To investigate the medication adherence trajectory during the intensive phase in patients with drug-resistant tuberculosis(DR-TB) and to analyze its influencing factors.

Patients with DR-TB treated at the Public Health Clinical Center of Chengdu city from March to December 2024 were selected as the study subjects by a convenience sampling method.Medication adherence was assessed using the Morisky Medication Adherence Scale(MMAS-8) at the beginning of treatment,3 months of treatment,and 6 months of treatment.The latent class growth model(LCGM) was used to analyze medication adherence trajectories.Multivariate Logistic regression analysis was used to explore the influencing factors of different trajectories.

A total of 179 patients with DR-TB completed follow-up.Their MMAS-8 scores at the beginning of treatment,3 months of treatment,and 6 months of treatment were 6.07±1.72,5.92±1.75,and 6.01±1.69,respectively.There were no statistically significant differences across the three time points(P>0.05).Two medication adherence trajectories were identified among patients with DR-TB,namely the improving medication adherence group(56.425%) and the declining medication adherence group(43.575%).Logistic regression analysis showed that average monthly income,place of residence,educational level,category of systemic adverse reactions,presence of other chronic diseases,self-efficacy,social support,and self-management ability were influencing factors for the medication adherence trajectory during the intensive phase in patients with DR-TB(all P<0.05).

Medication adherence during the intensive phase in patients with DR-TB was at a moderate level and exhibited population heterogeneity.Healthcare providers should pay attention to patients with declining medication adherence and develop personalized nursing measures based on the influencing factors to improve patient medication adherence.

To explore the dose-response relationship between hypothermia risk scores and the risk of concurrent trauma-induced coagulopathy(TIC) in emergency trauma patients.

A total of 220 emergency trauma patients admitted to our hospital from April 2023 to December 2024 were selected as the study subjects.They were divided into a TIC group and a non-TIC group based on the concurrent TIC condition.Univariate and multivariate Logistic regression analyses were used to explore the influencing factors of concurrent TIC in emergency trauma patients.The impact of the hypothermia risk score on concurrent TIC was analyzed after adjusting for different covariates.Restricted cubic spline(RCS) and threshold effect analyses were employed to investigate the dose-response relationship between the hypothermia risk score and the risk of concurrent TIC.

Among the 220 emergency trauma patients,42 developed TIC,resulting in an incidence of 19.09%. The hypothermia risk scores were 24.31±8.27.The hypothermia risk score was significantly higher in the TIC group than that in the non-TIC group(P=0.012). Multivariate Logistic regression analysis showed that the hypothermia risk score and admission hemoglobin level were influencing factors of concurrent TIC in emergency trauma patients(both P<0.05).After adjusting for covariates,the hypothermia risk score remained associated with concurrent TIC in emergency trauma patients(P=0.046).The RCS curve indicated a nonlinear dose-response relationship between the hypothermia risk score and concurrent TIC after adjusting for covariates(P_{for overall}=0.002,P_{for nonlinear}=0.023).The threshold effect analysis revealed a threshold effect between the hypothermia risk score and concurrent TIC(P_{for likelihood ratio test}=0.007).When the hypothermia risk score was≥25,each one-point increased in the score was associated with a 0.170-fold increase in the risk of concurrent TIC.Subgroup analysis showed that the relationship between the hypothermia risk score and concurrent TIC was not significantly influenced by gender,age,body mass index,hypertension,diabetes,or hyperlipidemia(all P_{for interaction}>0.05).

There exists a nonlinear dose-response relationship between the hypothermia risk score and concurrent TIC in emergency trauma patients.When the hypothermia risk score is ≥25,the risk of concurrent TIC increases with higher scores.

To explore the development trajectories of pain catastrophizing in elderly lung cancer patients with chronic pain undergoing chemotherapy,to analyze influencing factors,and to compare differences in physical activity among patients in different trajectory categories.

A total of 213 elderly lung cancer patients with chronic pain undergoing chemotherapy in Jiangsu Provincial People's Hospital were selected as research subjects from January 2022 to February 2024.Pain catastrophizing levels of patients were surveyed before chemotherapy initiation,during the mid-phase of chemotherapy,at the end of chemotherapy,and one month after chemotherapy completion.Group-based trajectory modeling was used to identify categories of pain catastrophizing trajectories.Logistic regression analysis was employed to explore influencing factors for different trajectory categories.Physical activity levels were compared among patients in different trajectory categories.

Model fitting ultimately identified three categories of pain catastrophizing trajectories,namely the low pain catastrophizing group,the moderate pain catastrophizing stable group,and the high pain catastrophizing increasing group.Logistic regression analysis showed that age,pain intensity,duration of persistent pain,personality traits, anxiety or depression,and family support were influencing factors for pain catastrophizing trajectory categories in elderly lung cancer patients with chronic pain undergoing chemotherapy (P<0.05). Comparisons of physical activity scores among patients in different pain catastrophizing trajectory categories showed statistically significant differences(P<0.05).

Elderly lung cancer patients with chronic pain undergoing chemotherapy exhibit three categories of pain catastrophizing trajectories.Healthcare professionals can develop and implement intervention plans based on the influencing factors of pain catastrophizing trajectories of patients to reduce their levels of pain catastrophizing.

To investigate the relationship between different types of cardiovascular disease and transitions in cognitive frailty states.

Data from the 2010—2014 Health and Retirement Study (HRS) in the United States and the 2011-2015 China Health and Retirement Longitudinal Study(CHARLS) were selected as data sources. A multi-state Markov model was employed to examine the impact of cardiovascular disease on cognitive frailty transitions.

Among patients with cardiovascular disease,the incidence rates of cognitive frailty,frailty,and cognitive impairment were 2.5%,8.6%,and 16.2%,respectively.A total of 5 990 state transitions were observed,of which deteriorations accounted for 60.2% and improvements accounted for 39.8%.Patients with multimorbid cardiovascular disease were more likely to transition from a normal state to physical frailty and were less likely to recover from deteriorated states compared to those with a single condition.Hypertensive patients demonstrated a higher likelihood of recovery from deteriorated states.

The relationships between different types of cardiovascular disease and transitions in cognitive frailty states vary.Healthcare providers should pay attention to state transitions in patients with different cardiovascular conditions and provide timely,personalized interventions and care.

To explore the developmental trajectories of post-traumatic stress disorder in patients with early pregnancy loss and to analyze their influencing factors.

Patients with early pregnancy loss who attended the obstetrics and gynecology outpatient clinic of a tertiary grade A hospital in Wuhan city were selected as the study subjects by a convenience sampling method from September 2024 to May 2025.Surveys were conducted on the day of early pregnancy loss,one month after early pregnancy loss,and three months after early pregnancy loss using a general information questionnaire,the post-traumatic stress disorder Checklist-Civilian Version,the Dyadic Coping Inventory,the Chinese Version Perceived Stress Scale,the Sense of Coherence Scale-13,and the Perceived Social Support Scale.A latent class growth model was used to identify the developmental trajectories of post-traumatic stress disorder in patients.Logistic regression analysis was employed to explore the influencing factors.

A total of 405 patients were finally included.Three distinct developmental trajectories of post-traumatic stress disorder were identified in patients with early pregnancy loss,namely a high traumatic stress response-chronic risk group(113 cases,27.9%),a low traumatic stress response-sustained improvement group(230 cases,56.8%),and a high traumatic stress response-rapid remission group(62 cases,15.3%).The results of Logistic regression analysis showed that the mode of conception,number of miscarriages,social support,sense of coherence,dyadic coping,and perceived stress were influencing factors for the developmental trajectories of post-traumatic stress disorder in patients with early pregnancy loss(all P<0.05).

There is group heterogeneity in the developmental trajectories of post-traumatic stress disorder in patients with early pregnancy loss.Clinical healthcare providers should promptly conduct psychological screening for patients with early pregnancy loss and develop precise nursing interventions based on the influencing factors of different trajectories to alleviate post-traumatic stress disorder in these patients.

To analyze and clarify the connotation of the concept of emotional intelligence among nurses.

Relevant literature on emotional intelligence among nurses was systematically searched in databases including CNKI,CBM,Wanfang Data,VIP Database,PubMed,EMbase,Web of Science,and ScienceDirect.Articles were screened according to inclusion and exclusion criteria,and analyzed using Rodgers' evolutionary concept analysis method.

A total of 42 articles were included.The conceptual attributes of emotional intelligence among nurses encompassed four aspects,namely self-awareness,social awareness,emotion management,and interpersonal relationship management.Antecedents were divided into internal factors(general demographic characteristics and individual traits) and external factors(organizational climate,education and training,and social support).Consequences mainly involved three areas,namely interpersonal relationships,nursing quality,and professional development.

The concept of emotional intelligence among nurses was clarified through Rodgers' evolutionary concept analysis method,which may provide a reference for improving emotional intelligence among nurses.

To explore the research status quo,hotspots,and development trends of artificial intelligence in global chronic disease prevention and control.

Relevant studies on artificial intelligence empowering chronic disease prevention and control were retrieved from the Science Citation Index Expanded of Web of Science.The literature was analyzed using R-bibliometrix and VOSviewer.

A total of 624 articles related to artificial intelligence empowering chronic disease prevention and control published between 2016 and 2025 were retrieved.High-frequency technology keywords included "machine learning" "deep learning" "Internet of things" and so on.High-frequency chronic disease keywords included "diabetes" "COVID-19" "cardiovascular diseases" and so on.Emerging technology keywords were "large language models" "long short-term memory networks" and so on.Emerging disease keywords were "asthma" and so on.

Artificial intelligence algorithms and the Internet of things constitute the core supporting technologies in the field of artificial intelligence empowering chronic disease prevention and control.Diabetes,COVID-19,and cardiovascular diseases are the focal diseases.Large language models and long short-term memory networks represent emerging technological directions.Asthma is an emerging hotspot disease.Artificial intelligence has played an important role in the field of chronic disease prevention and control.

To analyze the relationships between sleep duration,cognitive function,handgrip strength,and the risk of cardiovascular diseases(CVD) in middle-aged and elderly adults.

Based on data from the China Health and Retirement Longitudinal Study for the years 2011,2013,2015,2018,and 2020,restricted cubic spline curves were employed to investigate potential non-linear relationships between sleep duration,cognitive function,handgrip strength,and the risk of CVD.Log-Rank tests and Kaplan-Meier curves were utilized to analyze the relationships between sleep duration,cognitive function,handgrip strength,and the cumulative incidence of CVD.Cox proportional hazards models were applied to examine the associations between variables.The mediating roles of handgrip strength and cognitive function in the relationship between sleep duration and CVD risk were analyzed.

A U-shaped association was observed between sleep duration and the risk of CVD.Middle-aged and elderly adults with shorter sleep duration and lower handgrip strength levels had higher risk of CVD.Cognitive function was found to influence the risk of CVD through the mediating effect of handgrip strength.

Middle-aged and elderly adults could potentially prevent CVD by optimizing sleep duration,enhancing muscle function and so on.

To propose a 2D/3D medical image registration method based on generative adversarial network(GAN) for improving spatial alignment accuracy of images in minimally invasive spinal surgery navigation.

A registration framework for spinal preoperative 3D CT and intraoperative 2D X-ray images was constructed based on the LIDC-IDRI dataset.Deformation parameters conforming to vertebral joint constraints were generated using a generative adversarial network.Digitally reconstructed radiographs technology was employed to project preoperative 3D CT data onto a 2D plane to generate synthetic X-ray images.A stage-wise parameter decoupling method was adopted for iterative parameter optimization.2D/3D medical image registration was achieved. The performance of the proposed algorithm was validated using Elastix as the benchmark method.

The GAN-based registration method outperformed the open-source medical image registration framework Elastix in terms of mean absolute error(MAE),normalized cross-correlation(NCC),and normalized mutual information(NMI).The GAN-based registration achieved an MAE that was only 52.4% of that of the open-source medical image registration framework Elastix,while its NCC and NMI were 10.2% and 42.8% higher than Elastix,respectively.

By synergizing adversarial learning with gradient optimization,the GAN-based registration method achieves high-precision and robust intraoperative image registration.

To investigate the impact of physical activity and depressive symptoms on cognitive impairment among middle-aged and elderly people in China.

A total of 5 353 middle-aged and elderly people were selected from the 2018 China Health and Retirement Longitudinal Study.Relevant data were collected from three modules,namely basic information,health status,and cognitive function and depression.Univariate and multivariate Logistic regression analyses were performed to explore the effects of physical activity and depressive symptoms on cognitive impairment.

Both physical activity and depressive symptoms were influencing factors for cognitive impairment in middle-aged and elderly people(both P<0.001).Compared with the group with no depressive symptoms and high physical activity,the risk of cognitive impairment was significantly increased in the groups with depressive symptoms and high physical activity,no depressive symptoms and low-to-moderate physical activity,and depressive symptoms and low-to-moderate physical activity(all P<0.001).

Physical activity,depressive symptoms,and their joint effect among middle-aged and elderly people were associated with the risk of cognitive impairment.Greater attention should be paid to the mental health of middle-aged and elderly people.Efforts should be made to promote higher levels of physical activity among this population to reduce the risk of cognitive impairment.