OBJECTIVE To construct a preoperative medication reconciliation model assisted by a localized large language model （LLM） for gastric cancer and evaluate its clinical efficacy. METHODS A total of 249 gastric cancer patients with a history of continuous medication before admission in the Gastric Surgery Department of Jiangsu Cancer Hospital were retrospectively enrolled. Patients were divided into training set （154 cases） and validation set （95 cases） based on the order of time. Based on guidelines， drug package inserts， and other evidence， a standardized medication reconcili ation process and a structured knowledge base were constructed. DeepSeek-V3 LLM was deployed privately in the hospital， combined with retrieval-augmented generation technology， to achieve automated integration of medication information， risk screening， and generation of personalized recommendations. The quality of LLM-generated recommendations was evaluated using automatic metrics （BERT Score and ROUGE-1， 2， L） and manual scoring [seven-dimensional index （7DI） ] . Spearman correlation analysis was performed to explore the correlation between automatic scores and manual scores. Cronbach’s α coefficient was used to test the internal consistency of manual scoring results. The time consumed by manual and LLM-assisted medication reconciliation was compared across tasks of different difficulty levels （simple， moderate， and high）. RESULTS A structured knowledge base covering 8 major drug categories was finally established， covering common and high-risk preoperative medication scenarios and providing structured retrieval support for the LLM. For automatic evaluation， the precision， recall， and F1-score of BERT Score were 0.783±0.033， 0.811±0.038， and 0.796±0.028， respectively. The F1-scores of ROUGE-1， ROUGE-2 and ROUGE-L were 0.566±0.067， 0.338±0.076 and 0.468±0.082， respectively. The 7DI scores from three manual raters ranged from 32.06 to 33.45. The F1-score of automatic scoring was significantly positively correlated with the 7DI score of manual scoring （maximum coefficient of determination＝0.611， P ＜0.001）， and the internal consistency of manual scoring was good （Cronbach’s α ＝ 0.876）. In terms of efficiency， LLM-assisted medication reconciliation reduced time consumption by more than 90% compared with manual reconciliation in the simple， moderate， and high-difficulty groups （ P ＜0.001）. CONCLUSIONS The medication reconciliation model constructed based on a localized LLM and structured knowledge base shows high accuracy， consistency， and clinical applicability in complex preoperative medication scenarios for gastric cancer. It can improve the efficiency of medication reconciliation and reduce potential medication risks.

Objective To investigate the predictive value of edema metabolic and hematoma dynamics changes on motor and cog-nitive recovery outcomes in patients with intracerebral hemorrhage(ICH).Methods The CT data of ICH patients were collected to evaluate hematoma volume changes from admission to day 3.On day 3,multivoxel magnetic resonance spectroscopy(MRS)was per-formed with region of interest located in the edema region and contralateral normal tissue.Motor and cognitive function recovery was assessed using the simplified F-M scale and the Montreal cognitive assessment(MoCA)on day 3 and at the 3-month follow-up,respec-tively.Overall clinical outcomes were assessed using the Glasgow outcome scale(GOS),and all patients were divided into good and poor outcome groups.Clinical data and metabolic differences in the edema region between the two groups were compared,respec-tively.Logistic regression analysis and receiver operating characteristic(ROC)curves were used to identify and evaluate independent prognostic factors.Subgroup analysis were performed via stratification of hematoma location.Results The logistic regression analy-sis indicated that intraventricular extension,hematoma changes,and the ratio of N-acetyl aspartate(NAA)around the hematoma to contralateral normal brain parenchyma NAA(rNAA)were inde-pendent prognostic factors for poor outcomes(P＜0.05).The area under the curve(AUC)for each factor and the combined model were 0.69,0.73,0.79,and 0.82,respectively.In patients with ICH in the basal ganglia region,△F-M was negatively correlated with hematoma changes and positively correlated with rNAA value(P＜0.001).In patients with ICH in the thalamic and lobar regions,△MoCA was not significantly correlated with hematoma changes(P＞0.05),but was positively correlated with rNAA value(P＜0.001).Conclusion The rNAA holds predictive value for motor and cognitive recovery outcomes following standard treatment.

Objective:To evaluate the feasibility and safety of open ventilation masks in patients with proliferative diabetic retinopathy (PDR) undergoing vitrectomy under local anesthesia.Methods:A randomized clinical trial was conducted.Eighty PDR patients (80 eyes) undergoing vitrectomy with local anesthesia were enrolled at Xuzhou Municipal Hospital from May to July 2024.Patients were randomly divided into an experimental group and a control group using a random number table method, with 40 cases (40 eyes) in each group.The experimental group received oxygen through an ophthalmic surgical open ventilation mask during the operation, while the control group used a traditional nasal cannula.The respiratory rate, heart rate, systolic blood pressure, diastolic blood pressure, and oxygen saturation before and after oxygen inhalation during the operation were compared between the two groups.Patient comfort level, airway patency, anxiety status, satisfaction level, operation time, surgical success rate, and incidence of intraoperative complications were also compared.This study adhered to the Declaration of Helsinki and the study protocol was appreed by the Ethics Committee of Xuzhou Municipal Hospital (No.2024-KY-065).Results:After oxygen inhalation during the operation, improvements in respiratory rate, heart rate, and oxygen saturation were greater in the experimental group than in the control group, with statistically significant differences ( t=4.671, 7.894, 1.588; all P<0.05).The Borg, and Hamilton Anxiety Scale scores were lower in the experimental group than in the control group, with statistically significant differences ( t=2.828, 4.880; both P<0.05), while the Bruggrmann Comfort Scale score was higher than that in the control group ( t=2.774, P<0.05).There were no statistically significant differences in operation time, surgical success rate or incidence of complications between the two groups ( t=0.595, P=0.554; χ2=0.346, 0.263; both P>0.05).Satisfaction rate of patients in the experimental group was 97.5%(39/40), which was higher than 85.0%(34/40) in the control group, with a statistically significant difference ( χ2=3.914, P=0.048). Conclusions:For PDR patients undergoing vitreous surgery under local anesthesia, using an ophthalmic surgical open ventilation mask for oxygen inhalation can effectively enhance respiratory comfort level, alleviate anxiety, maintain stable vital signs, improve overall comfort level, and ensure smooth surgery, without observed adverse reactions related to mask use, which makes it worthy of clinical promotion and application.

With the rapid development of medical big data and artificial intelligence,Clinical Prediction Models(CPMs)have become pivotal tools for disease prevention,diagnosis,and treatment.Current research predominantly focuses on the economic analysis of pharmacological or public health interventions,yet a comprehensive methodological framework for the economic evaluation of CPMs has been notably absent.The Guidelines for Economic Evaluation of Clinical Prediction Models(hereafter the Guidelines),jointly initiated by the Chinese Research Hospital Association and Peking University,Tsinghua University,and Capital Medical University,adheres to the WHO Handbook for Guideline Development and the Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards.A multidisciplinary collaboration,including a steering committee,expert panel,secretariat,and external review group,was established to develop the guideline following evidence-based principles and procedures.Consensus recommendations were formulated through the Delphi method.It describes the background,objectives,target group,and the development methodology and process,ensuring the entire compilation process of the Guidelines is transparent and standardized.Through comprehensive evidence retrieval,systematic evidence appraisal,and a scientific approach to forming recommendations,the scientific rigor and validity of the Guidelines were further enhanced.

Objective:To search, evaluate, and summarize the best evidence of built-in fecal incontinence management device, to inform the management of incontinence dermatitis by clinical healthcare professionals.Methods:BMJ Best Practice, UpToDate, Guideline International Network, Joanna Briggs Institute, National Institute for Health and Care Excellence, Scottish Intercollegiate Guidelines Network, Registered Nurses′Association of Ontario, The Cochrane Library, Medline, Embase, SinoMed, CINAHL, PubMed, Web of Science, OVID, China National Knowledge Infrastructure, Wanfang Database were systematically searched for all evidence regarding the application of fecal collection devices. It included clinical practice, guidelines, systematic reviews, expert consensuses, evidence summaries, and randomized controlled trial. Two researchers independently evaluated the literature quality and extracted the literature that met the standards.Results:A total of 12 pieces of the literature were involved, including 2 best practice, 5 guidelines, 3 expert consensuses, and 2 systematic reviews. This study summarized 26 pieces of best evidence in relation to the following 5 themes: indications and contraindications, device insertion, device maintenance, device removal and effectiveness evaluation.Conclusions:This study scientifically and systematically summarized the best evidence regarding the insertion and maintenance of built-in fecal incontinence management device. We recommend that clinical practitioners integrate this evidence into their practice, while considering individual patient preferences and medical contexts. Adhering to individualization for evidence translation improves standardization and benefits patients in the clinical use of fecal collection devices.

Objective:To analyze the current situation of health-related quality of life (HRQOL) and its influencing factors among community-dwelling elderly with mild cognitive impairment (MCI) based on the health ecology model (HEM).Methods:From December 2023 to September 2024, a cross-sectional survey was conducted among 997 community-dwelling elderly in Beijing, Shandong, Chongqing and other regions. The EuroQol five-dimensional questionnaire 5 level (EQ-5D-5L), the Montreal cognitive assessment (MoCA), and the Pittsburgh sleep quality index (PSQI) were used to assess the subjects.Descriptive analysis, Mann-Whitney U test, Kruskal-Wallis test, and Tobit regression analysis were performed using Stata 18.0 software. Results:A total of 324 valid samples were finally obtained, and the health utility value of MCI elderly was 0.842(0.815, 0.951). Tobit regression analysis showed that ≥80 years old( β=-0.121, 95% CI=-0.193--0.050) in individual traits level, don't exercise( β=-0.196, 95% CI=-0.255--0.137) and poor quality of sleep ( β=-0.064, 95% CI=-0.116--0.013) in behavior characteristics level, and poor subjective economic status( β=-0.153, 95% CI=-0.261--0.045) in living and working conditions level were risk factors for the health utility value of the elderly with MCI. Drinking( β=0.096, 95% CI=0.022-0.171) in behavior characteristics level and participating in social activities( β=0.126, 95% CI=0.062-0.190) in interpersonal network level were protective factors for the health utility value of the elderly with MCI. Conclusions:The HRQOL of the community-dwelling elderly with MCI in China is low, and its influencing factors are multi-level. HEM should be combined to strengthen the intervention and management of the elderly with MCI from personal constitution to policy environment to improve their HRQOL.

With the rapid development of medical big data and artificial intelligence,Clinical Prediction Models(CPMs)have become pivotal tools for disease prevention,diagnosis,and treatment.Current research predominantly focuses on the economic analysis of pharmacological or public health interventions,yet a comprehensive methodological framework for the economic evaluation of CPMs has been notably absent.The Guidelines for Economic Evaluation of Clinical Prediction Models(hereafter the Guidelines),jointly initiated by the Chinese Research Hospital Association and Peking University,Tsinghua University,and Capital Medical University,adheres to the WHO Handbook for Guideline Development and the Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards.A multidisciplinary collaboration,including a steering committee,expert panel,secretariat,and external review group,was established to develop the guideline following evidence-based principles and procedures.Consensus recommendations were formulated through the Delphi method.It describes the background,objectives,target group,and the development methodology and process,ensuring the entire compilation process of the Guidelines is transparent and standardized.Through comprehensive evidence retrieval,systematic evidence appraisal,and a scientific approach to forming recommendations,the scientific rigor and validity of the Guidelines were further enhanced.

Objective: To conduct network analysis of biased constitution to provide theoretical basis for daily health management. Methods: Purposive sampling and snowball sampling methods were used to collect the required data via a web-based questionnaire from February 3rd, 2022 to January 21st, 2023. The tendency scores of 8 biased constitutions (qi-deficiency type, yang-deficiency type, yin-deficiency type, phlegm-dampness type, damp-heat type, blood-stasis type, qi-depression type, and special diathesis type) were evaluated by 30-Item Short Version of Constitution in Chinese Medicine Questionnaire. Data analysis was conducted in R. The qgraph package was used to construct network analysis models and calculate the edge weight, namely regularised partial correlation coefficients (r) and centrality coefficients (including strength, closeness, betweenness and expected influence), while mgm was used to calculate the predictability of each node within the network. The ggplot2 package was used to visualize network analysis result, and bootnet was applied to assess the structural reliability and robustness of the network, including the r accuracy assessment, the stability assessment of the centrality coefficients, and the difference test result of node centrality coefficients. Results: A total of 3, 691 valid samples were obtained from the survey. The result of the network analysis showed that: (1) the strength of the association between phlegm dampness type and damp-heat type (r=0.370), qi-deficiency type and qi-depression type (r =0.315), qi-deficiency type and special diathesis type (r=0.260), qi-deficiency type and phlegm-dampness type (r=0.247), and the phlegm-dampness type and qi-depression type (r=0.247) was high. (2) The centrality of phlegm-dampness type and qi-deficiency type was the strongest, and the differences between the centrality coefficients of phlegm-dampness type and qi-deficiency type were not significant. There were no other nodes where all 4 centrality coefficients were not significantly different from qi-deficiency type and phlegm-dampness type, and the predictability of phlegm-dampness type and qi-deficiency type was the highest. (3)The result of the r accuracy assessment showed that the r of this network did not differ significantly from the average of multiple samples, so the r accuracy of this network was high. (4) Correlation stability(CS) coefficient of the four centrality indicators were CS Strength=0.59, CS Closeness=0.75, CS Betweenness=0.75, and CS Expected influence=0.75. This indicated that the stability of the centrality indicators of this network was very good. Conclusion Complex connections exist between various biased constitutions, and phlegm-dampness type and qi-deficiency type are the two key biased constitutions in the entire biased constitution.

Objective:To evaluate the utility of ultrasonographic monitoring of the rectus femoris muscle—specifically, the rates of change in thickness and cross-sectional area (CSA)—in assessing nutritional status and long-term functional outcomes in patients with sepsis.Methods:In this prospective observational study, sepsis patients admitted to the ICU of the Second Affiliated Hospital of Soochow University between October 2023 and October 2024 were classified by nutritional status at discharge using the Global Leadership Initiative on Malnutrition (GLIM) criteria. Differences in serial ultrasound-measured rectus femoris thickness and CSA on days 1, 3, 5, and 7 were compared between malnourished and non-malnourished groups. The predictive value of these ultrasound parameters for malnutrition was analyzed. Functional prognosis was assessed using the Sarcopenia Assessment Scale, Short Physical Performance Battery, and Manual Muscle Testing, with correlations to muscle changes examined.Results:Of the 71 enrolled patients (median age 73.00 [ IQR: 61.00–80.00]; 47.89% female, 52.11% male), those with malnutrition showed significantly greater variation rates in rectus femoris thickness and CSA on days 3, 5, and 7 compared to the non-malnourished group ( P < 0.05). ROC analysis revealed that the day-7 CSA variation rate had the highest predictive value for malnutrition (AUC = 0.817, 95% CI: 0.713-0.930). These muscle variation rates also correlated strongly with conventional nutritional markers such as BMI, albumin, and urea. Similarly, patients with impaired functional outcomes exhibited higher variation rates in muscle parameters on days 3, 5, and 7 ( P < 0.05), with the day-7 CSA variation rate being most predictive of functional prognosis (AUC = 0.749, 95% CI: 0.632-0.867). Conclusions:Ultrasonographic assessment of rectus femoris thickness and CSA variation rates provides a valuable tool for evaluating nutritional status and predicting functional prognosis in sepsis patients, outperforming traditional biomarkers. This method shows promise for guiding individualized nutrition support and rehabilitation strategies to improve long-term outcomes.

Objective:Based on bioinformatics analysis, this study aimed to identify the complement component 5a receptor 1(C5aR1)and chemokine C-C motif ligand-2(CCL2)genes in vascular dementia(VaD)and to explore the expression and clinical significance of serum C5aR1 and CCL2 levels in VaD patients.Methods:The GSE122063 dataset was selected from the Gene Expression Omnibus(GEO)database to screen for consistently differentially expressed genes in the frontal and temporal lobes of VaD patients and non-dementia patients.The Matascape database was used to analyze the functions and pathways of differentially expressed genes, and the STRING network and Cytoscape software were used to identify key genes.In this case-control study, 53 VaD patients seeking care at the Department of Neurology of the Affiliated Hospital of Jiangsu University between January 2022 and December 2022 were included in the VaD group, and 50 non-dementia individuals were included in the control group.General information, Montreal Cognitive Assessment(MoCA)scores, Mini-Mental State Examination(MMSE)scores, and scores of the total cerebral small vessel disease(CSVD)burden were collected for both groups, and serum C5aR1 and CCL2 expression was detected.The correlation of serum C5aR1 and CCL2 levels with MoCA scores, MMSE scores, and scores of the total CSVD burden in the VaD group was analyzed.Receiver operating characteristic(ROC)curve analysis was used to assess the diagnostic value of serum C5aR1 and CCL2 levels in VaD.Results:In the GSE122063 dataset, compared with non-dementia patients, there were 43 upregulated genes and 63 downregulated genes simultaneously in the frontal and temporal lobes in the VaD group.After importing 106 genes into the Cytoscape software and using the Stress and Betweenness algorithms in the cytoHubba plugin, two key genes, C5aR1 and CCL2, were identified.Serum levels of C5aR1[(57.25±10.34)μg/L vs.(43.26±8.24)μg/L, t=7.607, P<0.001]and CCL2[(210.42±42.19)ng/L vs.(151.73±36.04)ng/L, t=7.570, P<0.001]in the VaD group were higher than those in the control group.Serum levels of C5aR1 and CCL2 were negatively correlated with MoCA scores( r=-0.691, -0.668, P<0.001)and MMSE scores( r=-0.736, -0.729, P<0.001), and positively correlated with scores of the total CSVD burden( r=0.598, 0.582, P<0.001).The areas under the ROC curve for serum C5aR1 and CCL2 levels in diagnosing VaD was 0.838 and 0.845, respectively.The area under the ROC curve with the combination of C5aR1 and CCL2 for the diagnosis of VaD was 0.896. Conclusions:Serum levels of C5aR1 and CCL2 are elevated in VaD patients and closely related to their cognitive function and the total CSVD burden, and may be used as an auxiliary diagnostic tool for VaD patients.