OBJECTIVE To analyze the influencing factors for achieving target plasma drug concentration （trough） （abbreviated as “PDC”） of vancomycin in patients from high-altitude regions and establish a predictive model for PDC using single- center data， providing references for rational clinical drug use. METHODS Inpatients with vancomycin （1 g， q12 h） administered intravenously in our hospital from January 2021 to June 2024 were retrospectively included. Demographic data， liver and kidney function and hematological indexes were collected. Spearman correlation analysis was used to evaluate the correlation between vancomycin PDC and each detection index. Univariate analysis was used to evaluate the differences of each index in patients with different PDC， and the effects of different gender， body mass index， age and underlying diseases （hypertension/diabetes） on vancomycin PDC. Based on the results of correlation analysis and univariate analysis， multiple linear stepwise regression analysis was used to obtain the independent predictors of vancomycin PDC and construct the prediction model. RESULTS A total of 141 patients were included， with an overall attainment rate of 46.81% for the target PDC of vancomycin. Correlation analysis showed that the vancomycin PDC was positively correlated with age， blood urea nitrogen， uric acid （UA）， serum creatinine （CRE） and β2- microglobulin （β2-MG）， and negatively correlated with height， weight， creatinine clearance rate （CCR）， glomerular filtration rate （GFR）， alanine transaminase （ALT）， hemoglobin （HGB）， white blood cell count and neutrophils （P＜0.05）. There were significant differences in age， CRE and other 14 indexes among different PDC groups （P＜0.05 or P＜0.01）. Age and underlying diseases had significant effects on vancomycin PDC （P＜0.05 or P＜0.01）. CCR， direct bilirubin （DBil）， β2-MG， UA， HGB and height （standardized coefficients were －0.371， 0.367， 0.169， 0.232， －0.140， －0.132； P＜0.05） were independent predictors of vancomycin PDC. The F value of the regression equation was 34.858 （P＜0.05）， the R2 was 0.610， and the adjusted R2 was 0.592. CONCLUSIONS The vancomycin PDC of patients in high-altitude regions is affected by multiple factors such as renal function， liver function and hematological indexes. CCR， HGB and height could be used to predict vancomycin PDC negatively， while DBil， β2-MG and UA could be used to predict vancomycin PDC positively. The variables of the established prediction model could explain 59.2% of the variation of vancomycin PDC.

Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

ObjectiveTo investigate the impact of anticentromere antibody （ACA） on the clinical features and prognosis of patients with primary biliary cholangitis （PBC） by comparing clinical classification， ursodeoxycholic acid （UDCA） response， GLOBE score， and UK-PBC score between ACA-positive PBC patients and ACA-negative PBC patients. MethodsA total of 749 patients who were admitted to Beijing Ditan Hospital， Capital Medical University， from August 2013 to December 2022 and were diagnosed with PBC were enrolled and divided into ACA-positive group with 147 patients and ACA-negative group with 602 patients. According to their conditions on admission， the two groups were compared in terms of the distribution of clinical types， i.e.， chronic progression-type PBC， portal hypertension-type PBC， and standard jaundice/liver failure-type PBC. There were 261 patients with complete data after 1-year follow-up， among whom there were 53 patients with positive ACA and 208 with negative ACA. A statistical analysis was performed， and propensity score matching was performed based on sex and age at a ratio of 1∶2. The two groups were compared in terms of 1-year UDCA response rate， GLOBE score， and UK-PBC score before and after matching. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. ResultsCompared with the ACA-negative group， the ACA-positive group had a significantly higher age （61.28±10.35 years vs 56.74±12.17 years， t=4.164， P<0.001）， a significantly higher proportion of female patients （93.9% vs 77.6%， χ²=20.221， P<0.001）， a significantly higher proportion of patients with portal hypertension （48.3% vs 27.6%， χ²=23.289， P<0.001）， and a significantly lower proportion of patients with jaundice/liver failure （24.5% vs 38.5%， χ²=10.205， P<0.001）. After 1-year follow-up， for the 261 PBC patients with complete data， there was no significant difference in UDCA response rate before propensity score matching between the ACA-positive group and the ACA-negative group （41.5% vs 41.8%， P>0.05）， and there was a significant difference in the proportion of patients with a GLOBE score of >0.3 between the ACA-positive group and the ACA-negative group （92.5% vs 80.3%， χ²=3.935， P=0.047）. There were 53 patients in the ACA-positive group and 106 patients in the ACA-negative group after propensity score matching， and there were no significant differences between the two groups in UDCA response rate， GLOBE score， and UK-PBC score （all P>0.05）. ConclusionACA-positive patients tend to have an older age， with a higher proportion of female patients or patients with portal hypertension， while there is a relatively low proportion of patients with jaundice/liver failure. Positive ACA has no significant impact on UDCA response rate， GLOBE score， and UK-PBC score.

OBJECTIVE To investigate the current status of monitoring indicators related to the"Perioperative In-fection Control"in medical institutions above the secondary level in Guizhou Province,and to delve into the imple-mentation of key measures for infection prevention and control during the perioperative period for patients under-going surgical operations.METHODS Based on the"Implementation Plan for the'Perioperative Infection Control'Initiative in Guizhou Province",a"Case Investigation Form on Key Measures for Infection Prevention and Control During the Perioperative Period for Patients Undergoing Surgical Operation"was developed.A total of 138 medi-cal institutions participated in the case investigation,and a total of 2 128 cases were investigated.RESULTS The overall monitoring indicators for the"Perioperative Infection Control"initiative in the 138 medical institutions a-bove the secondary level in Guizhou Province were at a relatively low level.The skin cleansing compliance rate was 80.32％,the hair removal compliance rate was 16.43％,the prophylactic antibacterial drug administration rate within 0.5-1 hour before surgery was 55.94％and the antibacterial drug discontinuation rate within 24 hours after prophylactic medication for type Ⅰ incision surgeries was 56.48％.The hair removal compliance rate was higher in tertiary medical institutions(19.21％)than in secondary medical institutions(14.34％)(P=0.039).The distri-bution of the four monitoring indicators varied in clinical departments and surgery types,with statistically signifi-cant differences(P＜0.05).The preferred method for surgical site skin cleansing in medical institutions across the province was local wiping,primarily with clean water(57.21％).The primary method for hair removal was razors(68.82％),and hair removal on the day of surgery was most common(61.75％).CONCLUSIONS Conduc-ting a survey on the current status of"Perioperative Infection Control"initiative monitoring indicators in medi-cal institutions in Guizhou Province helps to understand the implementation of key measures for perioperative in-fection prevention and control and set intervention targets,thus providing references for establishing a dynam-ic monitoring indicator change mechanism.

Objective:To explore the effect of self-compassion-based writing on prosocial behavior in college students with different self-construals.Methods:A total of 182 college students were recruited,and the Self-Con-structional Scales were used to determine the self-construal types(independent or interdependent).Participants were then assigned to either a self-compassion-based writing group(n=91)or a non-self-compassion daily writing group(n=91)and completed writing tasks according to the respective instructions.Prosocial behavior was evaluated with the Prosocial Tendencies Measure(PTM),situational judgment tests,and donation amounts.Results:The evaluation results from the PTM showed that prosocial behavior was significantly higher in individuals with interdependent self-construal compared to those with independent self-construal(P＜0.001),the main effect of the group type was not statistically significant(P＞0.05).The evaluation results from situational judgment tests showed that prosocial behavior was significantly higher in individuals with interdependent self-construal compared to those with independ-ent self-construal(P＜0.001),the self-compassion-based writing group demonstrated significantly more prosocial behavior than the non-self-compassion daily writing group(P＜0.05).The evaluation results from donation a-mounts showed that the main effect of self-construal type was not statistically significant(P＞0.05),the self-com-passion-based writing group demonstrated significantly more prosocial behavior than the non-self-compassion daily writing group(P＜0.05).Conclusion:Compared to daily writing,self-compassion-based writing could effectively increase prosocial behavior in college students,regardless of their self-construal type.

Objective:To explore the effectiveness of the"full-chain"integrated medical and elderly care service model in addressing key issues in medical-nursing services such as weak medical support capacity and insufficient provision of community-and home-based medical-nursing services.Methods:The development pathway for the"full-chain"integrated medical-elderly care service standardization system,encompassing core components such as operational mechanisms,smart platforms,policy documents,and quality control systems was systematically outlined.Effectiveness based on dimensions including service coverage,quality improvement,talent development,and social benefits was evaluated.With standardization as the core driver,the'1234567'management model was innovatively implemented.Results:The model leveraged the downward allocation of high-quality resources from tertiary general hospitals to strengthen subdistrict community health service centers.By collaborating with subdistrict elderly-care service centers,it established"subdistrict medical-elderly care and wellness service centers".These centers enhanced the capabilities of"community-embedded elderly-care complexes",including community daytime care centers,established two-way referral channels between medical and elderly care services,aligned with healthcare demands to provide elderly individuals with reliable medical support.It reduced the burden on families and society,stimulated market vitality,boosted domestic demand,promoted the development of integrated medical-elderly care and wellness initiatives,thereby advancing the silver economy.With provincial government endorsement,the model had been applied to 203 communities across 37 counties by the end of 2024.Conclusion:The established"full-chain"integrated medical-elderly care service model facilitates regional high-quality development in integrated care by consolidating healthcare group resources and seamlessly connecting the service chain across hospitals,nursing homes,community institutions,and home-based settings,thereby creating a practical paradigm for comprehensive elderly care service delivery.

Objective:To explore the effectiveness of the"full-chain"integrated medical and elderly care service model in addressing key issues in medical-nursing services such as weak medical support capacity and insufficient provision of community-and home-based medical-nursing services.Methods:The development pathway for the"full-chain"integrated medical-elderly care service standardization system,encompassing core components such as operational mechanisms,smart platforms,policy documents,and quality control systems was systematically outlined.Effectiveness based on dimensions including service coverage,quality improvement,talent development,and social benefits was evaluated.With standardization as the core driver,the'1234567'management model was innovatively implemented.Results:The model leveraged the downward allocation of high-quality resources from tertiary general hospitals to strengthen subdistrict community health service centers.By collaborating with subdistrict elderly-care service centers,it established"subdistrict medical-elderly care and wellness service centers".These centers enhanced the capabilities of"community-embedded elderly-care complexes",including community daytime care centers,established two-way referral channels between medical and elderly care services,aligned with healthcare demands to provide elderly individuals with reliable medical support.It reduced the burden on families and society,stimulated market vitality,boosted domestic demand,promoted the development of integrated medical-elderly care and wellness initiatives,thereby advancing the silver economy.With provincial government endorsement,the model had been applied to 203 communities across 37 counties by the end of 2024.Conclusion:The established"full-chain"integrated medical-elderly care service model facilitates regional high-quality development in integrated care by consolidating healthcare group resources and seamlessly connecting the service chain across hospitals,nursing homes,community institutions,and home-based settings,thereby creating a practical paradigm for comprehensive elderly care service delivery.

Objective:To explore the effect of self-compassion-based writing on prosocial behavior in college students with different self-construals.Methods:A total of 182 college students were recruited,and the Self-Con-structional Scales were used to determine the self-construal types(independent or interdependent).Participants were then assigned to either a self-compassion-based writing group(n=91)or a non-self-compassion daily writing group(n=91)and completed writing tasks according to the respective instructions.Prosocial behavior was evaluated with the Prosocial Tendencies Measure(PTM),situational judgment tests,and donation amounts.Results:The evaluation results from the PTM showed that prosocial behavior was significantly higher in individuals with interdependent self-construal compared to those with independent self-construal(P＜0.001),the main effect of the group type was not statistically significant(P＞0.05).The evaluation results from situational judgment tests showed that prosocial behavior was significantly higher in individuals with interdependent self-construal compared to those with independ-ent self-construal(P＜0.001),the self-compassion-based writing group demonstrated significantly more prosocial behavior than the non-self-compassion daily writing group(P＜0.05).The evaluation results from donation a-mounts showed that the main effect of self-construal type was not statistically significant(P＞0.05),the self-com-passion-based writing group demonstrated significantly more prosocial behavior than the non-self-compassion daily writing group(P＜0.05).Conclusion:Compared to daily writing,self-compassion-based writing could effectively increase prosocial behavior in college students,regardless of their self-construal type.

Objective:To construct and validate a depression risk prediction model for middle-aged and elderly patients with diabetes.Methods:Data were extracted from the fifth wave (2020) of the China Health and Retirement Longitudinal Study (CHARLS). A total of 900 diabetic patients were identified, and after excluding those with missing data or invalid questionnaires, 769 patients were included in the analysis. Patients were randomly divided into a training set and a validation set in a 7∶3 ratio. Univariate analysis and logistic regression analysis were performed to screen the optimal predictors of depression in diabetic patients, and a nomogram model was developed. The predictive performance of the model was assessed by the area under the receiver operating characteristic curve ( AUC). Model calibration and accuracy were evaluated using bootstrap resampling, calibration plots, and the Hosmer-Lemeshow test. The clinical utility was further assessed by decision curve analysis (DCA) and clinical impact curves (CIC) . Results:Among the 769 patients, 366 (47.59%) had depression. Logistic regression analysis showed that place of residence, pain, difficulty in toileting, difficulty in bathing, sleep duration, physical exercise, life satisfaction, and children's satisfaction were independent predictors of depression in diabetic patients. A nomogram was constructed based on these variables, yielding an AUC of 0.775. At the optimal cutoff value of 0.557, the model demonstrated a sensitivity of 59.1% and a specificity of 84.8%, indicating good discriminative ability. The Hosmer-Lemeshow test showed (χ 2=15.821, P=0.105), suggesting good agreement between predicted and observed outcomes. In the validation set, the AUC was 0.778, with Hosmer-Lemeshow (χ 2=8.557, P=0.575). DCA and CIC indicated favorable clinical applicability of the model. Conclusions:The depression risk prediction model constructed in this study demonstrated good predictive performance. It can assist clinicians in early identification of high-risk individuals with diabetes and provide a theoretical basis for targeted interventions.

Objective:To construct and validate a depression risk prediction model for middle-aged and elderly patients with diabetes.Methods:Data were extracted from the fifth wave (2020) of the China Health and Retirement Longitudinal Study (CHARLS). A total of 900 diabetic patients were identified, and after excluding those with missing data or invalid questionnaires, 769 patients were included in the analysis. Patients were randomly divided into a training set and a validation set in a 7∶3 ratio. Univariate analysis and logistic regression analysis were performed to screen the optimal predictors of depression in diabetic patients, and a nomogram model was developed. The predictive performance of the model was assessed by the area under the receiver operating characteristic curve ( AUC). Model calibration and accuracy were evaluated using bootstrap resampling, calibration plots, and the Hosmer-Lemeshow test. The clinical utility was further assessed by decision curve analysis (DCA) and clinical impact curves (CIC) . Results:Among the 769 patients, 366 (47.59%) had depression. Logistic regression analysis showed that place of residence, pain, difficulty in toileting, difficulty in bathing, sleep duration, physical exercise, life satisfaction, and children's satisfaction were independent predictors of depression in diabetic patients. A nomogram was constructed based on these variables, yielding an AUC of 0.775. At the optimal cutoff value of 0.557, the model demonstrated a sensitivity of 59.1% and a specificity of 84.8%, indicating good discriminative ability. The Hosmer-Lemeshow test showed (χ 2=15.821, P=0.105), suggesting good agreement between predicted and observed outcomes. In the validation set, the AUC was 0.778, with Hosmer-Lemeshow (χ 2=8.557, P=0.575). DCA and CIC indicated favorable clinical applicability of the model. Conclusions:The depression risk prediction model constructed in this study demonstrated good predictive performance. It can assist clinicians in early identification of high-risk individuals with diabetes and provide a theoretical basis for targeted interventions.