Narrative will represents an emerging concept in the context of population aging. Guided by life value orientation and premised on respecting individuals’ wishes and needs， it presents individuals’ unique life stories through narrative form. It conveys the holistic experience， meaning interpretation， and life understanding of the experienced events. Preserved and transmitted in a manner that aligns with individuals’ expectations， it also facilitates human beings’ pursuit， reflection， and growth in life meaning through interpersonal interactions that transcend space and time. This paper comprehensively introduced the essence of narrative wills by reviewing their conceptual evolution， connotation attributes， value manifestation， implementation paths， and specific case analysis， aiming to provide a reference for their implementation.

ObjectiveTo explore the pathological mechanism-syndrome-treatment patterns of approved Chinese patent medicines （CPMs） that treat collateral disorders， providing a reference for the principle of "treating different diseases with the same therapy" in collateral pathology. MethodsCPMs that apply treatment strategies based on collateral disorders were identified from the Pharmacodia database by extracting information from the "efficacy" or "indications" sections of drug package inserts. A database was established to extract the names and compositions of the CPMs， as well as their indications， related traditional Chinese medicine （TCM） symptoms， disease locations （affected areas）， and pathological factors. Frequency statistics were performed. Using the Apriori algorithm， an association rule analysis was conducted on CPMs and disease-location combinations related to the top three most frequent pathological factor combinations. Core formulas for these combinations were identified and analyzed through drug network analysis and MCODE module clustering. ResultsA total of 660 CPMs targeting collateral disorders were retrieved， involving 299 indications， 323 TCM symptoms， 21 disease locations， 19 pathological factors， and 124 pathological factor combinations. The most frequent pathological factor combinations were blood stasis （involved in 109 CPMs， 16.52%）， exogenous wind （外风） -cold-dampness （involved in 43 CPMs， 6.52%）， and qi deficiency-blood stasis （involved in 42 CPMs， 6.36%）. Analysis of the core formulas for these combinations revealed common ingredients such as Honghua （Carthami Flos）， Chuanxiong （Chuanxiong Rhizoma）， Danggui （Angelicae Sinensis Radix）， and Dilong （Pheretima）. ConclusionCollateral disorders involve a wide range of pathogenesis and represent a fundamental mechanism in the onset and development of various diseases， characterized by obstruction and stagnation. The primary therapeutic principle is unblocking of the collaterals. Blood stasis obstructing the collaterals is the core pathological basis， and the strategy of activating blood circulation and resolving stasis to unblock the collaterals should be central to the treatment. The core medication pattern involves combining blood-activating and stasis-resolving herbs with insect-derived medicinals that unblock collaterals. Exogenous wind is often the initiating patholo-gical factor in colla-teral disorders， and the appropriate addition of wind-dispelling herbs can enrich the treatment strategies for such conditions.

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

OBJECTIVES: Depressive and anxiety disorders are among the most common mental disorders worldwide and are associated with unhealthy lifestyle behaviors. The Life's Simple 7 (LS7) guideline proposed by the American Heart Association aims to reduce cardiovascular risk by improving behaviors such as diet and physical activity, but its impact on mental health is not yet fully clear. This study examined the association between LS7 scores and symptoms of anxiety and depression in adults undergoing routine health examinations. METHODS: Data were collected from individuals who underwent health examinations from May 2015 to December 2024 at the Health Management Center of the Third Xiangya Hospital. All participants completed the LS7 assessments, the Self-Rating Depression Scale (SDS), and the Self-Rating Anxiety Scale (SAS). Participants were categorized into 4 LS7 score groups: Low (≤7), average (8-9), good (10), and excellent (11-14). Those with SDS or SAS≥50 were classified as having mental disorder symptoms; with this group, SAS≥50 indicated anxiety, SDS≥50 indicated depression, and SDS and SAS≥50 indicated comorbid anxiety-depression. Binary logistic regression was used to assess associations between LS7 score and mental symptoms, calculating odds ratio (OR) and 95% confidence interval (CI). A restricted cubic spline (RCS) regression model was used to analyze the dose-response relationship between LS7 score (continuous variable) and the risk of mental symptoms. Nodes were set at the 5th, 35th, 65th, and 95th percentiles of the LS7 score, with the 5th percentile as the reference point. All models were adjusted for covariates such as gender, age, living alone, drinking status, education level, and sleep quality. Logistic regression framework was used to fit and calculate the adjusted OR (aOR) and 95% CI. Nonlinear relationship tests were also conducted. Subgroup analysis was performed to explore the interaction between gender, age, drinking habits, education level, and other factors and the LS7 score in influencing the risk of mental symptoms. RESULTS: A total of 5 449 participants were included; 1 363 (25.01%) had depressive symptoms, 398 (7.30%) had anxiety symptoms, and 259 (4.75%) had comorbid anxiety-depression. The prevalence of mental symptoms decreased significantly as LS7 scores increased. Univariate and multivariate Logistic regression indicated that LS7 score≥8 was protective against mental symptoms. Multivariate Logistic regression demonstrated moderate discriminative ability (AUC=0.672). Among individuals with anxiety, depression, or comorbid symptoms, LS7 score distributions showed a graded decrease from poor to excellent groups. After adjustment, an excellent LS7 score was associated with a 39% lower risk of depression (aOR=0.61, 95% CI 0.47 to 0.78, P<0.001), a 63% lower risk of anxiety (aOR=0.37, 95% CI 0.22 to 0.59, P<0.001), and a 66% lower risk of comorbid anxiety-depression (aOR=0.34, 95% CI 0.17 to 0.62, P=0.001). The AUC values of the anxiety model, depression model, and comorbid anxiety and depression model were 0.632, 0.672, and 0.619, respectively. All models demonstrated moderate discriminatory ability, which was statistically significant, but their capacity to distinguish cases from non-cases was limited. RCS analysis confirmed a linear inverse relationship between LS7 score and mental symptom risk. Not smoking and regular physical activity were the strongest protective behaviors. Subgroup analysis suggested stronger protective effects in men, younger adults (≤60), non-drinkers, and those with higher education levels, and revealed a significant interaction between alcohol use and LS7 score (P for interaction=0.021), indicating that alcohol consumption may weaken the protective effect of LS7. CONCLUSIONS Ideal healthy lifestyle behaviors, as reflected by higher LS7 scores, are associated with lower risks of anxiety and depression in adults. Promoting LS7-based lifestyle practices may serve as a practical and effective strategy for the prevention and management of anxiety and depression in both clinical and daily life settings.
Humans ; Cross-Sectional Studies ; Depression/epidemiology* ; Anxiety/epidemiology* ; Adult ; Male ; Female ; Middle Aged ; Healthy Lifestyle ; Risk Factors ; Anxiety Disorders/epidemiology* ; Exercise ; Physical Examination ; Aged

Acupuncture is an ancient treatment method used in traditional Chinese medicine and has been popularized worldwide. Over the past decade, there has been an increase in the amount of acupuncture research, mostly comprised of randomized controlled trials (RCTs) that aimed to answer the question on the efficacy of acupuncture. However, poor methodology and low replicability in these acupuncture RCTs have resulted in uncertainty about the efficacy of acupuncture. In this review, current advancements and challenges in acupuncture RCTs, regarding the methodological aspects of randomization, blinding, sham acupuncture and quality of reporting, were discussed. While there have been advancements in various aspects, current acupuncture RCTs still face pressing issues such as inadequate randomization and blinding, unviable sham acupuncture controls, and poor reporting quality. Given these limitations, this review seeks to identify the methodological problems that are responsible for these problems and to suggest solutions that could help to overcome them so as to improve the quality of future studies evaluating the efficacy of acupuncture. Please cite this article as: Seetoh WS, Lim RQR, Xu RB, Sun MX, Zhang P, Wang MN. Advancements and challenges of acupuncture randomized controlled trials. J Integr Med. 2025; 23(4): 333-343.
Acupuncture Therapy ; Humans ; Randomized Controlled Trials as Topic/methods* ; Research Design

Objective To analyze risk factors for poor postoperative wound healing in spinal tuberculo-sis patients and construct prediction models along with a risk scoring table using machine learning algorithms,providing references for early prevention and management.Methods Clinical data from 420 spinal tuberculo-sis patients treated at four tertiary hospitals in Guizhou Province between January 2017 and February 2024 were retrospectively analyzed.Risk factors were identified through univariate and multivariate analyses.Logis-tic regression,random forest,and support vector machine prediction models were constructed.Model perform-ance was evaluated using receiver operating characteristic(ROC)curves,precision,recall,accuracy,and F1-score.A risk prediction scoring table for poor postoperative wound healing was subsequently developed.Re-sults Among the 420 patients with spinal tuberculosis,132 experienced poor postoperative wound healing,with an incidence rate of 31.43%.Logistic regression analysis showed that BMI≤18.5 kg/m2,preoperative albumin≤30 g/L,combined surgical procedure,intraoperative blood loss>1 000 mL,direct bilirubin>8 μmol/L within 3 days after surgery,neutrophil count≤75×109/L within 3 days after surgery,and postopera-tive drainage volume>500 mL were risk factors for poor postoperative wound healing(P<0.05).In the comparison among the three risk prediction models constructed based on machine learning algorithms,the ran-dom forest model demonstrated the best predictive performance.A risk prediction scoring table was construc-ted based on the partial regression coefficients from the multivariate analysis,with a total score range from 0 to 11 points.A score>6 points indicated an increased risk of poor postoperative wound healing.The area un-der the ROC curve(AUC)for this risk prediction scoring table was 0.846(95%CI:0.769 to 0.923),indica-ting good predictive performance.Conclusion The random forest model based on machine learning algorithms and the risk prediction scoring table have certain predictive value for assessing the risk of poor postoperative wound healing in patients with spinal tuberculosis;they can assist healthcare professionals in early identifica-tion of high-risk patients.

Objective:To investigate the clinical application value of a novel filter's retraction hook capture technique of pull-assisted method for the endovascular retrieval of conical inferior vena cava (IVC) filters whose hook attached to the wall.Methods:From January 2020 to December 2024, patients with conical filters whose hook attached to the wall admitted at Beijing Jishuitan Hospital were enrolled consecutively.Results:A total of 46 patients underwent filter retrieval using filter's retraction hook capture technique of pull-assisted method. Among these patients, 39 cases (84.8%) were successful in filter retrieval, with the penetration distance of cranial anchor vertex of 3.3(2.5, 4.4) mm, and 13 (33.3%) filters were deformed. The other 7 cases were unsuccessful, with a penetration distance of cranial anchor vertex of 5.0 (4.3, 5.0) mm, and 6 (85.7%) filters were deformed. There was a statistically significant difference between the two groups ( P<0.05). One case (2.2%) had IVC injury, one case (2.2%) experienced filter fracture, and no symptomatic pulmonary embolism occurred. Logistic regression analysis showed that filter deformation was an independent dangerous factor for filter's retraction. Conclusions:Filter's retraction hook capture technique of pull-assisted method is effective in removing conical filters whose hook attached to the wall, with no symptomatic PE occurring. This method can be considered as a new adjuvant technique for filter retrieval.

Objective:To investigate the status quo of cognitive frailty in elderly patients with heart failure and analyze its influencing factors, so as to provide evidence for healthcare professionals to formulate effective intervention strategies.Methods:A total of 330 elderly patients with heart failure admitted to the First Affiliated Hospital of the University of South China and the Second Affiliated Hospital of the University of South China from October 2023 to January 2024 were selected as the study objects by convenience sampling method. General data questionnaire, Frailty Phenotype, Montreal Cognitive Assessment, Clinical Dementia Rating Scale, Geriatric Depression Scale-15 and Short Form Mini Nutritional Assessment were used for a sectional investigation. Random forest algorithm was used to rank the importance of variables and binary logistic regression was combined to explore the influencing factors of elderly patients with heart failure.Results:According to the evaluation criteria of cognitive frailty, 330 elderly patients with heart failure were divided into cognitive frailty group (124 cases) and non-cognitive frailty group (206 cases). The incidence of cognitive frailty was 37.6% (124/330). Among which, the median age of the cognitive frailty group was 73 years old, with 63 males and 61 females. The median age of the non-cognitive frailty group was 71 years old, with 117 males and 89 females. The random forest results showed that the top 7 variables in importance ranking were weekly intellectual activity, frequency of physical exercise, age, educational levels, depression status, cardiac function grade and risk of malnutrition. Binary logistic regression analysis showed that weekly intellectual activity ( OR=0.076, 95% CI 0.027-0.216), requency of physical exercise ( OR=0.184, 95% CI 0.079-0.430), age ( OR=1.173, 95% CI 1.077-1.277), educational levels ( OR=0.283, 95% CI 0.143-0.559), depression status ( OR=4.440, 95% CI 1.451-13.585), cardiac function grade ( OR=3.030, 95% CI 1.673-5.489) and risk of malnutrition ( OR=3.833, 95% CI 1.530-9.602) were the main influencing factors (all P<0.05). Conclusions:The incidence of cognitive frailty in elderly patients with heart failure is high. Healthcare professionals ought to focus on the screening and assessing of cognitive frailty in elderly patients with heart failure, and formulate effective intervention strategies by considering the above influencing factors to mitigate the occurrence of cognitive frailty.

Objective:To investigate the status quo of cognitive frailty in elderly patients with heart failure and analyze its influencing factors, so as to provide evidence for healthcare professionals to formulate effective intervention strategies.Methods:A total of 330 elderly patients with heart failure admitted to the First Affiliated Hospital of the University of South China and the Second Affiliated Hospital of the University of South China from October 2023 to January 2024 were selected as the study objects by convenience sampling method. General data questionnaire, Frailty Phenotype, Montreal Cognitive Assessment, Clinical Dementia Rating Scale, Geriatric Depression Scale-15 and Short Form Mini Nutritional Assessment were used for a sectional investigation. Random forest algorithm was used to rank the importance of variables and binary logistic regression was combined to explore the influencing factors of elderly patients with heart failure.Results:According to the evaluation criteria of cognitive frailty, 330 elderly patients with heart failure were divided into cognitive frailty group (124 cases) and non-cognitive frailty group (206 cases). The incidence of cognitive frailty was 37.6% (124/330). Among which, the median age of the cognitive frailty group was 73 years old, with 63 males and 61 females. The median age of the non-cognitive frailty group was 71 years old, with 117 males and 89 females. The random forest results showed that the top 7 variables in importance ranking were weekly intellectual activity, frequency of physical exercise, age, educational levels, depression status, cardiac function grade and risk of malnutrition. Binary logistic regression analysis showed that weekly intellectual activity ( OR=0.076, 95% CI 0.027-0.216), requency of physical exercise ( OR=0.184, 95% CI 0.079-0.430), age ( OR=1.173, 95% CI 1.077-1.277), educational levels ( OR=0.283, 95% CI 0.143-0.559), depression status ( OR=4.440, 95% CI 1.451-13.585), cardiac function grade ( OR=3.030, 95% CI 1.673-5.489) and risk of malnutrition ( OR=3.833, 95% CI 1.530-9.602) were the main influencing factors (all P<0.05). Conclusions:The incidence of cognitive frailty in elderly patients with heart failure is high. Healthcare professionals ought to focus on the screening and assessing of cognitive frailty in elderly patients with heart failure, and formulate effective intervention strategies by considering the above influencing factors to mitigate the occurrence of cognitive frailty.