ObjectiveTo investigate the independent predictive factors for 90-day mortality in patients with acute-on-chronic liver failure （ACLF）， to establish a risk predictive model， and to assess its predictive efficacy in comparison with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ. MethodsA retrospective analysis was performed for the clinical data of 394 patients with ACLF who were admitted to The Affiliated Hospital of Inner Mongolia Medical University and Hohhot Second Hospital from July 2018 to July 2024， and general information and laboratory markers on admission were collected from all patients. The independent-samples t test or the Mann-Whitney U test was used for comparison of quantitative data between two groups， and the chi-square test or the adjusted chi-square test was used for comparison of qualitative data between two groups. The LASSO regression analysis was used to identify related variables， and the multivariate logistic regression analysis was used to establish a predictive model and generate a nomogram. The receiver operating characteristic （ROC） curve， the area under the ROC curve （AUC）， calibration curve， and clinical decision curve were used to assess the performance of the model. ResultsA total of 394 patients with ACLF were included in this study， with 136 patients in the training set， 58 in the internal validation set， and 200 in the external validation set. The cohort had a mean age of 52.9±11.7 years， among whom male patients accounted for 72.84% （287/394）， the patients with HBV infection accounted for 22.33% （88/394）， the patients with alcohol-related causes accounted for 45.94% （181/394）， and the patients with other causes （including drug-induced and autoimmune diseases） accounted for 31.73% （125/394）. The overall 90-day mortality rate was 27.41% （108/394）. The multivariate logistic regression analysis showed that diabetes （odds ratio ［OR］= 5.831， 95% confidence interval ［CI］： 1.587 — 21.424， P=0.008）， cystatin C （Cys-C） （OR=2.984， 95%CI： 1.501 — 5.933， P=0.002）， and spontaneous peritonitis （SBP） （OR=5.692， 95%CI： 2.150 — 15.071， P<0.001） were independent risk factors， and a nomogram was generated based on these factors. This model had an AUC of 0.836 in the training set， 0.881 in the internal validation set， and 0.878 in the external validation set， showing a good discriminatory ability. The calibration curve showed a good degree of fitting， with a relatively high net clinical benefit. The subgroup analysis based on etiology showed that the model had an AUC of 0.850 in the patients with HBV infection， 0.858 in the patients with alcohol-induced ACLF， and 0.908 in the patients with other etiologies， indicating that the model had a good discriminatory ability across the populations with different etiologies. Compared with traditional scores， the model （AUC=0.836） had a significantly better predictive value than MELD （AUC=0.619， Z=3.197， P=0.001）， MELD-Na （AUC=0.651， Z=2.998， P=0.003）， MELD 3.0 （AUC=0.601， Z=3.682， P<0.001）， and COSSH-ACLF Ⅱ （AUC=0.719， Z=2.396， P=0.017） alone. ConclusionDiabetes， SBP， and Cys-C are independent risk factors for 90-day mortality in patients with ACLF. Compared with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ scores， this model has a higher predictive value for 90-day prognosis in patients with ACLF and is suitable for patients with ACLF caused by various etiologies.

Objective To establish a fingerprint spectrum for Qiangshen Oral Liquid;To predict its quality markers combined with network pharmacology.Methods HPLC-ELSD method was used to establish fingerprint spectrum of Qiangshen Oral Liquid,and common peaks were identified.Its targets and related pathways were predicted through network pharmacology.A component-target-pathway network was constructed,and molecular docking verification was performed to analyze the quality markers of Qiangshen Oral Liquid.Results The HPLC fingerprint spectrum of Qiangshen Oral Liquid was established.20 common peaks were identified and belonged to all prescription drug tastes.13 chromatographic peaks were located using reference standards.The similarity evaluation showed that the similarity of 19 batches of Qiangshen Oral Liquid ranged from 0 to 0.995.Network pharmacology identified 45 key targets related to 13 components,and KEGG enrichment analysis obtained 151 pathways.A component-target-pathway network was constructed,predicted that calycosin-7-O-glucoside,ginsenoside Rg1,ginsenoside Re,ginsenoside Rf,ginsenoside Rb1,astragaloside Ⅳ,ginsenoside Rd,ginsenoside Rb2,astragaloside Ⅱ,astragaloside Ⅰ,schisandrin A and panaxatriol were quality markers for Qiangshen Oral Liquid.Conclusion The fingerprint spectrum of Qiangshen Oral Liquid was established,and quality markers were predicted preliminarily,providing a reference for its standard establishment and quality evaluation.

Objective:To gain a understanding of the occurrence of cognitive impairment among residents in drinking water-borne endemic fluorosis (drinking water-borne fluorosis) areas, and to study its influencing factors.Methods:In March 2023, a cluster sampling method was used to select local residents aged 18 and above from the drinking water-borne fluorosis areas in Jishan County, Shanxi Province as survey subjects. General demographic data were collected through face-to-face surveys, and a random urine sample was collected once to determine urinary fluoride level. Cognitive function was assessed using the mini-mental state examination (MMSE), and the survey subjects were divided into a cognitive impairment group ( < 27 points) and a control group (27 - 30 points) based on the MMSE scores. A multiple logistic regression model and a decision tree model based on chi-squared automatic interaction detector were constructed to analyze the factors affecting cognitive impairment, and the model fitting effect was evaluated using receiver operating characteristic (ROC) curve.Results:A total of 3 301 subjects were included in the survey, including 2 081 females and 1 220 males. There were 1 515 subjects < 60 years old and 1 786 subjects ≥60 years old, with urinary fluoride level [ M ( Q1, Q3)] of 2.92 (1.78, 4.54) mg/L. There were 1 939 cases in the cognitive impairment group and 1 362 cases in the control group, with a detection rate of 58.74% (1 939/3 301) for cognitive impairment; and the differences in gender, age, education level, marital status, annual household income, alcohol consumption, smoking distribution, and urinary fluoride level between the two groups were statistically significant ( P < 0.05). The results of multiple logistic regression analysis showed that female, ≥60 years, and urinary fluoride > 4.54 mg/L were risk factors for cognitive impairment [ OR (95% CI): 1.25 (1.01, 1.54), 2.66 (2.26, 3.14), 1.32 (1.06, 1.65), P < 0.05]. Education level of primary school or above, annual household income≥12 000 yuan, and mild alcohol consumption were protective factors for cognitive impairment [ OR (95% CI): 0.15 (0.09, 0.25), 0.58 (0.48, 0.68), 0.67 (0.51, 0.87), P < 0.05]. The analysis results of the decision tree model showed that age had the greatest impact on the occurrence of cognitive impairment, followed by annual household income, education level, and urinary fluoride. The areas under the ROC curves of the multiple logistic regression and decision tree model were 0.72 and 0.70 ( P < 0.001), respectively, indicating good model fitting performance. Conclusion:The detection rate of cognitive impairment in residents of drinking water-borne fluorosis areas is relatively high, and age, annual household income, education level, and urinary fluoride are all influencing factors for occurrence of cognitive impairment.

Objective:To study the impact of fluoride exposure through drinking water on the risk of hypertension among residents in Jishan County, Shanxi Province.Methods:From March to April 2023, a cluster sampling method was used to select permanent residents aged ≥18 years and residing for ≥10 years in 12 villages in drinking water-borne endemic fluorosis areas of Jishan County, Shanxi Province as the survey subjects. A questionnaire survey, physical examination, and morning urinary fluoride level testing were conducted. The least absolute shrinkage and selection operator (Lasso) regression were used to analyze the key influencing factors of hypertension. Restricted cubic spline was used to evaluate the linear relationship between urinary fluoride and hypertension. Logistic regression was used to analyze the impact of urinary fluoride on hypertension.Results:Finally, 2 453 survey subjects were included, aged (62 ± 10) years, including 1 565 patients (63.80%) with hypertension. There were significant differences in the distribution of age, gender, education level, annual household income, body mass index (BMI), and the level and distribution of urinary fluoride between hypertension group and normal blood pressure group ( P < 0.05). The Lasso regression results showed that age, education level, BMI, and urinary fluoride were the key influencing factors of hypertension, with coefficients of 1.04, - 0.12, 0.24 and 0.01, respectively. The results of the restricted cubic spline showed that there was a linear relationship between urinary fluoride and hypertension after adjusting for age, education level, and BMI ( Poverall = 0.018, Pnonlinear = 0.482). The logistic regression results showed that after adjusting for age, education level, and BMI, urinary fluoride > 4.68 mg/L was a risk factor for hypertension ( OR = 1.42, 95% CI: 1.10 - 1.84, P = 0.007). Conclusion:High urinary fluoride is a risk factor for hypertension in drinking water-borne endemic fluorosis areas of Jishan County, Shanxi Province.

Objective:To investigate the current status of knowledge, attitude, and practice (KAP) of intensive care unit (ICU) medical staff for post-intensive care syndrome (PICS) and explore its influencing factors.Methods:The cross-sectional investigation study with stratified sampling was conducted. From June to September 2024, ICU medical staff from general hospitals in 5 regions (Chongqing, Beijing, Shaanxi, Jiangsu, and Gansu) were selected as the research subjects. The KAP of PICS questionnaire was distributed in the form of an electronic questionnaire. Observation indicators: (1) results of the questionnaire survey; (2) general information of ICU medical staff; (3) KAP scores of PICS and the correlation among various dimensions; (4) analysis of influencing factors for KAP of PICS. Comparison of measurement data with normal distribution between groups was conducted using the independent samples t test. One-way analysis of variance (ANOVA) was applied for com-parison among multiple groups, and post-hoc LSD test was used for pairwise comparison. Comparison of count data between groups was conducted using the chi-square test. Pearson correlation analysis was adopted for correlation analysis. Multiple linear regression analysis was used for univariate and multivariate analyses. Results:(1) Results of questionnaire survey. A total of 410 questionnaires were distributed and retrieved, among which 408 were valid, with an effective rate of 99.512%(408/410). (2) General information of ICU medical staff. Among the 408 ICU medical staff, there were 79 males and 329 females. Eight cases were under 25 years old, 248 cases were 25-35 years old, 132 cases were 36-40 years old, and 20 cases were over 40 years old. In terms of professional title, there were 10 junior nurses, 130 junior nurse practitioners, 228 intermediate nurse practitioners, and 40 senior nurse practitioners. About the educational background, 34 cases had a junior college degree, 347 cases had a bachelor's degree, and 27 cases had a master's degree or above. Regarding the hospital level, 25 nurses worked in secondary hospitals and 383 cases in tertiary hospitals. In terms of ICU type, 181 cases were from specialized ICU and 227 cases from general ICU. About working experience in ICU, 41 nurses had less than 5 years, 207 cases had 5-10 years, and 160 cases had more than 10 years. (3) KAP scores of PICS and the correlation among various dimensions. The total KAP score of PICS among the 408 ICU medical staff was 88.7±14.2, with 40.2±9.2 for the knowledge dimension, 22.0±5.6 for the attitude dimension, and 26.5±6.3 for the practice dimension. Pearson correlation analysis showed that the knowledge dimension of PICS among ICU medical staff was significantly positively correlated with both the attitude dimension and the practice dimension ( r=0.15, 0.69, P<0.05); the attitude dimension was positively correlated with the practice dimension ( r=0.23, P<0.05).(4) Analysis of influencing factors for KAP of PICS. Results of multivariate analysis showed that age (25-35 years old, 36-40 years old, over 40 years old), educational background and hospital level were independent influencing factors for the KAP of PICS among ICU medical staff ( t=2.23, 1.97, 2.84, 0.15, 2.04, P<0.05). Conclusions:The KAP of PICS among ICU medical staff is relatively good, while their practical ability still needs to be improved. Age, educational background, and hospital level are independent influencing factors for the KAP of PICS among ICU medical staff.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective To establish a fingerprint spectrum for Qiangshen Oral Liquid;To predict its quality markers combined with network pharmacology.Methods HPLC-ELSD method was used to establish fingerprint spectrum of Qiangshen Oral Liquid,and common peaks were identified.Its targets and related pathways were predicted through network pharmacology.A component-target-pathway network was constructed,and molecular docking verification was performed to analyze the quality markers of Qiangshen Oral Liquid.Results The HPLC fingerprint spectrum of Qiangshen Oral Liquid was established.20 common peaks were identified and belonged to all prescription drug tastes.13 chromatographic peaks were located using reference standards.The similarity evaluation showed that the similarity of 19 batches of Qiangshen Oral Liquid ranged from 0 to 0.995.Network pharmacology identified 45 key targets related to 13 components,and KEGG enrichment analysis obtained 151 pathways.A component-target-pathway network was constructed,predicted that calycosin-7-O-glucoside,ginsenoside Rg1,ginsenoside Re,ginsenoside Rf,ginsenoside Rb1,astragaloside Ⅳ,ginsenoside Rd,ginsenoside Rb2,astragaloside Ⅱ,astragaloside Ⅰ,schisandrin A and panaxatriol were quality markers for Qiangshen Oral Liquid.Conclusion The fingerprint spectrum of Qiangshen Oral Liquid was established,and quality markers were predicted preliminarily,providing a reference for its standard establishment and quality evaluation.

Objective:To investigate the current status of fertility concerns among early-stage endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) patients with fertility preservation, and analyze its influencing factors.Methods:Convenience sampling was used to select early-stage EC and AEH patients with fertility preservation at Peking University People's Hospital from January to December 2021 as study subjects. The study subjects were surveyed using the General Information Questionnaire, Chinese version of the Reproductive Concerns after Cancer Scale (RCAC), and Social Support Rating Scale (SSRS). Pearson correlation was employed to examine the relationship between fertility concerns and social support in early-stage EC and AEH patients with fertility preservation. Single-factor analysis and multiple linear regression analysis were used to examine the factors influencing fertility concerns in early-stage EC and AEH patients with fertility preservation.Results:A total of 170 questionnaires were distributed, and 167 valid questionnaires were collected, with a valid response rate of 98.24% (167/170). The RCAC and SSRS scores of 167 early-stage EC and AEH patients with fertility preservation were (56.58±10.58) and (34.22±8.21), respectively. Educational level, disease type and staging, marital status, and social support were statistically significant factors influencing fertility concerns among early-stage EC and AEH patients undergoing fertility preservation ( P<0.05), explaining 32.80% of the total variance. Conclusions:Early-stage EC and AEH patients with fertility preservation exhibit high levels of fertility concerns. Clinical practice should develop individualized psychological intervention programs for patients with high education level, unmarried status, high pathological grading, and lack of social support to improve their physical and mental health.

Objective To prepare a stable rat model of chronic liver failure to provide a tool for basic research.Methods Sixty-six SPF SD rats were divided into a normal group(n=18)and a modeling group(n=48).Rats in the modeling group received an intraperitoneal injection of 50％CCl4 olive oil solution(1.5 mL/kg,twice a week).Multidimensional assessment was performed at 8,16,and 24 weeks,respectively,including ultrasonic examination of liver morphology,hardness,portal vein diameter,and ascites,and collection of serum,plasma,and liver tissue to detect liver function,coagulation function,and blood ammonia levels.Liver tissue injury and fibrosis were observed by hematoxylin-eosin(HE)and Masson staining.Cognitive function was assessed using the water maze test.Survival were recorded simultaneously.Results Rats in the model group showed decreased activity and appetite,yellow urine,and increased abdominal circumference compared with the normal group.Ultrasound showed enhanced liver parenchyma echo in the model group that thickened with time,secondary ascites formation,portal vein dilation,and portal hypertension.Water maze and blood ammonia tests confirmed cognitive decline(memory and orientation loss)and hepatic encephalopathy in the model group.Gross observation showed that the liver in the model group was atrophied and appeared rough and uneven.HE staining showed hepatocyte swelling,steatosis,and necrosis,and Masson staining confirmed fibrosis progression with pseudolobule formation.The liver function indexes AST,ALT,TBIL and blood ammonia continued to increase,and coagulation dysfunction(prolonged PT and increased INR)gradually increased with the modeling process.Conclusions Intraperitoneal injection of 50％CCl4 olive oil solution(1.5 mL/kg,every week)for 24 weeks can stably simulate persistent chronic liver injury in rats and lead to the typical pathological changes and complications of chronic liver failure,based on the decompensation stage of cirrhosis.This model replicates the pathological evolution of human hepatitis from liver fibrosis → liver cirrhosis compensation → decompensation → chronic liver failure,providing a reliable modeling reference for the study of the mechanism of chronic liver failure.