Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

Objective:To analyze the preferences of medical staff in TCM hospitals in Beijing regarding the achievements transformation of hospital traditional Chinese medicine preparations,and to provide a reference for formulating incentive policies.Methods:233 medical staff from five TCM hospitals in Beijing were taken as the research objects,and surveyed with a questionnaire designed based on the discrete choice experiment(DCE).Mixed logit models and latent class models were then used to analyze their transformation preferences.Results:The mixed Logit model revealed that seven key attributes significantly influenced medical staff's preferences for the achievements transformation of traditional Chinese medicine preparations(P<0.05).Latent class analysis identified three distinct preference groups among respondents:an organization-dependent group(27.0%),a pro-transformation group(61.4%),and a conservative group(11.6%).Conclusions:Medical Staff preferred transformation conditions that increased monthly income;utilized"human use+re-experimentation";involved the hospital's achievements transformation department as the entity;were funded by the hospital;offered a 70%profit share;enabled promotion three years earlier,and assigned patents to the hospital.The study recommends implementing diverse incentive measures and developing differentiated strategies tailored to the distinct Medical Staff categories to facilitate the transformation of hospital traditional Chinese medicine preparations into new drugs.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Purpose To investigate the clinicopathological features,differential diagnosis and prognosis of atypical fibroxanthoma(AFX).Methods Pathological features of 15 cases of AFX and 3 cases of pleomorphic dermal sarcoma(PDS)misdiagnosed as AFX were retrospectively analyzed by hematoxylin and eosin staining and immunohistochemical EnVision staining technology.Clinical information was collected and analyzed,and the relevant literatures were re-viewed.Results The age of the 15 patients with AFX ranged from 18 to 78 years,with an average age of 57 years.4 cases occurred in the head and neck,and 11 cases occurred in the trunk and limbs.3 patients with PDS misdiagnosed as AFX were aged from 56 to 60 years,with an average age of 58 years.The tumors were located in the trunk and limbs.Microscopically,15 cases of AFX and 3 cases of PDS misdiagnosed as AFX were composed of proliferative pleo-morphic and atypical spindle cells interspersed with a varying number of multinucleated cells.15 cases of AFX tumors were superficial and located in the dermis.In 3 cases of PDS misdiagnosed as AFX,1 case was located in subcutane-ous adipose tissue,1 case had superficial subcutaneous extension,and the third case had positive basal margin.Immu-nohistochemically,the immunophenotypes of the two groups were consistent.CD10 was expressed in all cases,CD68 was positive in most cases,SMA was expressed in a few cases,desmin was focal expressed in a very few cases,and S-100,SOX10,CD34,HMB-45,Melan A,STAT6 and CK(AE1/AE3)were not expressed in all cases.Ki67 prolifera-tion index ranged from 2％to 30％.15 patients with AFX were followed up from 12 to 108 months.One patient had tumor recurrence 1 year and 3 years after operation due to positive basal margin.Most of the other patients underwent extended resection after diagnosis and were in good condition without tumor recurrence and metastasis.3 cases of PDS misdiagnosed as AFX were followed up for 31 to 78 months.One patient had lung metastasis after 2 years,one patient recurred 4 times after operation,and the other patient died after 4 times of recurrence.Conclusion AFX is a rare dis-ease with similar pathological characteristics and immunophenotype to PDS.AFX can be diagnosed only when the tumor is small and completely confined to the dermis.When the maximum diameter of the tumor is more than 3 cm,or the presence of any form of subcutaneous extension requires a high level of vigilance for PDS.Careful differentiation and correct classification of AFX and PDS are very important for the treatment and prognosis of the disease.

Objective:To analyze the preferences of medical staff in TCM hospitals in Beijing regarding the achievements transformation of hospital traditional Chinese medicine preparations,and to provide a reference for formulating incentive policies.Methods:233 medical staff from five TCM hospitals in Beijing were taken as the research objects,and surveyed with a questionnaire designed based on the discrete choice experiment(DCE).Mixed logit models and latent class models were then used to analyze their transformation preferences.Results:The mixed Logit model revealed that seven key attributes significantly influenced medical staff's preferences for the achievements transformation of traditional Chinese medicine preparations(P<0.05).Latent class analysis identified three distinct preference groups among respondents:an organization-dependent group(27.0%),a pro-transformation group(61.4%),and a conservative group(11.6%).Conclusions:Medical Staff preferred transformation conditions that increased monthly income;utilized"human use+re-experimentation";involved the hospital's achievements transformation department as the entity;were funded by the hospital;offered a 70%profit share;enabled promotion three years earlier,and assigned patents to the hospital.The study recommends implementing diverse incentive measures and developing differentiated strategies tailored to the distinct Medical Staff categories to facilitate the transformation of hospital traditional Chinese medicine preparations into new drugs.

Objective: To explore the correlation between the composition of bone marrow lymphocyte subsets and the clinical attributes observed in de novo AML patients, as well as their influence on prognosis. Methods: A detailed study was carried out on a cohort of 191 de novo acute myeloid leukemia patients who were admitted to our medical center between October 2022 and September 2024. In addition, a group of 24 patients with iron deficiency anemia individuals was carefully chosen as the control cohort. The proportions of lymphocyte subsets within the bone marrow of de novo AML patients were analyzed. Furthermore, an in-depth analysis was performed to investigate the association between the expression levels of these subsets in de novo AML patients and their clinical attributes, as well as their prognostic implications. Results: The proportion of CD19 and CD56 lymphocytes within the bone marrow of de novo AML patients significantly diminished compared to the control cohort (8.5% vs 13.2% P<0.05, and 15.5% vs 18.0%, P<0.05). Conversely, no significant discrepancies were observed in the CD3 , CD3 CD4 , and CD3 CD8 lymphocyte percentages between the AML patients and control group (71.7% vs 72.1%, 32.5% vs 33.7% and 32.8% vs 35.7%, P>0.05). When analyzing the relationships between lymphocyte subsets within the bone marrow of de novo patients and their respective clinical characteristics, patients aged 60 years and above exhibited diminished percentages of CD3 CD8 lymphocytes in the bone marrow compared to their younger counterparts (31.6% vs 34.1%, P<0.05), while the CD56 lymphocyte subsets demonstrated an increased prevalence (17.2% vs 14.4%, P<0.05). Furthermore, patients with leukocytosis (WBC≥100×10 /L) presented lower levels of CD3 and CD3 CD4 lymphocytes in the bone marrow compared with those without it (65.3% vs 72.9% P<0.05, and 28.9% vs 33.2%, P<0.05), respectively. The AML1-ETO fusion gene-positive cohort exhibited a higher prevalence of CD3 CD8 lymphocytes in the bone marrow than in the negative group (38.2% vs 32.3%, P<0.05), whereas the FLT3-ITD mutation-positive group presented a decreased prevalence of CD56 lymphocytes compared with the negative group (12.4% vs 16.8%, P<0.05). In addition, the NPM1 mutation-positive group demonstrated lower levels of CD3 CD8 lymphocytes in the bone marrow than in the negative group (29.1% vs 33.3%, P<0.05). Variables such as tumor protein p53(TP53) mutation positive, the absence of hematopoietic stem cell transplantation, and CD3 CD4 lymphocyte proportions below 25% were identified as independent adverse prognostic indicators for AML patients (P<0.05). Conclusion: The pathogenesis of AML is closely associated with an imbalance in bone marrow lymphocyte subsets. The FLT3-ITD mutation potentially contributes to the dysregulation of CD56 lymphocyte subset expression. The AML1-ETO fusion gene and NPM1 mutation are implicated in the abnormal expression of CD3 CD8 lymphocytes within the bone marrow. Moreover, the percentage of CD3 CD4 lymphocytes in the bone marrow serves as a prognostic factor for de novo AML patients.

Objective: To explore the correlation between the composition of bone marrow lymphocyte subsets and the clinical attributes observed in de novo AML patients, as well as their influence on prognosis. Methods: A detailed study was carried out on a cohort of 191 de novo acute myeloid leukemia patients who were admitted to our medical center between October 2022 and September 2024. In addition, a group of 24 patients with iron deficiency anemia individuals was carefully chosen as the control cohort. The proportions of lymphocyte subsets within the bone marrow of de novo AML patients were analyzed. Furthermore, an in-depth analysis was performed to investigate the association between the expression levels of these subsets in de novo AML patients and their clinical attributes, as well as their prognostic implications. Results: The proportion of CD19 and CD56 lymphocytes within the bone marrow of de novo AML patients significantly diminished compared to the control cohort (8.5% vs 13.2% P<0.05, and 15.5% vs 18.0%, P<0.05). Conversely, no significant discrepancies were observed in the CD3 , CD3 CD4 , and CD3 CD8 lymphocyte percentages between the AML patients and control group (71.7% vs 72.1%, 32.5% vs 33.7% and 32.8% vs 35.7%, P>0.05). When analyzing the relationships between lymphocyte subsets within the bone marrow of de novo patients and their respective clinical characteristics, patients aged 60 years and above exhibited diminished percentages of CD3 CD8 lymphocytes in the bone marrow compared to their younger counterparts (31.6% vs 34.1%, P<0.05), while the CD56 lymphocyte subsets demonstrated an increased prevalence (17.2% vs 14.4%, P<0.05). Furthermore, patients with leukocytosis (WBC≥100×10 /L) presented lower levels of CD3 and CD3 CD4 lymphocytes in the bone marrow compared with those without it (65.3% vs 72.9% P<0.05, and 28.9% vs 33.2%, P<0.05), respectively. The AML1-ETO fusion gene-positive cohort exhibited a higher prevalence of CD3 CD8 lymphocytes in the bone marrow than in the negative group (38.2% vs 32.3%, P<0.05), whereas the FLT3-ITD mutation-positive group presented a decreased prevalence of CD56 lymphocytes compared with the negative group (12.4% vs 16.8%, P<0.05). In addition, the NPM1 mutation-positive group demonstrated lower levels of CD3 CD8 lymphocytes in the bone marrow than in the negative group (29.1% vs 33.3%, P<0.05). Variables such as tumor protein p53(TP53) mutation positive, the absence of hematopoietic stem cell transplantation, and CD3 CD4 lymphocyte proportions below 25% were identified as independent adverse prognostic indicators for AML patients (P<0.05). Conclusion: The pathogenesis of AML is closely associated with an imbalance in bone marrow lymphocyte subsets. The FLT3-ITD mutation potentially contributes to the dysregulation of CD56 lymphocyte subset expression. The AML1-ETO fusion gene and NPM1 mutation are implicated in the abnormal expression of CD3 CD8 lymphocytes within the bone marrow. Moreover, the percentage of CD3 CD4 lymphocytes in the bone marrow serves as a prognostic factor for de novo AML patients.

Objective To compare the long-term survival of elderly patients with esophageal squamous cell carcinoma (ESCC) treated with surgical versus non-surgical treatment. Methods A retrospective analysis was conducted on the clinical data of elderly patients aged ≥70 years with ESCC who underwent esophagectomy or radiotherapy/chemotherapy at Sichuan Cancer Hospital from January 2009 to September 2017. Patients were divided into a surgical group (S group) and a non-surgical group (NS group) according to the treatment method. The propensity score matching method was used to match the two groups of patients at a ratio of 1∶1, and the survival of the two groups before and after matching was analyzed. Results A total of 726 elderly patients with ESCC were included, including 552 males and 174 females, with 651 patients aged ≥70-80 years and 75 patients aged ≥80-90 years. There were 515 patients in the S group and 211 patients in the NS group. The median follow-up time was 60.8 months, and the median overall survival of the S group was 41.9 months [95%CI (35.2, 48.5)], while that of the NS group was only 24.0 months [95%CI (19.8, 28.3)]. The 1-, 3-, and 5-year overall survival rates of the S group were 84%, 54%, and 40%, respectively, while those of the NS group were 72%, 40%, and 30%, respectively [HR=0.689, 95%CI (0.559, 0.849), P<0.001]. After matching, 138 patients were included in each group, and there was no statistical difference in the overall survival between the two groups [HR=0.871, 95%CI (0.649, 1.167), P=0.352]. Conclusion Compared with conservative treatment, there is no significant difference in the long-term survival of elderly patients aged ≥70 years who undergo esophagectomy for ESCC. Neoadjuvant therapy combined with surgery is still an important choice to potentially improve the survival of elderly patients with ESCC.

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic