with an increased risk of the coexistence of different categories of negative emotions and overweight/obesity among female students ( OR =1.99-4.71) (all P <0.05). Conclusions Poor sleep characteristics are associated with the coexistence of negative emotions and overweight/obesity among college students. Greater attention should be paid to sleep issues in this population, and sleep education should be actively promoted to reduce the risk of comorbid negative emotions and overweight/obesity.

Objective To develop and validate a prediction model for extended hospitalisation in patients with ischemic stroke.Methods A total of 318 patients with ischemic stroke hospitalised between November 2021 and May 2023 in a Grade ⅢA hospital in Changzhou were selected as study objects with a convenience sampling method.The modelling group consisted 212 patients and the validation group included 106 patients.The patients in the modelling group were divided into a group of extended hospital stay and a group of normal hospital stay.Binary logistic regression analysis was conducted to develop the prediction model,and data from the 106 patients in the validation group were then incorporated into the developed prediction model.The prediction performance and goodness-of-fit of the model were accessed using the area under the curve(AUC)of the receiver operation characteristic(ROC)curve and the Hosmer-Lemeshow test.Results Multivariate logistic analysis showed that comorbid diabetes,number of complications during hospitalisation,a Braden score less than 18,and a white blood cell count greater than 3.5×109/L or more than 9.5×109/L were the risk factors of extended hospitalisation in patients with cerebral ischemic stroke.Based on the factors,a prediction model was developed with following formula:P=1/[1+exp(-Z)].Hosmer-Lemeshow test for the prediction model yielded χ 2=7.430,P=0.191.AUC of the prediction model was 0.818(95％CI:0.754-0.883,P<0.001)with Jordon index of 0.51 and the optimal cut-off value of 0.268,sensitivity of 78.9％and specificity of 72.3％The results of the validation of independent data model showed a sensitivity of 75.0％,specificity of 74.4％,and accuracy of 74.5％.Conclusion Comorbid diabetes,Braden score at admission,white blood cell count and the number of complications during hospitalisation are the significant factors that affect the length of hospital stay in the patients with ischemic stroke.The prediction model for extended hospitalisation of the patients with ischemic stroke exhibits good predictive value and can provide reference in clinical decision-making.

Objective To develop and validate a prediction model for extended hospitalisation in patients with ischemic stroke.Methods A total of 318 patients with ischemic stroke hospitalised between November 2021 and May 2023 in a Grade ⅢA hospital in Changzhou were selected as study objects with a convenience sampling method.The modelling group consisted 212 patients and the validation group included 106 patients.The patients in the modelling group were divided into a group of extended hospital stay and a group of normal hospital stay.Binary logistic regression analysis was conducted to develop the prediction model,and data from the 106 patients in the validation group were then incorporated into the developed prediction model.The prediction performance and goodness-of-fit of the model were accessed using the area under the curve(AUC)of the receiver operation characteristic(ROC)curve and the Hosmer-Lemeshow test.Results Multivariate logistic analysis showed that comorbid diabetes,number of complications during hospitalisation,a Braden score less than 18,and a white blood cell count greater than 3.5×109/L or more than 9.5×109/L were the risk factors of extended hospitalisation in patients with cerebral ischemic stroke.Based on the factors,a prediction model was developed with following formula:P=1/[1+exp(-Z)].Hosmer-Lemeshow test for the prediction model yielded χ 2=7.430,P=0.191.AUC of the prediction model was 0.818(95％CI:0.754-0.883,P<0.001)with Jordon index of 0.51 and the optimal cut-off value of 0.268,sensitivity of 78.9％and specificity of 72.3％The results of the validation of independent data model showed a sensitivity of 75.0％,specificity of 74.4％,and accuracy of 74.5％.Conclusion Comorbid diabetes,Braden score at admission,white blood cell count and the number of complications during hospitalisation are the significant factors that affect the length of hospital stay in the patients with ischemic stroke.The prediction model for extended hospitalisation of the patients with ischemic stroke exhibits good predictive value and can provide reference in clinical decision-making.

Objective To investigate the influence of preoperative serum heat shock protein 90α (HSP90α) level on the survival time of patients with hepatocellular carcinoma treated by transarterial chemoembolization (TACE). Methods A retrospective analysis was performed for the clinical data of 97 patients with hepatocellular carcinoma who received TACE alone in Department of Hepatobiliary Surgery, The Affiliated Hospital of Southwest Medical University, from January 1, 2019 to June 1, 2020. With the median of serum HSP90α level as the cut-off value, the patients were divided into high-level group with 48 patients (HSP90α > 135 ng/L) and low-level group with 49 patients (HSP90α ≤135 ng/L). The chi-square test was used for comparison of categorical data between groups. The Kaplan-Meier method was used to calculate the median survival time, and the log-rank test was used for comparison between groups. The log-rank univariate analysis and multivariate Cox regression analysis were used to explore the influencing factors for the survival time of patients after surgery. Results There were significant differences between the high-level group and the low-level group in Child-Pugh class ( χ 2 =19.356, P <0.01), tumor necrosis ( χ 2 =9.964, P =0.002), BCLC staging ( χ 2 =22.356, P <0.01), and ECOG score ( χ 2 =6.644, P <0.05). The high-level group had a significantly shorter median survival time than the low-level group ( χ 2 =15.551, P <0.01). HSP90α level (hazard ratio [ HR ]=1.690, P <0.05) and BCLC staging ( HR =2.373, P <0.05) were independent influencing factors for the survival time of patients with hepatocellular carcinoma after TACE. Conclusion Preoperative serum HSP90α level is an independent influencing factor for the survival time of patients with hepatocellular carcinoma after TACE, and it is expected to become one of the potential indicators for evaluating the prognosis of patients with hepatocellular carcinoma treated by TACE.

Objective To investigate the relationship between bacteria biofilm and bacterial culture in patients with chronic rhinosinusitis (CRS). Methods Ninety patients with CRS were enrolled in the study. Five patients with deviation of nasal septum and 10 healthy subjects served as controls. Mucosa of uncinate process or near the ostium of the maxillary sinus was obtained during endoscopic sinus surgery. All specimens were processed for bacterial culture and scanned by electron microscopy. Pearson test was performed to analyze the relationship between the presence of bacterial biofilm and the results of bacteria culture. Results The scanning electron microscopy showed bacterial biofilms in 64 (71.1%) out of 90patients with CRS, while the positive rate of bacteria culture in the study group was 66.7% (60/90). No bacterial biofilm and bacterium was detected in the control group and 26 culture-negative individuals in study group. Pearson correlation analysis showed a statistically association between bacterial biofilm and bacterial culture in CRS ( r = 0. 901, P = 0. 000). Conclusion Positive results of bacteria culture are highly correlated with the presence of bacterial biofilm in CRS patients.