OBJECTIVE To construct a classification prediction model for vancomycin blood concentration， and to optimize its precision dosing strategies. METHODS Patient records meeting inclusion criteria were extracted from the Medical Information Mart for Intensive Care database. Following data cleaning and preprocessing， a final cohort of 9 902 patient was analyzed. Feature selection was performed through correlation analysis and the Boruta feature selection algorithm. Vancomycin blood concentrations were discretized into three categories based on clinical therapeutic windows： low （＜10 μg/mL）， intermediate （10-20 μg/mL）， and high （≥20 μg/mL）. Six machine learning algorithms were employed to construct classification models： tabular prior-data fitted network （TabPFN）， logistic regression （LR）， random forest （RF）， extreme gradient boosting （XGBoost）， support vector machine （SVM）， K-nearest neighbors （KNN）. Model performance was evaluated using 10-fold cross-validation （10-CV）， with primary metrics including： accuracy， balanced accuracy， precision macro， recall macro， macro F1， area under the receiver operating characteristic curve （OvR-AUC）. Shapley Additive Explanations （SHAP） was adopted to analyze the direction and magnitude of the impact that different features had on the model’s predictive outcomes. RESULTS The results showed that the RF and TabPFN models performed the best （with accuracy of 0.741 4 and 0.737 7， and OvR-AUC of 0.907 0 and 0.895 8， respectively）. XGBoost model exhibited moderate performance， while LR， SVM， and KNN models demonstrated relatively poor performance. Confusion matrix heatmap analysis revealed that both RF and TabPFN achieved higher accuracy in predicting high- concentration cases but exhibited slightly lower performance in the low and medium concentration categories. Bootstrap with 10-CV revealed that the RF model demonstrated stable performance across various evaluation metrics （accuracy： 0.741 4； balanced accuracy： 0.740 3； precision macro： 0.732 1； recall macro： 0.736 0； macro F1： 0.736 0； OvR-AUC： 0.907 0）， indicating good classification performance and generalization ability. SHAP analysis revealed that creatinine， urea nitrogen， daily cumulative dose and administration frequency of vancomycin， which were key predictors， had a significant impact on the prediction results. CONCLUSIONS RF and TabPFN models demonstrate certain advantages in the classification prediction of vancomycin trough blood concentrations； however， their performance in the low to moderate concentration categories still requires improvement.

Objective: To investigate the status of salt-restriction spoons use among residents in Zhejiang Province, so as to provide evidence for optimizing salt-reduction intervention strategies and preventing chronic disease. Methods: Residents aged 18-69 from five counties (cities/districts) in Zhejiang Province were selected using a multi-stage stratified random sampling method. Demographic characteristics, dietary habits, and salt-restriction spoons use were collected using questionnaires. The rate of salt-restriction spoons use and correct rate of salt-restriction spoons use were analyzed. Factors affecting salt-restriction spoons use among residents were analyzed by multivariable logistic regression model. Results: Totally 7 601 questionnaires were allocated, and 7 509 valid questionnaires were recovered, with an effective recovery rate of 98.79%. The respondents included 3 744 males (49.86%) and 3 765 females (50.14%). The mean age was (44.81±14.03) years. The rate of salt-restriction spoons use was 11.97%, the correct rate of salt-restriction spoon use was 52.73%. Multivariable logistic regression analysis showed that rural (OR=0.851, 95%CI: 0.731-0.991), education level of primary school and below (illiterate or semi-literate, OR=0.269, 95%CI: 0.172-0.420; primary school, OR=0.595, 95%CI: 0.436-0.811), and excessive dietary salt intake (OR=0.718, 95%CI: 0.559-0.922) were inhibiting factors for salt-restriction spoons use among residents; physical exercise (OR=1.581, 95%CI: 1.362-1.836) and received health education on a low-salt diet (OR=2.082, 95%CI: 1.790-2.421) were promoting factors for salt-restriction spoons use among residents. Conclusions The rate of salt-restriction spoons use among residents in Zhejiang Province was relatively low, primarily influenced by region, educational level, physical activity, dietary salt intake, and health education on a low-salt diet. It is recommended that propose a multi-component intervention strategy centered on skill enhancement and health education, delivered through progressive staged implementation, to promote sustained adoption of salt-restriction spoons among residents.

Objective: To investigate the current status and influencing factors for cognitive frailty among the elderly in community, so as to provide the evidence for early identification and prevention of cognitive frailty among the elderly. Methods: Residents aged 60 years and above with local household registration from 11 counties (cities, districts) in Zhejiang Province from 2021 to 2023 were selected as study participants using a multistage random sampling method. Demographic information, lifestyle, and health status were collected through questionnaire surveys. Depressive symptoms were assessed using the Patient Health Questionnaire. Cognitive frailty was evaluated using the FRAIL Scale and the Mini-Mental State Examination. Factors affecting cognitive frailty among the elderly in community were identified using a multivariable logistic regression model. Results: A total of 16 613 individuals were surveyed, including 7 465 males (44.93%) and 9 148 females (55.07%). The average age was (70.97±7.29) years. A total of 784 individuals were detected with depressive symptoms, with a detection rate of 4.72%. A total of 724 individuals were detected with cognitive frailty, with a detection rate of 4.36%. Multivariable logistic regression analysis showed that females (OR=1.419, 95%CI: 1.179-1.708), aged ≥70 years (70-<80 years old, OR=1.869, 95%CI: 1.490-2.345; ≥80 years old, OR=5.017, 95%CI: 3.935-6.398), without a spouse (OR=1.495, 95%CI: 1.234-1.810), sedentary (OR=2.420, 95%CI: 1.829-3.202), chronic diseases (1 type, OR=1.456, 95%CI: 1.175-1.804; ≥2 types, OR=1.639, 95%CI: 1.314-2.045), and depressive symptoms (OR=4.191, 95%CI: 3.361-5.225) were associated with a higher risk of cognitive frailty among the elderly in community. Conversely, a lower risk of cognitive frailty was seen among the elderly in community who had primary school or above (primary school, OR=0.512, 95%CI: 0.389-0.676; junior high school or above, OR=0.464, 95%CI: 0.354-0.608), engaged in physical exercise (OR=0.396, 95%CI: 0.291-0.539), and were reported average or good self-rated health status (average, OR=0.641, 95%CI: 0.475-0.866; good, OR=0.150, 95%CI: 0.109-0.208). Conclusions The detection rate of cognitive frailty among the elderly in community is relatively low and is influenced by demographic factors such as gender, age, education level, as well as lifestyle like sedentary and physical exercise, and health status. It is recommended to reduce the risk of cognitive frailty among the elderly through multidimensional interventions, including health education, promotion of healthy lifestyles, and enhanced mental health support.

Objective:To explore the current status of work-family behavioral role conflict among Operating Room nurses from the resource perspective and analyze its influencing factors using Logistic regression and decision tree models.Methods:A convenience sampling method was used to survey 1 231 Operating Room nurses from 20 hospitals in Henan Province from September to November 2023, utilizing a general information questionnaire, Survey of Nurse Perceived Organizational Support (SNPOS), Family APGAR Index (APGAR), and Work-Family Behavioral Role Conflict Scale (WFBRCS). Univariate analysis, Logistic regression, and decision tree model analyses were applied to identify factors affecting work-family behavioral role conflict among the Operating Room nurses.Results:A total of 1 231 questionnaires were retrieved, and 1 182 were validly questionnaires, resulting in a retrieving rate of 96.02%. Both models identified gender, having children, hospital type, organizational support perception, and family care as influencing factors of work-family behavioral role conflict among the Operating Room nurses ( P<0.05). The areas under the curve ( AUC) for the receiver operating characteristic curves of the Logistic regression and decision tree models were 0.782 and 0.735, respectively, with sensitivities of 76.1% and 65.9%, and specificities of 67.2% and 74.1%, respectively. Conclusions:The work-family behavioral role conflict among Operating Room nurses is at a moderate level and influenced by multiple factors. Both Logistic regression and decision tree models have predictive value for classification, with the Logistic regression model showing higher sensitivity and the decision tree model showing higher specificity. The complementary use of both models has more clinical significance.

Objective:To systematically review the risk prediction models for cognitive impairment in stroke patients, aiming to provide references for clinical healthcare professionals in selecting or constructing high-quality risk assessment tools.Methods:A computerized search was conducted in PubMed, Embase, Web of Science, OVID, Cochrane Library, SinoMed, CNKI, Wanfang Database, and VIP to identify studies related to risk prediction models for cognitive impairment in stroke patients. The search was limited to articles published up to August 1, 2023. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability of the included studies using PROBAST.Results:A total of 26 articles were included. The applicability of the studies was generally good, but all studies had some degree of bias risk, mainly arising from unreasonable study designs, inappropriate time intervals between predictor assessment and outcome determination, insufficient sample sizes, unreasonable handling of continuous variables, omission of missing data, lack of reporting of calibration, and overfitting of the models. Meta-analysis results showed that age ( OR=0.05, 95% CI: 0.033-0.057), education level ( OR=-0.13, 95% CI: -0.171 - -0.082), history of diabetes ( OR=2.32, 95% CI: 1.867-2.881), history of hypertension ( OR=0.67, 95% CI: 0.420-0.918), and NIHSS score ( OR=0.40, 95% CI: 0.331-0.469) were factors for cognitive impairment in stroke patients. Conclusions:While various risk prediction models for cognitive impairment in stroke patients exist, they suffer from methodological flaws and high bias risks, with some commonalities and controversies in predictors. Future research should adhere to the principles of transparent reporting of individual prognosis or diagnosis of multivariate prediction models, develop localized prediction models with low bias risk and good applicability, and conduct internal and external validations to demonstrate their applicability and feasibility in clinical practice.

Objective To explore the effect of aerobic exercise on renal function abnormalities and mitochondrial oxidative stress of obese rats.Methods Ninety 5-week male Sprague-Dawley rats were randomly divided into a normal diet group(CON,n=10)and a high-fat diet group(n=80).The latter group was on high-fat diet for 8 weeks to induce obesity with renal function abnormality.After success-ful modelling,40 rats were chosen and randomly divided into a high-fat diet control group(HFD)and three groups of high-fat diet+aerobic exercise with different intensities(40%VO2max,60%VO2max,and 80%VO2max),each of 10.All exercise groups underwent daily 60-min aerobic exercise on treadmill,5 days per week for 4 weeks.After the intervention,their body weight,body length,perirenal and epi-didymal fat weights were measured,and morphometric indices including fat-body ratio and Lee's in-dex were calculated.Moreover,such biochemical indicators of renal function as serum creatinine(SCr),serum cystatin C and urinary microalbumin(mALB)were tested.Meanwhile,the pathological changes of the kidney were observed using hematoxylin eosin(HE)staining and Periodic acid-Schiff(PAS)staining,while the ultrastructural changes of the kidney and mitochondria were observed using the transmission electron microscopy.Moreover,the levels of superoxide dismutase(SOD),malondialde-hyde(MDA),and mitochondrial membrane potential in mitochondria were evaluated using ELISA kits.Results After 4 weeks of intervention,the average SCr,serum cystatin C,and mALB levels in the HFD group increased significantly compared with the CON group(P<0.05).Moreover,the average SCr levels of all exercise groups were significantly lower than the HFD group(P<0.05),with the average serum cystatin C and mALB levels of the 60%VO2max and 80%VO2max groups significantly lower than the HFD group(P<0.05).Meanwhile,the renal tubular epithelial cells in the HFD group showed mod-erate degeneration and increased glomerulosclerosis index(GSI)(P<0.05)and the degree of glomerular hypertrophy in each exercise group was significantly lower than the HFD group,with the renal tubules of the 60%VO2max group showing a clearer contour and decreased GSI(P<0.05).What's more,com-pared with the CON group,the number of swollen mitochondria in the HFD group increased,but the mitochondria damage of the 60%VO2max group relieved significantly compared with the HFD group.The renal mitochondrial MDA levels in the CON group increased significantly compared with the HFD group(P<0.05),and those of the exercise groups were significantly lower than the HFD group(P<0.05),with the most significant decrease in the 40%VO2max group(P<0.05).Moreover,the average renal mito-chondrial SOD and membrane potential levels in the HFD group decreased significantly compared with the CON group(P<0.05),while those in the 40%and the 60%VO2max groups were significantly higher than the HFD group(P<0.05).Conclusion Moderate to low intensity aerobic exercise can relieve renal dysfunction of obese rats by lowering the level of oxidative stress in renal mitochondria,mainly down-regulating such renal function biochemical indicators as SCr,serum cystatin C,and mALB,as well as alleviating the degree of renal tissue damage.

Objective To standardize nursing management on postoperative patients with a left ventricular assist-ant device(LVAD).Methods The first draft of the Consensus was formed on the basis of literature review.2 rounds of expert consultations and a round of online meeting discussion were held for adjustments and modifications the draft of the Consensus.Results The recovery rate of the inquiry questionnaire was 93.75%.The authority coefficients of the 2 rounds of inquiry experts were 0.927 and 0.920.The concentration degree of expert opinions for each indicator was greater than 3.5 score,and the coefficient of variation was less than 0.25.The Kendall harmony coefficients for 2 rounds of correspondence were 0.402 and 0.407(P<0.01).The final Consensus formed through expert consultations and meetings includes 7 themes:hemodynamic monitoring,LVAD function monitoring,coagulation function monitoring,percutaneous cable and wound care,exercise rehabilitation care,health education and guidance,and pre-discharge assessment.Conclusion The Consensus is scientific,rigorous,and authoritative.The Consensus covers all aspects of postoperative care for patients with LVAD,and it will benefit to clinical practice.

Objective:To identify the risk factors, and develop and validate a risk prediction model for abnormal bone mass in end-stage renal disease (ESRD) patients.Methods:It was a retrospective cross-sectional study. The clinical and laboratory data of ESRD patients who were hospitalized in the Department of Nephrology, Zhongda Hospital Affiliated to Southeast University from January 2022 to May 2023 were collected retrospectively. The patients were randomly divided into training and validation cohorts at a ratio of 7∶3. They were further divided into normal and abnormal bone mass groups according to the T value measured by dual-energy X-ray absorptiometry (DXA). Then, backward stepwise regression and least absolute shrinkage and selection operator (LASSO) were respectively used to develop the risk prediction model for abnormal bone mass in ESRD patients. Akaike information criterion (AIC), bayesian information criterion (BIC), and accuracy were used to evaluate the performance of these two models, after which the preferable model was selected. Moreover, the receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow test, and decision curve analyses (DCA) were applied to evaluate the diagnostic performance of the preferable model. Finally, a dynamic nomogram for individual assessment was constructed based on the preferable model.Results:A total of 254 ESRD patients were enrolled, including 160 (63.0%) males, 161 (63.4%) hemodialysis patients, and 202 (79.5%) patients with abnormal bone mass. There was no significant difference in the prevalence of abnormal bone mass between training group ( n=178) and validation group ( n=76) (79.2% vs. 80.3%, χ2=0.036, P=0.849). The final variables and variable parameters included in the LASSO and stepwise regression models were the same, which were five variables: age, body mass index, hypertension, diabetes, and osteocalcin. Both models also had the same AIC, BIC, and accuracy in the training group, which were 113.45, 132.54, and 0.837, respectively. Therefore, the LASSO model and the stepwise regression model performed consistently in this study and could be considered as the same model, hereafter referred to as the Model. The Model's area under the ROC curve in the training and validation groups was 0.923 (95% CI 0.884-0.963) and 0.809 (95% CI 0.675-0.943), respectively. The optimal cutoff for the training group was 0.858, with a sensitivity of 0.801, a specificity of 0.973 and an accuracy of 0.837; when this cutoff value was taken, the validation group's sensitivity was 0.689, specificity was 0.800, and accuracy was 0.711. The Model demonstrated excellent performance in the calibration curve, Hosmer-Lemeshow test ( P>0.05), and DCA. Finally, based on the five predictors of the Model, a dynamic nomogram was created for clinicians to enter baseline clinical parameters for early identification of high-risk patients with abnormal bone mass. Conclusions:A dynamic nomogram for abnormal bone mass in ESRD patients is constructed with good predictive performance based on the prediction model, which can be used as a practical approach for the personalized early screening and auxiliary diagnosis of the potential risk factors and assist physicians in making a personalized diagnosis for patients.

Objective:To determine the safety and efficacy of sandwich surgery in minimally invasive orthopedic surgery.Methods:A retrospective analysis was performed on 79 pectus carinatum patients undergoing minimally invasive orthopedic surgery admitted to the Department of Thoracic Surgery, Beijing Children's Hospital from July 2016 to July 2018, including 53 cases in the Abramson surgery group and 26 cases in the sandwich surgery group.Results:79 cases successfully completed the operation, the difference in complication rate between the two groups was not statistically significant. All cases were followed up to two years after bar removal, and no recurrence during the follow-up period. The excellent rate of orthopedic effect in sandwich surgery group was higher than that in Abramson surgery group.Conclusion:Sandwich surgery is safe, feasible and can achieve satisfactory postoperative results. It can be used as a surgical option for the treatment of pectus carinatum with depression or depression after orthosis.

Purpose: To understand the recurrence risk perception of stroke patients and develop a chain mediation model of recurrence risk perception and health behavior. Methods: A cross-sectional study and convenience sampling were used. Stroke survivors were recruited from the neurology departments of three tertiary hospitals. Their recurrence risk perception, behavioral decision-making, social support, self-efficacy, recurrence worry, and health behavior were measured by relevant tools. Data was analyzed through one-way analysis and regression analysis, and the AMOS 21.0 software was used to explore the mediating relationships between variables. Results: Of the 419 participants, 74.7% were aware of stroke recurrence risk. However, only 28.2% could accurately estimate their own recurrence risk. Recurrence risk perception was significantly correlated with behavioral decision-making, social support, self-efficacy, and health behavior (r = .19 ∼ .50, p < .05). Social support and recurrence risk perception could affect health behavior indirectly through self-efficacy, behavioral decision-making, and worry. Behavioral decision-making acted as a main mediator between recurrence risk perception and health behavior, while the path coefficient was .47 and .37, respectively. The chain mediation effect between recurrence risk perception and health behavior was established with a total effect value of .19 (p < .01). Conclusion Most stroke survivors could be aware of recurrence risk but failed to accurately estimate their individual risk. In the mediation model of recurrence risk perception and health behavior, social support seemed to be an important external factor, while self-efficacy, behavioral decision-making, and worry seemed to act as key internal factors.