OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

ObjectiveTo evaluate the efficacy and possible mechanism of Wei's Huoxue Tongluo Formula （韦氏活血通络方，WHTF） in treating atrophic-stage non-arteritic anterior ischemic optic neuropathy （NAION） with qi deficiency and blood stasis. MethodsA total of 82 atrophic-stage NAION patients with qi deficiency and blood stasis were randomly divided into a treatment group and a control group， with 41 cases in each group. The treatment group was given oral administration of WHTF twice a day plus acupoint injection of distilled water 2 ml at Taiyang （EX-HN5） once daily， while the control group received injection of compound anisodine injection 2 ml at Taiyang （EX-HN5） once daily and oral administration of WHTF placebo twice a day. Both groups received treatment for a course of 14 days. The best-corrected visual acuity （BCVA）， optic disc perfusion density （PD）， flux index （FI）， macular superficial PD， vascular density （VD）， and traditional Chinese medicine （TCM） syndrome scores were compared between groups before treatment and on day 7 and day 14 of treatment. Additionally， mean defect （MD） and mean sensitivity （MS） of visual fields were measured before treatment and on day 14， along with safety evaluation. ResultsAfter treatment， both groups showed significant improvement in BCVA， visual field MD and MS， and TCM syndrome scores （P＜0.05 or P＜0.01）. On day 14 of treatment， the TCM syndrome score in the treatment group was significantly lower than that in the control group （P＜0.05）. There was no significant improvement in optic disc PD and FI， and macular superficial PD and VD after treatment in either group （P＞0.05） except that on day 7 the macular superficial foveal PD in the control group was significantly better than that in the treatment group （P＜0.05）. During the treatment period， no serious adverse events occurred in either group. ConclusionWHTF can improve the visual function indicators including visual acuity and visual field， as well as TCM syndrome scores in atrophic-stage NAION patients with qi deficiency and blood stasis. It shows clinical safety， although it does not appear to have a significant effect on optic disc or macular blood flow.

ObjectiveTo analyze the output and efficiency of chronic disease management services for hypertension and diabetes in community health service institutions in Shanghai, to evaluate the allocation and efficiency of chronic disease management resources, and to provide references for improving the efficiency of chronic disease management in Shanghai’s communities. MethodsA total of 73 community health institutions from 15 districts of Shanghai were selected. Based on the chronic disease management resource data of community health institutions in 2019, 2021, and 2023, descriptive methods and the BCC model in Data Envelopment Analysis (DEA) were used to analyze the resource allocation, service output, and the efficiency of chronic disease management services in community health institutions in Shanghai. ResultsFrom 2019 to 2023, the indicators of resource allocation and service output of community health service institutions in Shanghai all showed upward trends. In terms of service efficiency, the average number of chronic disease patients managed by each health technician decreased from 237 to 231, and the number of patients served per 1 000 working hours decreased from 54 to 44. DEA efficiency analyses showed that the average overall efficiency increased from 0.867 in 2019 to 0.886 in 2021 and then decreased to 0.811 in 2023. The average technical efficiency decreased from 0.901 to 0.847, which was the main reason for the decline in overall efficiency. The average scale efficiency showed an initial increase followed by a decrease, rising from 0.961 in 2019 to 0.977 in 2021 and dropping back to 0.955 in 2023. The number of strong effective districts (overall efficiency=1.000) decreased from 6 in 2019 to 3 in 2023, and the efficiency differences between districts expanded. The range of overall efficiency widened from 0.622‒1.000 to 0.513‒1.000, indicating a decline in overall efficiency and an increase in inter-district heterogeneity. ConclusionFrom 2019 to 2023, the total volume of resource allocation and service output for chronic disease management in community health service institutions in Shanghai increased continuously. However, both the service output efficiency and the overall resource allocation efficiency declined, driven primarily by a decrease in technical efficiency, and accompanied by widening inter‑district disparities.

AIM: To explore the factors influencing heart rate(HR)changes during small incision lenticule extraction(SMILE)surgery by monitoring HR trends at different time points of the procedure.METHODS: Prospective cohort study. A total of 69 patients who underwent SMILE surgery at the Laser Vision Correction Center of Xi'an No.1 Hospital from April to May 2024 were enrolled. Before the surgery, patients completed the State Anxiety Inventory(S-AI, questions 1-20)to assess their preoperative anxiety scores related to the next day's surgery. Baseline HR was recorded using medical pulse oximeter, and real-time HR was recorded during patient positioning, lenticule scanning, lenticule separation and extraction, and the application of postoperative eye drops.RESULTS: The HR during patient positioning was 83.61±13.87 bpm, which was significantly different from the baseline HR(77.52±10.88 bpm), HR during lenticule separation and extraction(75.54±12.52 bpm), and HR during postoperative eye drop application(76.65±10.54 bpm; all P<0.001). When stratified by median age, older patients(>26 years)had the HR during lenticule separation and extraction 76.27±9.93 bpm, which differed from the HR at positioning(84.82±14.10 bpm)and at lens scanning(82.76±13.72 bpm; all P<0.005). Stratified by gender, the HR of male patients at positioning was the highest(85.31±16.61 bpm), which differed significantly from the baseline HR(78.26±12.63 bpm), HR during lenticule separation and extraction(77.14±14.59 bpm), and HR during postoperative eye drop application(77.11±12.49 bpm; all P<0.005). There was no correlation between HR during positioning and preoperative anxiety scores(r=0.124, P=0.418).CONCLUSION: HR changes during SMILE surgery vary with different procedural stages, peaking during patient positioning and reaching the lowest point during lenticule separation and extraction. Older patients showed higher HR during positioning, and male patients exhibited higher HR during positioning.

The analysis presented here is based on the blood components of Guanxin Qiwei tablets, the key anti-atherosclerosis pathway of Guanxin Qiwei tablets was screened by network pharmacology, and the anti-atherosclerosis mechanism of Guanxin Qiwei tablets was clarified and verified by cell experiments. HPLC-Q-Exactive-MS/MS technique was used to analyze the components of Guanxin Qiwei tablets into blood, to determine the precise mass charge ratio of the compounds, and to conduct a comprehensive analysis of the components by using secondary mass spectrometry fragments and literature comparison. Finally, a total of 42 components of Guanxin Qiwei tablets into blood were identified. To better understand the interactions, we employed the Swiss Target Prediction database to predict the associated targets. Atherosclerosis (AS) disease targets were searched in disease databases Genecard, OMIM and Disgent, and 181 intersection targets of disease targets and component targets were obtained by Venny 2.1.0 software. Protein interactions were analyzed by String database. The 32 core targets were selected by Cytscape software. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed in DAVID database. It was found that the anti-atherosclerosis pathways of Guanxin Qiwei tablets mainly include lipid metabolism and atherosclerosis and AGE-RAGE signaling pathway in diabetic complications and other signal pathways. The core targets and the core compounds were interlinked, and it was found that cryptotanshinone and tanshinone ⅡA in Guanxin Qiwei tablets were well bound to TNF, PPARγ, AKT1, PTG2 and other targets. The lipid metabolism and atherosclerotic pathway was verified using human hl-7702 hepatocytes. This study preliminarily identified the potential pharmacodynamic components of Guanxin Qiwei tablets in the treatment of AS diseases and predicted their pathways of action, and verified the relationship between regulating lipid metabolism and atherosclerosis of Guanxin Qiwei tablets in vitro, providing a reference for the further study of the pharmacodynamic material basis and mechanism of action of this prescription. This experiment was approved by the Medical Ethics Committee of Inner Mongolia Medical University (No. YKD202401262).

Nine compounds were isolated and purified from 90% ethanol extract of Alstonia mairei Lévl by using various chromatographic methods, including silica gel, SephadexLH-20, MCI Gel and ODS column chromatography, combined with semi-preparative liquid phase separation methods. Modern spectroscopic methods (1D and 2D NMR, UV, IR, MS, etc.) were used to identify the structures of the isolated compounds. They were identified as mairoside A (1), 3′,6-di-O-sinaloylsucrose (2), myristic acid (3), methyl myristate (4), ethyl myristate (5), 3,4,5-trimethoxycinnamic acid (6), 3,4,5-trimethoxybenzoic acid (7), vinoline (8), kaempferol-3-O-rutinoside (9), among which compound 1 is a new glycoside, compounds 4 and 5 are new natural products, and the nuclear magnetic data of compound 4 were reported for the first time.

ObjectiveTo investigate the optimal ratio of goat horn replacing antelope horn in Fufang Lingjiao Jiangya pills and the blood pressure-lowering mechanism of this medicine. MethodsThe blood pressure-lowering efficacy of Fufang Lingjiao Jiangya pills with varying proportions of goat horn replacing antelope horn was evaluated on spontaneous hypertensive rats （SHR）. In this experiment， 50 SHR rats were randomly grouped as follows： model （n=8）， captopril （0.01 g·kg^-1） （n=6）， low-dose blank Fufang Lingjiao Jiangya pills （0.342 g·kg^-1） （n=6）， high-dose blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1） （n=6）， low-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， high-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）， low-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， and high-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）. Additionally， 8 WKY rats were used as the normal group. Drugs were administered by gavage for 4 weeks while an equal volume of distilled water was administered for the normal and model groups. Blood pressure was measured before administration， 3 h post administration， and biweekly thereafter. In the experiment for Fufang Lingjiao Jiangya pills with goat horn replacing antelope horn in different proportions， 48 SHR rats were randomly grouped as follows： model， blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1）， antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1）， 2× goat horn-containing Fufang Lingjiao Jiangya pills （0.824 g·kg^-1）， 4× goat horn Fufang Lingjiao Jiangya pills （0.969 g·kg^-1）， and 6× goat horn Fufang Lingjiao Jiangya pills （1.112 g·kg^-1）. The normal group included 8 WKY rats， and the normal group and model group received an equal volume of distilled water. The treatment lasted for 2 weeks， and blood pressure was recorded at various time points （pre-administration， 3 h post administration， and on days 4， 7， 10， and 14 of administration）. Serum levels of angiotensin-converting enzyme （ACE）， angiotensin Ⅱ（Ang Ⅱ）， renin， and interleukin-6 （IL-6） were measured by enzyme-linked immunosorbent assay. Histopathological changes in the heart， kidney， and thoracic aorta were observed by hematoxylin-eosin staining. The protein levels of ACE2， angiotensin Ⅱ type 1 receptor （AT1R）， and angiotensinogen （AGT） in the kidney tissue were determined by Western blot， while the expression of nuclear factor （NF）-κB p65 and Toll-like receptor 4 （TLR4） in the thoracic aorta tissue was assessed by immunohistochemistry. ResultsCompared with the model group， all treatment groups showed lowered blood pressure （P<0.05， P<0.01）， and the 6× goat horn-containing Fufang Lingjiao Jiangya pills group showed consistent blood pressure-lowering effect with the antelope horn-containing Fufang Lingjiao Jiangya pills group. Compared with the normal group， the model group showed elevated serum levels of ACE， Ang Ⅱ， renin， and IL-6， while the elevations were declined in the Fufang Lingjiao Jiangya pills groups （P<0.05， P<0.01）. Pathological changes in the heart， kidney， and thoracic aorta were alleviated in all the treatment groups， with the 6× goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups exhibited the best effect. Western blot and immunohistochemistry results showed that all the treatment groups exhibited down-regulated protein levels of AT1R， AGT， NF-κB p65， and TLR4 and up-regulated protein levels of ACE2 （P<0.05， P<0.01） compared with model group， with the 6×goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups showcasing the best effect. ConclusionReplacing antelope horn with 6×goat horn in Fufang Lingjiao Jiangya pills can achieve consistent blood pressure-lowering effect with the original prescription. The prescription may exert the effect by inhibiting the renin-angiotensin-aldosterone system （RAAS） and TLR4/NF-κB signaling pathways.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

OBJECTIVE To evaluate the influence of pharmaceutical quality control on the efficiency and outcomes of standardized medication therapy management （MTM） services for patients with coronary heart disease by using Economic， Clinical and Humanistic Outcomes （ECHO） model. METHODS This study collected case data of coronary heart disease patients who received MTM services during January-March 2023 （pre-quality control implementation group， n＝96） and June-August 2023 （post-quality control implementation group， n＝164）. Using propensity score matching analysis， 80 patients were selected from each group. The study subsequently compared the economic， clinical， and humanistic outcome indicators of pharmaceutical services between the two matched groups. RESULTS There were no statistically significant differences in baseline data between the two groups after matching （P＞0.05）. Compared with pre-quality control implementation group， the daily treatment cost （16.26 yuan vs. 24.40 yuan， P＜0.001）， cost-effectiveness ratio [23.12 yuan/quality-adjusted life year （QALY） vs. 32.32 yuan/QALY， P＜0.001]， and the incidence of general adverse drug reactions （2.50% vs. 10.00%， P＝0.049） of post-quality control implementation group were decreased significantly； the utility value of the EuroQol Five-Dimensional Questionnaire （0.74± 0.06 vs. 0.71±0.07， P＝0.003）， the reduction in the number of medication related problems （1.0 vs. 0.5， P＜0.001）， the medication adherence score （[ 6.32±0.48） points vs. （6.10±0.37） points， P＝0.001]， and the satisfaction score （[ 92.56±1.52） points vs. （91.95±1.56） points， P＝0.013] all showed significant improvements. Neither group experienced serious adverse drug reactions. There was no statistically significant difference in the incidence of new adverse reactions between the two groups （1.25% vs. 3.75%， P＝0.310）. CONCLUSIONS Pharmaceutical quality control can improve the quality of pharmaceutical care， and the ECHO model can quantitatively evaluate the effect of MTM services， making pharmaceutical care better priced and more adaptable to social needs， thus being worthy of promotion.