Objective To systematically evaluate the efficacy and safety of traditional Chinese medicine (TCM) compound in treating pulmonary nodules, providing evidence-based medical evidence for TCM intervention in pulmonary nodules. Methods Computer search of PubMed, CNKI, Wanfang, VIP, and SinoMed was conducted to select randomized controlled trials (RCTs) of TCM compound intervention in pulmonary nodules, with the retrieval time from the inception to November 29, 2023. The Cochrane bias risk assessment tool was used to evaluate the quality of the included studies, and Review Manager 5.4 was used for Meta-analysis. Results A total of 18 RCTs were included, covering 8 provinces across the country, with a total sample size of 1301 patients. The TCM compounds used in the included studies all incorporated the method of dissolving phlegm and dissipating nodules. There was a high risk of bias uncertainty in the included studies. Meta-analysis results suggested that TCM compound could significantly reduce the diameter of pulmonary nodules [MD=−1.41, 95%CI (−1.70, −1.13), P<0.001], decrease the number of nodules [MD=−0.37, 95%CI (−0.73, −0.01), P=0.05], alleviate clinical symptoms [MD=−4.84, 95%CI (−6.04, −3.64), P<0.001], and improve lung function [forced expiratory volume in one second (FEV1), MD=0.55, 95%CI (0.09, 1.01), P=0.02; FEV1/forced vital capacity, MD=6.12, 95%CI (4.47, 7.78), P<0.001]. However, there was no statistically significant difference in the probability of malignancy between the experimental group and the control group [MD=−0.01, 95%CI (−0.01, 0.00), P=0.09]. Conclusion TCM compound can significantly reduce the diameter of pulmonary nodules, decrease the number of nodules, alleviate clinical symptoms, and improve lung function, but future multicenter, large-sample, high-quality RCTs are still needed to further explore and verify this conclusion.

Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.

Objective To investigate the predictive value of triglyceride glucose-body mass index(TyG-BMI),serum triglyceride-to-high-density lipoprotein cholesterol ratio(TG/HDL-C),and metabolic score for insulin resistance(METS-IR)for fatty pancreatic disease(FPD).Methods A total of 240 patients with FPD treated in The First Affiliated Hospital of Zhengzhou University from January 2020 to November 2023 were included as the case group,while 480 healthy subjects who underwent healthy checks in the same period were randomly selected as the control group.General clinical data and laboratory indicators were collected.The Mann-Whitney U test and chi-square test were used to compare non-normally distributed continuous variables,and categorical variables between groups,respectively.A binary logistic regression model was used to assess the relationship between TyG-BMI,TG/HDL-C,and METS-IR and FPD.The receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate the predictive diagnostic value of those simplified insulin resistance indicators for FPD in the general population and different sex populations.Results Age,BMI,systolic blood pressure,diastolic blood pressure,fasting plasma glucose,uric acid,alanine aminotransferase,aspartate aminotransferase,gamma-glutamyl transferase,total cholesterol,triglyceride,low-density lipoprotein cholesterol,TyG-BMI,TG/HDL-C,and METS-IR in the case group were significantly higher than those in the control group(all P<0.05).The case group had significantly higher proportions of individuals with hypertension,diabetes,and fatty liver disease than the control group(all P<0.05).The high-density lipoprotein cholesterol level was significantly lower in the case group than in the control group(P<0.05).The multivariable Logistic regression analysis showed that after adjusting for various influencing factors,TyG-BMI,TG/HDL-C,and METS-IR remained as independent risk factors for the development of FPD,with the odds ratios(95%confidence intervals)being 1.027(1.018-1.037),6.964(2.022-23.989),and 1.184(1.123-1.248),respectively.In the ROC curve analysis,the AUCs of METS-IR and TyG-BMI were 0.823 and 0.803,respectively,with their sensitivities being 76.3%and 75.8%,specificities being 74.6%and 71.7%,and optimal cut-off values being 34.86 and 196.70,respectively;the next were BMI(AUC=0.758)and TG/HDL-C(AUC=0.734);in the sex-stratified analysis,the AUC values of METS-IR were highest in both the male and female subgroups,which were 0.834 and 0.810,respectively.Conclusion TyG-BMI,TG/HDL-C,and METS-IR show good predictive value for the development of FPD,in which METS-IR is more excellent.

Objective·To develop an early diagnostic model for small cell lung cancer(SCLC)based on differences in serum metabolite expression profiles between patients with SCLC and those with benign pulmonary diseases,using machine learning algorithms.Methods·Serum samples were collected from 29 SCLC patients and 67 patients with benign lung diseases at Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine,as the training cohort.An independent external validation cohort included 20 SCLC patients and 40 patients with benign lung diseases from Gansu Provincial Cancer Hospital.A total of 69 serum metabolites were quantitatively analyzed using liquid chromatography-tandem mass spectrometry(LC-MS/MS).The XGBoost Classifier was employed to rank metabolite importance,and a forward feature selection strategy based on XGBoost was used to identify a subset of key metabolites.Diagnostic models were constructed using AdaBoost,random forest(RF),and light gradient boosting machine(LGBM)algorithms.Model performance was assessed using receiver operating characteristic(ROC)curves and the area under the curve(AUC),and validated on the external test cohort.Results·Principal component analysis(PCA)and orthogonal projections to latent structures-discriminant analysis(OPLS-DA)of the training cohort revealed distinct metabolic profiles between SCLC and benign lung disease patients.Based on feature importance rankings,six key metabolites were selected to construct the MTB-6 diagnostic model.Among the models,AdaBoost achieved the best performance,with an AUC of 0.943,sensitivity of 75.0%,and specificity of 90.9%in the training cohort.In the external test cohort,the model demonstrated robust performance with an AUC of 0.921,sensitivity of 80.0%,and specificity of 87.5%.Conclusion·The MTB-6 model,based on six serum metabolites and the AdaBoost algorithm,exhibits excellent diagnostic performance and holds potential for the differential diagnosis of SCLC and benign pulmonary diseases.

Objective To explore the pharmaceutical care clinical pharmacists provide for anti-infective therapy in patients undergoing continuous renal replacement therapy(CRRT)after lung transplantation.Methods The clinical pharmacist utilized a limited sampling strategy and participated in the entire anti-infective treatment process for an adult lung transplant recipient based on pharmacokinetic monitoring results.The CRRT duration was flexibly adjusted,the dosing regimen was optimized,and adverse drug reactions were monitored.Result The clinical pharmacist assisted the physician in optimizing the polymyxin B anti-infective therapy post-transplantation,leading to successful infection control and patient discharge.Conclusion Clinical pharmacists can conduct real-time drug concentration monitoring in lung transplant patients based on pharmacokinetic characteristics,develop individualized dosing regimens,and improve medication safety and efficacy during anti-infective therapy.

Objective:To evaluate the association between postoperative delirium (POD) and preoperative frailty in elderly patients undergoing knee or hip arthroplasty.Methods:This nested case-control study utilized medical records from elderly patients who underwent knee or hip arthroplasty under combined spinal-epidural anesthesia at Qingdao Municipal Hospital between September 2021 and May 2023. Participants were divided into 2 groups based on clinically diagnosed POD: POD group ( n=53) and non-POD group ( n=256). Univariate analysis was conducted on suspected influencing factors, and logistic regression analysis was utilized to identify the risk factors for POD. Receiver operating characteristic and clinical decision curves were plotted to evaluate the predictive performance of these risk factors for POD. Mediation analysis was performed, and a clinically applicable nomogram was constructed to achieve visual prediction of outcomes. Results:There were statistically significant differences in age, preoperative frailty, body mass index, American Society of Anesthesiologists Physical Status classification, Memorial Delirium Assessment Scale scores, and concentrations of Aβ 42, Aβ 40, phosphorylated tau protein (p-tau protein) and tau protein, Aβ 42/tau ratio and Aβ 42/p-tau ratio in cerebrospinal fluid (CSF) between non-POD group and POD group ( P<0.05). Preoperative frailty was a risk factor for POD ( P<0.05). Mediation analysis revealed that the association between preoperative frailty and POD was mediated by CSF tau protein concentrations. The area under the receiver operating characteristic curve of preoperative frailty and CSF biomarker concentrations in predicting POD was 0.974 ( P<0.05). The clinical decision curve demonstrated that the model combining the preoperative frailty and CSF biomarker concentrations predicted a higher net benefit ( P<0.05). The clinical decision curve showed that the model combining preoperative frailty and CSF biomarker concentrations predicted a higher net benefit. Conclusions:Preoperative frailty is a risk factor for POD in elderly patients undergoing knee or hip arthroplasty, and its combination with CSF biomarker concentrations can effectively predict the occurrence of POD. CSF tau concentration mediates the association between preoperative frailty and development of POD.

Objective:To evaluate the association between the preoperative aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio and postoperative delirium (POD) in patients undergoing total knee/hip arthroplasty.Methods:In this nested case-control study, medical records from patients, aged ≥55 yr, of American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ, with Mini-Mental State Examination (MMSE) scale score >24 on preoperative day 1, scheduled for elective total knee/hip arthroplasty under combined spinal-epidural anesthesia at Qingdao Municipal Hospital between November 2021 and December 2023, were collected. POD was assessed using the Confusion Assessment Method. Patients were categorized into POD and non-POD groups based on the occurrence of POD. Logistic regression was employed to identify protective and risk factors for POD. The predictive performance of preoperative AST/ALT ratio alone and its combination with cerebrospinal fluid (CSF) biomarker concentrations for POD was evaluated using receiver operating characteristic curves, and the clinical utility of the prediction models was assessed using decision curve analysis. Mediation analysis was conducted to examine the mediation role of CSF biomarkers in the relationship between the preoperative AST/ALT ratio and POD. Restricted cubic splines were used to assess the nonlinear relationship between the preoperative AST/ALT ratio and POD.Results:A total of 460 patients were finally included, with 49 in POD group and 411 in non-POD group. After adjustment for multiple confounding factors including age, sex, educational level, MMSE score, history of hypertension, history of diabetes, history of smoking and history of alcohol use, multivariable logistic regression identified that the higher preoperative AST/ALT ratio, CSF total tau protein (t-tau) and phosphorylated tau protein (p-tau) concentrations were independent risk factors for POD, whereas lower CSF β-amyloid 42 (Aβ 42) concentration, Aβ 42/t-tau ratio and Aβ 42/p-tau ratio served as protective factors ( P<0.05). The area under the receiver operating characteristic curve of the preoperative AST/ALT ratio combined with CSF biomarkers in predicting POD was 0.939 ( P<0.001), demonstrating high clinical efficacy. After adjusting for age, educational level, sex, MMSE score, history of hypertension, history of diabetes, history of smoking, history of alcohol use and body mass index, restricted cubic splines revealed a nonlinear relationship between preoperative AST/ALT levels and the probability of POD, and the probability of POD increased with rising ratios when the preoperative AST/ALT ratio ranged from 1.09 to 1.40 ( Poverall < 0.05, Pnonlinear <0.05). After stratification by sex, the preoperative AST/ALT ratio demonstrated a linear relationship with the probability of POD ( Poverall <0.05, Pnonlinear>0.05). Mediation analysis indicated that the relationship between the preoperative AST/ALT ratio and POD was partially mediated by CSF p-tau concentration (proportion mediated 18.1%), CSF t-tau concentration (proportion mediated 12.0%), and the Aβ 42/t-tau ratio (proportion mediated 15.4%). Conclusions:A higher preoperative AST/ALT ratio is an independent risk factor for POD in total knee/hip arthroplasty patients. The concentrations of CSF t-tau and p-tau and Aβ 42/t-tau ratio have a mediating role in the relationship between the preoperative AST/ALT ratio and POD.

Neuroimaging plays a vital role in researching the pathological mechanism of psychiatric disorders. Magnetoencephalography (MEG) non-invasively records the weak magnetic fields generated by neuronal activity, detecting spontaneous brain activity and magnetic responses evoked by auditory, visual, and other stimuli. It offers high temporal and spatial resolution. This article mainly reviews the applications of MEG in psychiatric disorders such as Alzheimer′s disease, schizophrenia, depression, etc., to provide new insights for exploring the pathophysiological mechanism of psychiatric disorders.

Objective To investigate the pharmacokinetic(PK)profile of ripretinib in patients with advanced gastrointestinal stromal tumors(GISTs)in real-world settings.Methods The PK data of eight advanced GIST patients treated with ripretinib and the steady-state trough concentration(Cmin)blood samples of 54 advanced GIST patients treated with ripretinib were collected from November 2023 to March 2025 at the First Affiliated Hospital of Sun Yat-sen University.A validated liquid chromatography-tandem mass spectrometry method was used to quantify ripretinib and DP-5439 concentrations.The PK profiles of ripretinib were characterized.Cmin was compared across various dosages.The correlations among PK parameters of ripretinib and DP-5439,and clinical features impacting PK were explored.Results All patients reached Cmin approximately 24 hours post-dose for ripretinib and DP-5439.The median time to maximum con-centration(Tmax)for both ripretinib and DP-5439 was 3.16 hours.The steady-state Cmin,maximum plasma concentration(Cmax),and area under the plasma concentration-time curve from 0 to 24 hours(AUC0-24 h)of ripretinib,DP-5439,and their combined total were found to be highly correlated(all r>0.85,all P<0.05).In patients receiving 150 mg once-daily(n=44),the median Cmin(range)was 381.66(40.90-1 045.48)ng/mL for ripretinib,589.08(25.28-1 168.11)ng/mL for DP-5439,and 998.00(66.18～2 381.48)ng/mL for total,with coeffi-cients of variation(CVs)of 59.4%,57.2%,and 53.6%.In the 300 mg group(n=11),the median Cmin(range)was 1 024.51(251.36-2 030.51)ng/mL for ripretinib,1 122.34(111.54-2 682.57)ng/mL for DP-5439,and 1 924.58(404.37-4 766.08)ng/mL for total,with CVs of 59.5%,57.3%,and 54.8%.Univariate analysis showed that no significant correlation was found between age or BMI and the dose-corrected Cmin of ripretinib and DP-5439(all P>0.05),and the median dose-corrected Cmin of ripretinib and DP-5439 was slightly lower in male patients than in female patients(P<0.05).In the multiple linear regression analysis,male patients were observed to have a lower median dose-cor-rected Cmin of DP-5439 than female patients(P=0.024),but no statistical difference was found in that of ripretinib(P>0.05).Conclusions In advanced GIST patients receiving ripretinib,ripretinib and DP-5439 reached Cmin 24 hours post-dose,just before the next administra-tion.The ripretinib,DP-5439,and total Cmin showed significant correlations with their AUC0-24 h,which indicated that Cmin could serve as an indicator of ripretinib exposure.The PK features of ripretinib in advanced GIST patients exhibit significant inter-individual variability.

Objective To investigate the pharmacokinetic(PK)profile of ripretinib in patients with advanced gastrointestinal stromal tumors(GISTs)in real-world settings.Methods The PK data of eight advanced GIST patients treated with ripretinib and the steady-state trough concentration(Cmin)blood samples of 54 advanced GIST patients treated with ripretinib were collected from November 2023 to March 2025 at the First Affiliated Hospital of Sun Yat-sen University.A validated liquid chromatography-tandem mass spectrometry method was used to quantify ripretinib and DP-5439 concentrations.The PK profiles of ripretinib were characterized.Cmin was compared across various dosages.The correlations among PK parameters of ripretinib and DP-5439,and clinical features impacting PK were explored.Results All patients reached Cmin approximately 24 hours post-dose for ripretinib and DP-5439.The median time to maximum con-centration(Tmax)for both ripretinib and DP-5439 was 3.16 hours.The steady-state Cmin,maximum plasma concentration(Cmax),and area under the plasma concentration-time curve from 0 to 24 hours(AUC0-24 h)of ripretinib,DP-5439,and their combined total were found to be highly correlated(all r>0.85,all P<0.05).In patients receiving 150 mg once-daily(n=44),the median Cmin(range)was 381.66(40.90-1 045.48)ng/mL for ripretinib,589.08(25.28-1 168.11)ng/mL for DP-5439,and 998.00(66.18～2 381.48)ng/mL for total,with coeffi-cients of variation(CVs)of 59.4%,57.2%,and 53.6%.In the 300 mg group(n=11),the median Cmin(range)was 1 024.51(251.36-2 030.51)ng/mL for ripretinib,1 122.34(111.54-2 682.57)ng/mL for DP-5439,and 1 924.58(404.37-4 766.08)ng/mL for total,with CVs of 59.5%,57.3%,and 54.8%.Univariate analysis showed that no significant correlation was found between age or BMI and the dose-corrected Cmin of ripretinib and DP-5439(all P>0.05),and the median dose-corrected Cmin of ripretinib and DP-5439 was slightly lower in male patients than in female patients(P<0.05).In the multiple linear regression analysis,male patients were observed to have a lower median dose-cor-rected Cmin of DP-5439 than female patients(P=0.024),but no statistical difference was found in that of ripretinib(P>0.05).Conclusions In advanced GIST patients receiving ripretinib,ripretinib and DP-5439 reached Cmin 24 hours post-dose,just before the next administra-tion.The ripretinib,DP-5439,and total Cmin showed significant correlations with their AUC0-24 h,which indicated that Cmin could serve as an indicator of ripretinib exposure.The PK features of ripretinib in advanced GIST patients exhibit significant inter-individual variability.