To observe the effectiveness of a family nurse dietary therapy regimen,developed based on the family nurse dietary therapy theory,in improving the severity of menopausal symptoms,metabolic indicators,and oxidative stress levels in overweight and obese patients with perimenopausal syndrome.

A total of 70 overweight and obese patients with perimenopausal syndrome were selected as study subjects from the gynecology outpatient clinic of a tertiary grade A hospital and a resident community in Shanxi province from May 25,2025 to August 29,2025.Patients were randomly divided into control group and intervention group,35 cases each.The control group patients received a conventional dietary program,while the intervention group cases received the family nurse dietary therapy regimen in addition to routine care.Anthropometric indicators,blood biochemical indicators,inflammatory indicators,and oxidative stress indicators were evaluated before the intervention and 6 weeks after the intervention.

During the intervention period,8 cases dropped out,31 patients in each group completed the trial.After 6 weeks of intervention,the intervention group demonstrated significantly lower levels than those before the intervention in terms of body weight,body mass index(BMI),waist circumference,abdominal circumference,hip circumference,body fat mass,visceral fat area,fasting plasma glucose(FPG),fasting insulin(FINS),homeostatic model assessment for insulin resistance(HOMA-IR),total cholesterol(TC),triglycerides(TG),low-density lipoprotein cholesterol(LDL-C),homocysteine(Hcy),alanine aminotransferase(ALT),aspartate aminotransferase(AST),blood urea nitrogen(BUN),serum creatinine(Scr),serum uric acid(UA),tumor necrosis factor-alpha(TNF-α),high-sensitivity C-reactive protein(hs-CRP),interleukin-6(IL-6),and malondialdehyde(MDA).Furthermore,the BMI,abdominal circumference,hip circumference,body fat mass,FPG,HOMA-IR,TG,LDL-C,Hcy,TNF-α,hs-CRP,IL-6,and MDA were significantly lower in the intervention group than that in the control group at the same time.Superoxide dismutase(SOD) levels were higher in the intervention group than that before the intervention.The SOD was significantly higher in the intervention group that in the control group at the same time(P<0.05).

The family nurse dietary therapy regimen,rich in non-nutrients,alleviated menopausal symptoms and effectively improved body composition,glucose and lipid metabolism,and inflammatory and oxidative stress levels in overweight and obese patients with perimenopausal syndrome.

To investigate the correlation between adverse outcomes and the Geriatric Nutritional Risk Index(GNRI) in elderly patients with bacterial pneumonia.

Based on the MIMIC-Ⅳ 2.2 database,a total of 2 903 elderly patients with bacterial pneumonia were selected as the study subjects. Nutritional risk was classified into four grades according to GNRI.The relationship between 28-day mortality and GNRI in elderly patients with bacterial pneumonia was elucidated using restricted cubic splines(RCS),Kaplan-Meier regression analysis,Cox proportional hazards regression models,and subgroup analysis.The Boruta algorithm was employed to rank the importance of predictors for 28-day mortality.

A non-linear negative correlation was observed between 28-day mortality and GNRI in elderly patients with bacterial pneumonia(P<0.001).GNRI value of 90.281 was identified as the critical point for clinical intervention.An elevated GNRI was associated with reduced mortality.The results of the Cox proportional hazards regression model indicated that GNRI was a significant predictor of 28-day mortality(P<0.001).Subgroup analysis revealed that factors such as demographic characteristics and comorbidities did not have statistically significant impact on the relationship between 28-day mortality and GNRI(P>0.05).GNRI was identified as one of the key influencing factors for 28-day mortality.

GNRI has demonstrated predictive value for short-term mortality in elderly patients with bacterial pneumonia.Nutritional support for elderly patients with bacterial pneumonia during treatment may reduce their mortality.

To explore the change trajectories of estimated cardiorespiratory fitness(eCRF) among middle-aged and older adults in China based on data from the China Health and Retirement Longitudinal Study(CHARLS) and to analyze the relationship betweent different classification of the trajectories and the risk of cardiovascular disease.

Data from 4 172 middle-aged and older adults who completed follow-up in CHARLS from 2011 to 2020 were included.eCRF levels in 2011,2013,and 2015 were calculated using non-exercise equations.Group-based trajectory modeling was employed to identify the classification of the eCRF change trajectories.Logistic regression was used to analyze the relationship between the classification of the eCRF change trajectories and the risk of cardiovascular disease,followed by subgroup analyses.

Among the 4 172 participants,1 150 developed cardiovascular disease,yielding an incidence rate of 27.6%.Three distinct eCRF change trajectories were identified,namely low-increasing then decreasing group(7.5%),moderate-rapidly decreasing group(28.0%),and high-slowly decreasing group(64.5%).After adjusting for multiple variables,Logistic regression showed that compared with the high-slowly decreasing group,both the low-increasing then decreasing group(OR=1.90,95%CI 1.43-2.51) and the moderate-rapidly decreasing group(OR=1.42,95%CI 1.20-1.69) had a higher risk of cardiovascular disease.Subgroup analyses revealed an interaction between the classification of the eCRF change trajectories and hypertension(P=0.008).

Group heterogeneity exists in eCRF change trajectories among middle-aged and older adults in China.Those with higher eCRF levels tend to have a lower risk of cardiovascular disease.Hypertensive status may influence the relative strength of the association between the classification of the eCRF change trajectories and the risk of cardiovascular disease.

To investigate the trajectories of symptom clusters in rectal cancer patients undergoing neoadjuvant chemotherapy and to analyze their correlation with postoperative recovery indicators.

A convenience sampling method was used to select 120 rectal cancer patients admitted to a tertiary grade A hospital in Shanghai city from April to December 2024 as study subjects.Patient symptom burden was assessed at five time points,namely before neoadjuvant chemotherapy(T1),after the first chemotherapy cycle(T2),after the second chemotherapy cycle(T3),after the third chemotherapy cycle(T4),and 3-5 days before surgery(T5).Exploratory factor analysis was employed to extract symptom clusters.Latent class growth modeling(LCGM) was used to identify the trajectory classes of the symptom clusters.Postoperative recovery indicators,including body weight,diet type,wound healing status,bowel function,and complication severity,were compared among different trajectory classes of symptom clusters.

There three stable symptom clusters were consistently identified across the five time points in rectal cancer patients,namely a core neurotoxicity symptom cluster,a gastrointestinal reaction symptom cluster,and a psychological stress symptom cluster.The cumulative variance contribution rate ranged from 66.71% to 80.60%.Patient symptom burden increased at T3 and peaked at T4.LCGM identified three trajectory classes for the core neurotoxicity symptom cluster,two for the gastrointestinal reaction symptom cluster,and two for the psychological stress symptom cluster.Statistically significant differences(all P<0.05) were found in body weight,diet type,bowel function,and complication severity among different trajectory classes of the core neurotoxicity symptom cluster.Significant differences(all P<0.05) were found in body weight,bowel function,and complication severity among different trajectory classes of the gastrointestinal reaction symptom cluster.Significant differences(all P<0.05) were found in body weight,diet type,and wound healing status among different trajectory classes of the psychological stress symptom cluster.

Symptom clusters in rectal cancer patients undergoing neoadjuvant chemotherapy show a progressively worsening trend with group heterogeneity.The trajectory classes of each symptom cluster have a certain impact on patients' postoperative recovery indicators.

To investigate nursing undergraduates' readiness and intention to use artificial intelligence,and to elucidate the path of action through which artificial intelligence readiness influences their intention to use artificial intelligence based on the technology acceptance model.

Using convenience sampling,460 nursing undergraduates from five universities in Shandong,Henan,and Sichuan provinces were selected from March to July 2025.Participants were surveyed using a general information questionnaire,the Artificial Intelligence Technology Acceptance Scale,and the Medical Artificial Intelligence Readiness Scale for Medical Students.

Among the 460 nursing undergraduates,the mean item score for artificial intelligence use intention was 5.53±1.13.Mean item scores for dimensions of the Medical Artificial Intelligence Readiness Scale for Medical Students,from lowest to highest,were cognition 2.85±0.79,ability 3.32±0.75,vision 3.54±0.72,and ethics 3.85±0.75.Path analysis results showed that cognition,ability,and ethics indirectly influenced artificial intelligence use intention through the mediating effect of perceived usefulness.Furthermore,cognition,ability,and vision indirectly influenced artificial intelligence use intention through the chain-mediating effects of perceived ease of use and perceived usefulness.

Nursing undergraduates' intention to use artificial intelligence is moderately high,but considerable room for improvement remained.Nursing educators should strengthen training in artificial intelligence knowledge and application skills for nursing undergraduates,while simultaneously fostering their forward-looking vision and awareness of ethics.These measures may enhance nursing undergraduates' artificial intelligence readiness,improve their perceived ease of use and perceived usefulness of artifical intelligence,and consequently increase their intention to use artificial intelligence.

To explore the influencing factors of adrenal crisis(AC) in children with nephrotic syndrome.To construct a risk prediction model,and validate its performance.

A total of 436 children with nephrotic syndrome admitted to the department of pediatric nephrology and rheumatology of a tertiary hospital in Guangdong province from May 2021 to May 2024 were selected as the study subjects.The children were divided into a training set(305 cases) and a validation set(131 cases) at a ratio of 7∶3.LASSO regression analysis and ten-fold cross-validation were used to screen significant variables influencing the occurrence of AC in children with nephrotic syndrome.Logistic regression analysis was employed to identify the influencing factors of AC in children with nephrotic syndrome.The performance of the model was evaluated using the area under the receiver operating characteristic curve(AUC),the Hosmer-Lemeshow goodness-of-fit test,calibration curves,and clinical decision curves.

Among the 436 children with nephrotic syndrome,60(13.76%) developed AC.Logistic regression analysis showed that the type of hormone effect,nephrotic syndrome recurrence>3 times,concurrent infection,previous history of AC,irregular use of traditional Chinese medicine,and excessively rapid hormone tapering or abrupt withdrawal were influencing factors for AC in children with nephrotic syndrome(all P<0.05).In the training set,the AUC was 0.831,the sensitivity was 0.767,the specificity was 0.756,the Kappa value was 0.343,and the Youden index was 0.523.In the validation set,the AUC was 0.855,the sensitivity was 1.000,the specificity was 0.561,the Kappa value was 0.249,and the Youden index was 0.561.The calibration curves of both the training set and the validation set were close to the ideal curves.The Hosmer-Lemeshow test yielded a χ² of 1.131(P=0.769) for the training set and a χ² of 7.271(P=0.064) for the validation set.The clinical decision curves indicated that the risk threshold probability ranged from 0.02 to 0.94 in the training set and from 0.02 to 0.60 in the validation set.

The risk prediction model for AC in children with nephrotic syndrome demonstrated good discrimination,accuracy,and clinical decision-making performance,which may assist healthcare providers in the early identification of children with nephrotic syndrome at risk of AC.

To explore the pressure injury incidence and influencing factors in elderly patients with different activity levels.

A multicenter cross-sectional survey was conducted,enrolling elderly patients aged≥65 years from eight tertiary hospitals. Data on general information,health status,skin examination,and implementation of preventive measures were collected using uniformly trained research tools and methods.

A total of 4 851 elderly patients were included,of whom 107 developed pressure injuries,resulting in an incidence rate of 2.2%.Among the independently mobile group,7(0.2%) developed pressure injuries.Among the crutches/assistance/wheelchairs group,16(1.9%) developed pressure injuries.Among the bedridden group,84(7.9%) developed pressure injuries.In the independently mobile group,age,dietary status,and type of dressing at pressure sites were independent risk factors for pressure injuries.In the crutches/assistance/wheelchair group,the Braden score was an independent risk factor.In the bedridden group,education level,Braden score and type of dressing at pressure sites were independent risk factors.

The incidence of pressure injuries in elderly patients is closely related to their activity levels,with lower activity levels associated with higher incidence rates.Risk factors for pressure injuries vary among patients with different activity levels.Targeted stratified prevention strategies should be implemented for independently mobile,crutches/assistance/wheelchair,and bedridden patients,focusing on key factors such as advanced age,nutrition,Braden score,medication use,and local dressing applications to effectively reduce the risk of pressure injuries.

To explore the categories of decision fatigue in young and middle-aged breast cancer patients,analyze their influencing factors,and construct a Nomogram model.

A total of 188 young and middle-aged breast cancer patients admitting to our hospital were selected as the study subjects by a convenience sample method from June 2023 to January 2025.The patients were surveyed using a general information questionnaire,the Decision Fatigue Scale,the Chinese version of the Decision Self-Efficacy Scale,the Decision Preparation Scale,and the Family Care Index.A latent class growth model was used to identify the categories of decision fatigue among patients. Logistic regression analysis was employed to screen for factors influencing decision fatigue categories.The R 4.2.1 software was used to construct a Nomogram model.The predictive performance of the Nomogram model was evaluated.

The decision fatigue score of young and middle-aged breast cancer patients was 17.74±2.63.Two categories were identified,namely a low decision fatigue group(70.2%) and a high decision fatigue group(29.8%).Age,education level,average monthly household income,awareness of specific tumor stage,whether radiotherapy or chemotherapy had been received,family care index,decision preparation score,and decision self-efficacy score were all influencing factors for decision fatigue categories in young and middle-aged breast cancer patients(P<0.05).A Nomogram model for predicting the risk of high decision fatigue in young and middle-aged breast cancer patients was constructed based on the influencing factors.The area under the receiver operating characteristic curve was 0.864,with a sensitivity of 87.50% and a specificity of 77.42%.The calibration curve approached the ideal curve.The net benefit value of the model was positive when the threshold probability ranged from 2% to 97%.

The level of decision fatigue in young and middle-aged breast cancer patients is relatively higher.Decision preparation and decision self-efficacy could influence decision fatigue categories.The Nomogram constructed in this study is beneficial for identifying patients with high decision fatigue.

To analyze the developmental trajectories of illness perception in patients with diabetic ketoacidosis(DKA) and to analyze the influencing factors.

A total of 197 hospitalized patients with DKA admitted to our hospital were selected as the study subjects by a convenience sampling method from February 2022 to December 2023.Surveys were conducted at admission,and at 1 month,3 months,and 6 months after admission using a general information questionnaire,the Summary Diabetes Self-Care Activities,the 10-Item Connor-Davidson Resilience Scale,the Brief Illness Perception Questionnaire,and the Hospital Anxiety and Depression Scale.Latent class growth modeling was used to identify the classification of the developmental trajectories of illness perception in patients with DKA.Logistic regression analysis was employed to explore influencing factors.

Illness perception scores of patients with DKA at admission and at 1 month,3 months,and 6 months after admission were 45.78±12.35,40.18±9.27,36.87±7.51,and 36.33±7.44,respectively.Latent class growth modeling identified three distinct developmental trajectories of illness perception in patients with DKA,namely a significant decline group(45 patients,accounting for 22.8%),a decline followed by increase group(90 patients,accounting for 45.7%),and a slow decline group(62 patients,accounting for 31.5%).Logistic regression analysis results showed that educational level,average monthly income,disease severity of DKA,anxiety,depression,diabetes self-management behaviors,and psychological resilience were all influencing factors for the classification of the developmental trajectories of illness perception in patients with DKA(all P<0.05).

The developmental trajectories of illness perception in patients with DKA exhibit group heterogeneity.Healthcare providers should develop targeted intervention strategies based on the influencing factors associated with different classification of the developmental trajectories to improve the illness perception of patients.