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）］

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

ObjectiveTo investigate the potential mechanism of action of the Qufeng Tongqiao Cough-relieving Decoction （祛风通窍止咳方， QTCD） in the treatment of upper airway cough syndrome （UACS）. MethodsTwenty-four guinea pigs were randomly divided into blank group， model group， traditional Chinese medicine （TCM） group， and inhibitor group， with six guinea pigs in each group. Except for the blank group， guinea pigs were sensitized with ovalbumin and aluminum hydroxide via intraperitoneal injection， followed by ovalbumin nasal drops combined with smoke exposure to establish the UACS model. After modeling， the TCM group was administered QTCD 0.9 g/（100 g·d） by gavage， the inhibitor group received the transient receptor potential vanilloid receptor 4 （TRPV4） inhibitor GSK2193874 1 mmol/L， 5 min by nebulisation， and the blank group and model group were given 2 ml/（100 g·d） normal saline by gavage once daily. After 7 days of treatment， a cough provocation test was performed using 0.4 mol/L citric acid. The levels of IgE in serum and inflammatory cytokines， including interleukin-6 （IL-6）， interleukin-8 （IL-8） in serum， bronchoalveolar lavage fluid （BALF）， and nasal lavage fluid （NLF） were detected by enzyme-linked immunosorbent assay （ELISA）. Histopathological changes in lung and nasal mucosal tissues were observed by hematoxylin-eosin （HE） staining. Immunohistochemistry was used to detect the protein levels of TRPV4， substance P （SP）， and calcitonin gene-related peptide （CGRP） in lung and nasal mucosal tissues. Real-time polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of TRPV4， SP， and CGRP in lung tissues. ResultsHE staining showed significant structural damage and infiltration of inflammatory cells in the lung and nasal mucosal tissues in the model group， while the TCM group and inhibitor group showed improved pathological changes. Compared with the blank group， the model group showed increased cough frequency， serum IgE level， and IL-6 and IL-8 levels in serum， BALF， and NLF. The protein levels of TRPV4， SP， and CGRP in lung and nasal mucosal tissues and their mRNA expression were elevated （P＜0.05 or P＜0.01）. Compared with the model group， the TCM group and inhibitor group showed reduced cough frequency， serum IgE level， and TRPV4 and SP mRNA expression in lung tissues. The TCM group showed reduced IL-6 and IL-8 levels in serum， BALF， and NLF， and reduced TRPV4 and CGRP protein levels in lung and nasal mucosal tissues. The inhibitor group showed reduced IL-6 and IL-8 levels in serum， BALF， and NLF， reduced IL-6 in BALF， reduced IL-8 in NLF， and decreased TRPV4， SP， and CGRP protein levels in lung tissues and SP and CGRP protein levels in nasal mucosal tissues （P＜0.05 or P＜0.01）. Compared with the TCM group， the inhibitor group had increased serum IgE， IL-6， and IL-8 levels， increased IL-6 level in BALF， and increased IL-8 levle in NLF， but decreased SP protein level in lung tissues and increased TRPV4 and SP mRNA expression in lung tissues （P＜0.01）. ConclusionQTCD effectively reduces cough frequency in the UACS guinea pig model. Its mechanism may involve inhibiting the activation of the TRPV4 pathway， improving airway neurogenic inflammation， alleviating inflammatory responses， and reducing cough hypersensitivity.

Polycystic ovary syndrome（PCOS） and its resulting infertility is one of the common diseases of gynecology and reproductive endocrinology. The phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt） signaling pathway is relatively well-studied in the development of intervention in PCOS， and the experiments on PCOS in rats conducted by traditional Chinese medicine through this signaling pathway is also the main direction of mechanistic research. In this paper， 20 articles published in academic journals in the past 5 years were selected through the corresponding criteria， and the objective situation and existing problems of the selected research projects were analyzed from five aspects， namely， baseline data， modeling and treatment， grouping， evaluative indexes， and pharmacodynamic indexes. It is found that there were different degrees of problems in each research project， such as the observation indicators of modeling， criteria for judging the success of the model， the treatment period， the calculation of dosage of prescription/active ingredients and specific dosage were not clearly defined， which could easily lead the bias of the results or reduce the validity of experimental data. Based on this， the list of PCOS rat experimental research operations was formed， involving five categories of experimental rats， model construction， study implementation， outcome measures and analysis and report with a total of 21 operation lists， with a view to provide a reference for the subsequent PCOS experiments related to scientific research and helping to form high-quality results.

BACKGROUND:Currently,there have been studies on three-dimensional digitalization and visualization systems for adult acupoints,but there are not many reports on the visualization of pediatric acupoints based on real pediatric digital sectional anatomical datasets. OBJECTIVE:To design and develop a digital three-dimensional visualization system for children's neck acupoints,to provide a basis for acupuncture and moxibustion,meridian and acupoint science teaching,clinical practice,acupuncture manipulation practice,and acupuncture safety research,and to provide a basis for the development of children's acupoint simulation system. METHODS:Based on a real cross-sectional anatomical dataset of pre-school boys,a three-dimensional digital virtual anatomical model of the neck region of children and internal multi-organ three-dimensional reconstruction were completed using PhotoShop 2021 and Digihuman Reconstruction System software.A database of 11 acupoints was compiled,including Fengfu and Fengchi,using the Unity database language.A three-dimensional model of children's neck anatomy,acupoint database,and writing acupuncture operation codes were integrated in Unity3D software.A three-dimensional digital visualization system for children's neck acupoints was successfully created,which integrated simulation acupoint positioning,three-dimensional acupoint anatomy,acupuncture training,clinical teaching,and acupuncture safety research. RESULTS AND CONCLUSION:(1)This study was based on real child specimens.Manual layer by layer segmentation of cross-sectional images was used to ensure the accuracy of the three-dimensional model to the greatest extent possible.The 3D software Digihuman Reconstruction System was utilized to extract and save independent segmentation data.PhotoShop 2021 software was collaborated with to complete dozens of three-dimensional reconstruction anatomical models of the outer skin of the neck and its internal bone structure,cervical spinal cord,blood vessels and nerves,muscles,and ligaments in children.The basic morphology and overall contour integrity verification of each independent structure were completed in MeshLab software.The 3-material research 13.0 software was applied for final fine tuning and anatomical position confirmation,successfully simulating and restoring the true anatomical morphology of the neck of preschool children.(2)Based on and referring to the national standards of the People's Republic of China,a database of commonly used acupoints in children's neck region was collected and organized,including their names,meridians,positioning,local anatomy,needle insertion levels,acupuncture methods,acupuncture accidents and prevention,acupoint indications,and two-dimensional anatomical sectional images.(3)Unity3D software was employed to integrate the three-dimensional model of children's neck,acupuncture simulation operation,and acupoint database,and a three-dimensional digital children's neck acupoint acupuncture visualization system was successfully constructed.The system displayed information on children's neck acupoints,two-dimensional and three-dimensional anatomical structures,and achieved two-dimensional and three-dimensional acupuncture simulation functions and acupuncture safety research functions for children's neck acupoints.Based on the ultra-thin sectional anatomical dataset of real child specimens,the first three-dimensional digital and visualization system for acupoints in the neck region of children had been constructed.Compared with previous acupoint acupuncture systems,it is more in line with the anatomical and morphological development characteristics of Asian children and has high application value in the fields of acupuncture safety research,clinical teaching,and acupuncture simulation training.

BACKGROUND: Preclinical studies have indicated that Angong Niuhuang Pills (ANP) reduce cerebral infarct and edema volumes. This study aimed to investigate whether ANP safely reduces cerebral infarct and edema volumes in patients with moderate to severe acute ischemic stroke. METHODS: This randomized, double-blind, placebo-controlled pilot trial included patients with acute ischemic stroke with National Institutes of Health Stroke Scale (NIHSS) scores ranging from 10 to 20 in 17 centers in China between April 2021 and July 2022. Patients were allocated within 36 h after onset via block randomization to receive ANP or placebo (3 g/day for 5 days). The primary outcomes were changes in cerebral infarct and edema volumes after 14 days of treatment. The primary safety outcome was severe adverse events (SAEs) for 90 days. RESULTS: There were 57 and 60 patients finally included in the ANP and placebo groups, respectively for modified intention-to-treat analysis. The median age was 66.0 years, and the median NIHSS score at baseline was 12.0. The changes in cerebral infarct volume at day 14 were 0.3 mL and 0.4 mL in the ANP and placebo groups, respectively (median difference: -7.1 mL; interquartile range [IQR]: -18.3 to 2.3 mL, P = 0.30). The changes in cerebral edema volume of the ANP and placebo groups on day 14 were 11.4 mL and 4.0 mL, respectively ( median difference: 3.0 mL, IQR: -1.3 to 9.9 mL, P = 0.15). The rates of SAE within 90 days were similar in the ANP (3/57, 5%) and placebo (7/60, 12%) groups ( P = 0.36). Changes in serum mercury and arsenic concentrations were comparable. In patients with large artery atherosclerosis, ANP reduced the cerebral infarct volume at 14 days (median difference: -12.3 mL; IQR: -27.7 to -0.3 mL, P = 0.03). CONCLUSIONS: ANP showed a similar safety profile to placebo and non-significant tendency to reduce cerebral infarct volume in patients with moderate-to-severe stroke. Further studies are warranted to assess the efficacy of ANP in reducing cerebral infarcts and improving clinical prognosis. TRAIL REGISTRATION Clinicaltrials.gov , No. NCT04475328.
Aged ; Female ; Humans ; Male ; Middle Aged ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Ischemic Stroke/drug therapy* ; Pilot Projects ; Stroke/drug therapy* ; Treatment Outcome

BACKGROUND: Pre-transplant exposure to immune checkpoint inhibitors (ICIs) significantly increases the risk of allograft rejection after liver transplantation (LT); however, whether ICI-related rejection leads to increased graft loss remains controversial. Therefore, this study aimed to investigate the association between ICI-related allograft rejection and perioperative graft loss. METHODS: This was a retrospective analysis of adult liver transplant recipients with early biopsy-proven T-cell-mediated rejection (TCMR) at Liver Transplantation Center of Sun Yat-sen Memorial Hospital from June 2019 to September 2024. The pathological features, clinical characteristics, and perioperative graft survival were analyzed. RESULTS: Twenty-eight patients who underwent early TCMR between June 2019 and September 2024 were included. Based on pre-LT ICI exposure, recipients were categorized into ICI-related TCMR (irTCMR, n = 12) and conventional TCMR (cTCMR, n = 16) groups. Recipients with irTCMR had a higher median Banff rejection activity index (RAI) (6 vs . 5, P = 0.012) and more aggressive tissue damage and inflammation. Recipients with irTCMR showed higher proportion of treatment resistance, achieving a complete resolution rate of only 8/12 compared to 16/16 for cTCMR. Graft loss occurred in 5/12 of irTCMR recipients within 90 days after LT, with no graft loss in cTCMRs recipients. Cox analysis demonstrated that irTCMR with an ICI washout period of <30 days was an independent risk factor for perioperative graft loss (hazard ratio [HR], 6.540; 95% confidence interval [CI], 1.067-40.067, P = 0.042). CONCLUSION IrTCMR is associated with severe pathological features, increased resistance to treatment, and higher graft loss in adult liver transplant recipients.
Humans ; Liver Transplantation/adverse effects* ; Male ; Female ; Middle Aged ; Retrospective Studies ; Graft Rejection/immunology* ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; T-Lymphocytes/drug effects* ; Graft Survival/immunology* ; Aged

The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans ; Sarcopenia/physiopathology* ; Obesity/physiopathology* ; Aging/physiology* ; Autophagy/physiology* ; Insulin Resistance ; Comorbidity ; Vitamin D/metabolism* ; Gonadal Steroid Hormones/metabolism* ; Gastrointestinal Microbiome ; Mitochondria ; MicroRNAs

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.