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China's total fertility rate has reached a critically low level, dropping to approximately 1.0 by the end of 2023which is significantly below the population replacement level of 1.5. This decline reflects a marked reduction in fertility intention among reproductive-aged women, exacerbating population aging and threatening long-term labor supply and social sustainability. Despite policy adjustments and governmental support initiatives, intended outcomes have not been realized. Current literature largely focuses on isolated determinants of fertility intention, overlooking heterogeneity within the population. Moreover, the pathways through which psychosocial factors operate across different subgroups remain poorly understood. Data for this study were derived from the 2021 Psychological and Behavioral Investigation of Chinese Residents (PBICR 2021), a nationally representative cross-sectional survey. Latent profile analysis (LPA) was employed to identify subtypes of fertility intention among reproductive-aged women, followed by multinomial logistic regression, which examined factors associated with different profiles. Among 2,973 reproductive-aged female participants, three distinct fertility intention profiles were identified via latent profile analysis: the Fertility Intention Decline Group (25.1%), the Low Fertility Intention Group (51.3%), and the High Fertility Intention Group (23.6%). Multinomial logistic regression analysis revealed that, compared with the Fertility Intention Decline Group, the Low Fertility Intention Group was significantly associated with family type, aged 20-40 years, residential location, having 2 children, and retirement status (all Fertility intention among reproductive-aged women demonstrates significant heterogeneity. This study identified three distinct latent profiles, each characterized by unique patterns of influencing factors. The findings highlight the necessity of moving beyond one-size-fits-all policy approaches and emphasize the importance of developing tailored interventions that account for the specific characteristics and determinants of each subgroup. Show less

Nurses in traditional Chinese medicine (TCM) departments face significant sleep challenges associated with occupational stressors. However, person-centered analyses classifying these sleep patterns remain scarce. This study aimed to identify heterogeneous sleep disturbance subgroups via latent profile analysis (LPA) and evaluate the performance of explainable machine learning models in discriminating these subgroups based on demographic and occupational features. A cross-sectional survey enrolled 7721 nurses from 130 TCM healthcare institutions in Liaoning Province (December 2024). Data encompassed demographic, occupational, and psychological variables obtained via self-administered questionnaires, including the Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance short form 8a. LPA was employed to categorize sleep disturbance patterns. Recursive feature elimination with random forest (RFE-RF) was used to select features associated with subgroup membership for five machine learning models. Models were trained on 70% of the data and evaluated on a 30% independent test set. The optimal classification model (XGBoost) underwent interpretability analysis using Shapley additive explanations (SHAP). LPA identified three subgroups: mild-stable (29.8%), moderate-fluctuating (60%), and severe-persistent (10.2%). Machine learning models achieved test AUCs of 0.71-0.84, with XGBoost demonstrating the highest discriminatory performance (AUC = 0.84, 95%CI: 0.83-0.85) in classifying subgroups. SHAP analysis indicated that monthly income, organizational support, hospital level, self-compassion, and resilience were the top five features contributing to the model's classification output. This study characterized three distinct sleep disturbance subgroups among TCM nurses, with the majority exhibiting moderate symptoms. The sequential application of LPA and explainable machine learning demonstrated robust performance in distinguishing sleep disturbance patterns. Identifying correlates-such as lower income and resilience-may assist nurse managers in stratifying risk and tailoring interventions for those most likely to fall into the severe subgroup. Future longitudinal studies are required to validate the stability of these subgroups and establish causal relationships. Show less

At present, the research on the effective teaching behaviors of clinical nursing teachers mainly focuses on the overall level of effective teaching behaviors and their relationship with other variables, ignoring the individual heterogeneity of the effective teaching behaviors of clinical nursing teachers. This study through latent profile analysis (LPA), aims to identify different effective teaching behavior profiles of clinical nursing teachers and explore the demographic and personal factors associated with these different effective teaching behavior profiles. This is a cross-sectional study. A survey was conducted among 842 clinical nursing teachers through demographic questionnaires, the Effective Teaching Behavior Scale, and the Self-Efficacy Scale. LPA analyzes the potential characteristics of effective teaching behaviors of clinical nursing teachers. The multiple logistic regression method was used to explore the predictors of different spectra. Three potential characteristics were identified: Profile 1- high effective teaching behavior group, Profile 2- moderate effective teaching behavior group, and Profile 3 - low effective teaching behavior group. Marital status, years of teaching experience and self-efficacy are predictive factors for different profiles. Most clinical nursing teachers are classified as type 1, and they have relatively good effective teaching behavior ability. Strategies such as enhancing self-efficacy, paying attention to the marital status of clinical nursing teachers, and focusing on training clinical nursing teachers with shorter tenure may be effective ways to improve the effective teaching behaviors of clinical nursing teachers in different situations. Show less

Emotional and motivational aspects of teacher-student relationships are central to adolescents' psychological need satisfaction and academic development. However, few longitudinal studies examine how these relational experiences evolve during adolescence or co-occur with emotional-motivational functioning. Drawing on the Self-Determination Theory and recent models of emotion transmission in classrooms, this study aims to explore how students' emotional and motivational perceptions of teachers co-occur with psychological need satisfaction in distinct developmental profiles and to examine their transitions over time during adolescence. The sample consisted of 779 German secondary school students (57% female; aged 12-15) from high-track schools, surveyed in Grade 8 (T1) and Grade 9 (T2). Latent profile analyses (LPA) and latent transition analyses (LTA) were conducted using six indicators: socio-emotional teacher-student relationship, perceived teacher motivation (positive/negative), and satisfaction of autonomy, competence and relatedness needs. Gender and academic grades were included as covariates. Three distinct profiles emerged: (1) emotionally disconnected & controlled, (2) emotionally ambivalent & uncertainly self-determined and (3) emotionally safe & self-determined. While transitions towards the moderate profile were most common, extreme profiles remained relatively stable. Lower academic performance significantly predicted membership in less favourable profiles. Findings underscore the intertwined nature of emotional relationships and motivational experiences in adolescence. Socio-emotional teacher support emerged as a key differentiator between profiles. Interventions should target emotionally supportive climates to foster students' psychological need satisfaction and engagement. Show less

Accurate measurement of lipoprotein(a)-cholesterol [Lp(a)-C] may be useful in interpreting the traditional lipid panel, particularly in patients with high Lp(a). We developed and analytically validated a direct immunocapture ELISA in a Clinical Laboratory Improvement Amendments-certified laboratory for quantifying Lp(a)-C in human plasma using an apolipoprotein(a)-specific monoclonal antibody (LPA4) coupled to magnetic beads. The linearity of the assay was found to be excellent (R Show less

Job satisfaction is a critical factor influencing workplace efficiency and employee well-being. In the context of Industry 5.0 transformation, understanding the latent profiles of job satisfaction and their relationship with mental health outcomes, such as depression, anxiety, and digital-intelligence job insecurity, is critical for promoting employee well-being and organizational sustainability. This study aims to explore the latent profiles of job satisfaction among industrial workers and explore their associations with mental health outcomes. This study used cross-sectional data from 3,420 male frontline workers from a large automobile manufacturing enterprise in Jilin Province, China in April 2024. Latent profile analysis (LPA) was employed to identify distinct latent profiles of job satisfaction among industrial workers, while hierarchical linear regression analysis was used to analyze the relationship between job satisfaction and psychological health outcomes (depression, anxiety and digital-intelligence job insecurity). The score of job satisfaction among industrial workers in Jilin Province was 3.62 ± 0.90. Four profiles were identified: very low (5.97%), low-to-moderate (31.14%), moderately high (42.63%), and high job satisfaction (20.26%). Depression and anxiety showed a clear level-gradient pattern across profiles, whereas digital-intelligence job insecurity displayed a non-monotonic pattern with higher levels in the low-to-moderate and moderately high profiles. Work stress showed consistent associations with all outcomes, and job satisfaction profiles remained associated with depression and anxiety after covariate and stress adjustment; associations with digital-intelligence job insecurity were smaller but detectable. This study examined heterogeneity in job satisfaction among frontline industrial workers and its associations with mental health outcomes. Latent profile analysis identified four job satisfaction profiles. Job satisfaction profile membership remained strongly associated with depression and anxiety. Digital-intelligence job insecurity showed a non-monotonic pattern across profiles. These findings suggest that an individual-centered profile approach provides actionable differentiation of mental health symptom burden across distinct job satisfaction patterns, supporting more targeted workplace strategies. Show less

Studies of surrogate decision-makers (SDMs) in the intensive care unit (ICU) often report high average levels of family decision-making self-efficacy (FDMSE). However, these findings contrast with the significant decision conflict commonly observed in clinical practice. This discrepancy suggests that high aggregate FDMSE scores may mask underlying subgroups with distinct experiences. Identifying these latent profiles is essential for understanding the true experiences of ICU SDMs. This study aimed to identify distinct latent profiles of FDMSE among ICU SDMs and explore key influencing factors. A cross-sectional study was conducted among SDMs of ICU patients. Exploratory and confirmatory factor analysis (EFA/CFA) was performed to examine the factor structure of the Chinese FDMSE scale. The verified factor structure was then used for latent profile analysis (LPA). Lastly, univariate and multivariate analyses were performed to identify the main influencing factors. A total of 350 ICU SDMs were included in the analysis. The three-factor model, including treatment decision-making, comfort promotion decision-making, and facing death decision-making, provided a good fit for the Chinese FDMSE scale. Two profiles emerged: 'weak family decision-making self-efficacy', accounting for 55.9% of cases, and 'strong family decision-making self-efficacy', represented by the remaining 44.1%. The 'strong family decision-making self-efficacy' group was more likely to be observed in families where the patients held religious beliefs and were diagnosed with cancer, and where the family decision-makers held religious beliefs, had higher incomes, and had engaged in prior discussions about treatment preferences. This study verified the multi-dimensionality and heterogeneity of the FDMSE of ICU SDMs through EFA, CFA and LPA. The identification of a subgroup with low FDMSE differs from previous studies. Key modifiable factors include socio-economic resources, prior communication of the patients' preferences, and spiritual and cultural background, which serve as crucial levers for strengthening the decision-support framework in critical care settings. By identifying two distinct FDMSE profiles and key influencing factors, it offers critical care nurses a new perspective to design targeted interventions, thereby enhancing their ability to provide personalised decision support. Critical care nurses should receive structured end-of-life communication training to address the shared vulnerability of ICU SDMs in facing death decision-making self-efficacy across both profiles. Show less

As sports socializing is becoming a dominant lifestyle that integrates physical health with social interaction in China, understanding the underlying drivers of participation is crucial. However, traditional research predominantly relies on a “variable-centered” paradigm, which assumes population homogeneity and focuses on linear relationships between single motives and behaviors. This approach often fails to capture the complexity of how multiple motivations are configured within individuals (heterogeneity), and how these internal configurations are associated with external behavioral choices. To address this gap, this study employed a novel hybrid methodological framework combining Latent Profile Analysis (LPA) and Random Forest (RF) modeling. Based on data from 1,104 adults, LPA was first used to identify distinct motivational subgroups. Subsequently, RF algorithms, utilizing feature importance ranking and “One-vs-Rest” strategies, were applied to identify the associative patterns between these motivational profiles and key behavioral indicators, including sports types, media usage, and economic investment. The analysis identified four distinct motivational profiles: (1) Psychologically Introverted (3.6%), prioritizing internal psychological rewards over social status; (2) Physiologically Oriented (44.1%), the largest group, driven primarily by physical health needs; (3) Balanced (39.0%), exhibiting moderate levels across all motivational dimensions; and (4) High-Motivation/Comprehensively Oriented (13.3%), showing high intensity in both internal and external rewards. The RF model achieved a training accuracy of 99.9% and identified that Sports Type (specifically large-ball games), Media Channels (particularly Douyin/Rednote), and Annual Spending were the top three salient behavioral markers distinguishing these profiles. Notably, the High-Motivation group was characterized by heavy reliance on visual social media for social display. Participation in sports socializing among Chinese residents is not characterized by a singular, homogeneous motivation but features a clear internal stratification structure. The specific pattern of motivational combinations (i.e., the type) systematically maps onto external behavioral choices, where the sociocultural attributes of the sport and the media characteristics of digital social platforms constitute the key predictive markers of behavioral differentiation. The establishment of this “Motivation Type—Behavioral Signal” integrated framework promotes a theoretical shift in the sports socializing research paradigm from “homogeneity” to “heterogeneity” and deepens the understanding of the complex manifestations of Self-Determination Theory and Social Capital Theory in a sports context. It also provides precise user profiles and behavioral insights for sports social platforms, commercial clubs, and public sports service departments. Exploring service customization and policy adjustments based on different motivation-behavior patterns could potentially enhance user engagement and satisfaction, suggesting a possible direction for the development of the sports socializing industry. The online version contains supplementary material available at 10.1186/s12889-026-26780-z. Show less

Elevated levels of lipoprotein(a) [Lp(a)] are increasingly recognized as an independent risk factor for cardiovascular diseases (CVDs). This systematic review and meta-analysis aimed to evaluate the impact of lipid apheresis therapy on serum Lp(a) levels in a wide array of disorders, particularly CVDs. Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science databases up to May 2025. Studies reporting pre- and post-treatment Lp(a) levels in participants undergoing lipid apheresis were included. A random-effects model was used when heterogeneity was significant. Subgroup and meta-regression analyses were conducted to explore potential sources of heterogeneity. A total of 43 publications comprising 67 studies with 2466 participants were analysed. Lipid apheresis significantly reduced serum Lp(a) levels (SMD = -1.52; 95% CI = -1.76 to -1.29; P < 0.001). Subgroup analyses confirmed significant reductions across various methods of Lp(a) detection, disease backgrounds, and initial Lp(a) levels. One-session lipid apheresis studies (n = 6) also demonstrated a significant reduction (SMD = -1.51; 95% CI = -1.72 to -1.29; P < 0.001). Meta-regression suggested that publication year and disease background contributed to heterogeneity. Lipid apheresis is effective in significantly lowering serum Lp(a) concentrations across a range of patient groups and treatment modalities. These findings support the therapeutic role of lipid apheresis in managing elevated Lp(a). Show less

Serum lipoprotein(a) [Lp(a)] is recognized as an independent risk factor for cardiovascular disease. However, whether hypertension modifies the association between Lp(a) and adverse outcomes in acute decompensated heart failure (ADHF) remains unclear. We investigated how hypertension status influences the relationship between Lp(a) and all-cause mortality in ADHF. We conducted a single-center retrospective observational study including 2610 patients hospitalized with ADHF. We normalized the distribution of Lp(a) by a logarithmic transformation and assessed the risk of all-cause mortality with Lp(a), using Cox regression with adjustment for potential confounders. Among 2610 patients (39.0% women; mean age, 68.8 years), 1606 (61.5%) had hypertension. Over 4.1 years (median), 1287 deaths occurred. In all patients, log-transformed Lp(a) was significantly associated with mortality (adjusted HR 1.21; 95% CI, 1.05-1.39; Increased admission Lp(a) levels were associated with a higher risk of all-cause mortality in ADHF patients with hypertension. Further studies are needed to explore the mechanistic links among Lp(a), hypertension and ADHF. Show less

This study aims to identify the 24-h movement behavior patterns of preschool children using Latent Profile Analysis based on Compositional Data Analysis (CoDA), and to examine their associations with physical fitness. The study employs a cross-sectional design. A total of 329 healthy children aged 4-6 years were selected. Accelerometers (ActiGraph wGT3-BT, Pensacola, FL, USA) were used to measure light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and sedentary behavior (SB), while sleep was assessed through parent and teacher questionnaires. The assessment of physical fitness was conducted in accordance with the "Chinese National Physical Fitness Test Standards" (Preschooler Section). To address the multicollinearity problems among components of physical activity (PA), CoDA was first applied, subsequently, Latent Profile Analysis was utilized to categorize 24-h movement behavior patterns, while a Generalized Ordered Logit Model (GOLM) was applied to investigate their associations with physical fitness. Three distinct behavioral patterns emerged from the analysis: the "brown bear group" (moderate PA and SB, high SP, N = 176, 53.5%), the "cheetah group" (high PA/MVPA, low SB, moderate SP, N = 102, 31%), and the "koala group" (low PA, high SB, lower SP, N = 51, 15.5%). After adjusting for potential confounding factors, it was found that compared with the "koala group", the "brown bear group" and the "cheetah group" exhibited higher levels of physical fitness, with the probability of improving their physical fitness rating being 3.69 times and 6.36 times that of the "koala group," respectively. This study highlights the significant impact of active and healthy activity patterns on the physical fitness of preschool children, providing a foundation for formulating personalized preventive and interventional approaches in early childhood. Show less

Accurate and ongoing assessments of physical activity (PA) and sedentary time (SED) are needed to support public health surveillance, evaluate interventions, and advance the understanding of how movement behaviours relate to health. After six cycles of data collection (2007 to 2019) using the Actical (AC) accelerometer, the Canadian Health Measures Survey (CHMS) transitioned to the ActiGraph wGT3X-BT (AG). To understand how estimates from the AC accelerometer may compare with those from the AG in the context of the CHMS, this study compares AC and AG accelerometer estimates of PA, step counts, and SED using CHMS protocols. A convenience sample of 47 adults (aged 18 to 79 years) and 36 children and youth (aged 3 to 17 years) wore both AC and AG accelerometers on their waist for seven consecutive days. Estimates of PA and SED, step counts, and the percentage of those meeting PA recommendations were compared between the devices using descriptive, correlation, and agreement statistics. Agreement ranged from poor to excellent, with variability across PA intensities and age groups. Significant absolute differences in SED and light PA (LPA) were observed across all age groups, and in step counts among children and youth. Agreement was good to excellent across most age groups for moderate-to-vigorous PA (MVPA), and among adults for step counts. While the percentage of those meeting PA recommendations was higher with the AG, results were not statistically different. Similar comparisons could be made with the AG device when using the normal and low frequency extension filters. The results of the present study provide data users and researchers with an indication of the expected differences between the devices across various movement behaviour outcomes in the context of the CHMS. Results suggest that comparisons between cycles 1 to 6 and Cycle 7 onward of the CHMS for MVPA are acceptable, but they should be carried out with caution. Comparisons of SED, LPA, vigorous PA, and step counts are not recommended. Show less

Lipoprotein(a) [Lp(a)] promotes atherosclerotic plaque vulnerability through pro-inflammatory and thrombogenic pathways, while the CatLet© angiographic score quantifies coronary lesion complexity. We hypothesized that their integration would improve prognostication in acute myocardial infarction (AMI) after emergency percutaneous coronary intervention (ePCI). In this retrospective cohort, 307 AMI patients undergoing successful ePCI (2020-2022) were stratified by 1-year major adverse cardiovascular/cerebrovascular events (MACCE). Serum Lp(a) and troponin I were measured post-admission. CatLet© and Gensini scores were assessed by blinded analysts. Multivariable logistic regression and ROC analyses evaluated predictive performance. MACCE patients (n = 78) exhibited higher Lp(a) (135.99 ± 33.07vs. 123.35 ± 42.70nmol/L, P = 0.0178) and CatLet© scores (33.58 ± 9.04vs. 30.80 ± 8.24, P = 0.0012) versus controls. Lp(a) (OR=2.339,95%CI:1.519-3.603, P <  0.001) and CatLet© score (OR=1.092, 95%CI:1.027-1.161, P = 0.005) independently predicted MACCE. The combined model Lp(a)≥70.70 nmol/L + CatLet© ≥ 18.6) significantly outperformed individual markers (AUC 0.862 [95%CI:0.83-0.96] vs. 0.780/0.833; DeLong's test confirmed the superiority of the combined model over individual predictors (P = 0.0089, Z = 2.64 vs. Lp(a); P = 0.034, Z = 2.12 vs. CatLet© score), with 88% sensitivity and 83% specificity. The Lp(a)-CatLet© synergy enhances MACCE risk stratification in ePCI-treated AMI, reflecting complementary pathobiological (Lp(a)-driven plaque vulnerability) and anatomical (CatLet©-quantified complexity) pathways. This dual-parameter approach could support post-PCI risk stratification and follow-up planning. Show less

Lipoprotein(a) [Lp(a)] is a well-established independent risk factor for cardiovascular disease. However, the long-term effects of Lp(a) on coronary plaque phenotype remain unclear. To explore the potential association between Lp(a) levels and coronary plaque volume, composition, and progression using coronary computed tomography angiography (CCTA). Patients with available data for Lp(a) and underwent baseline CCTA examinations between January 2009 to December 2015 and subsequently underwent a follow-up coronary CTA were retrospectively enrolled. Quantitative CCTA analyses measured plaque length, total plaque volume and composition volume. Patients were categorized into an elevated Lp(a) group (≥30 mg/dL) and a normal Lp(a) group (<30 mg/dL). The association between Lp(a) and baseline plaque characteristic and progression were investigated in linear mixed-effects models adjusted for clinical factors. Subgroup analyses were also conducted. Among 453 patients (mean age 64.7 years, 77.7% male) with a median follow-up of 6.15 years. elevated Lp(a) was linked to higher baseline plaque burden (all Elevated Lp (a) level was associated with high coronary artery plaque burden at baseline and rapid progression of LAP at follow-up. Lp(a) may serve as a significant residual risk factor in seemingly "low-risk" populations. Show less

Digital literacy has become a core competency for nursing professionals, enabling them to adapt to modern healthcare environments and engage effectively with emerging technologies. It is closely linked to innovative behavior, which is essential for problem solving and advancing nursing practice. Despite its importance, limited research has examined differences in digital literacy among undergraduate nursing students and how these differences influence innovation. A cross-sectional study was conducted using a convenience sample of 450 undergraduate nursing students from four universities in Anhui Province, China. Participants completed a general information questionnaire, the Undergraduate Digital Literacy Scale, and the Innovative Behavior Scale. Latent profile analysis (LPA) was employed to classify students into distinct digital literacy profiles, while logistic regression and one-way ANOVA were used to explore factors influencing profile membership and the relationship between digital literacy and innovative behavior. Three latent profiles were identified: a "Low Digital Literacy" group (34.1%), a "Moderate Digital Literacy" group (15.9%), and a "High Digital Literacy" group (50.0%). Significant differences were observed across profiles in relation to gender, age, academic year, and frequency of artificial intelligence (AI) use in the past 6 months. Importantly, students with higher digital literacy consistently exhibited stronger innovative behavior ( Digital literacy among undergraduate nursing students is heterogeneous and shaped by demographic and experiential factors. Targeted educational interventions tailored to distinct literacy profiles are needed to bridge gaps, promote equity, and strengthen innovation. By integrating AI and advanced digital tools into nursing curricula, educators can enhance students' competencies and better prepare them to thrive in an increasingly digital and intelligent healthcare landscape. Show less

This study uses label-free methods to determine the binding interactions of lysophosphatidic acid (LPA) with bovine and human serum albumin (BSA and HSA). LPA is a bioactive lysophospholipid (LysoPL) that signals through a G-protein-coupled receptor (GPCR). Plasma LPAs are primarily carried by albumin; however, their binding interactions with the carrier protein (HSA) are not as well studied as those with fatty acids, drugs, or metal ions. Therefore, the aim of this study is to determine the binding sites of LPA in serum albumin through spectroscopic methods. Intrinsic fluorescence quenching experiments in conjunction with a label-free, free solution light interferometric assay have been employed to determine the binding Show less

This study examined the relationship between motor competence (MC) and Physical Activity (PA) in school-aged children, and assessed the mediating role of physical fitness, based on the Model of the Relationship between Children’s Motor Development and Obesity Risk. From March to April 2022, 1,026 children (53.6% boys, mean age 8.93 years) from four public primary schools in Shijiazhuang City, China, were recruited via stratified cluster sampling. MC was assessed using the Test of Gross Motor Development, 3rd edition (TGMD-3), PA was measured via a three-axis accelerometer, and physical fitness was evaluated according to the Chinese National Student Physical Health Standards (2014 revision). Data were analyzed using SPSS 26.0, with mediation tested via the bias-corrected bootstrap method (10,000 resamples). Ball skills ( Ball skills are critical for promoting MVPA in school-aged children, with physical fitness acting as a significant mediator. Systematic ball skill training is recommended as a core strategy to enhance physical activity via improved fitness. Show less

This is a cross-sectional study designed to identify the latent profiles of psychological resilience in elderly patients with fracture and examine the relationship between resilience categories and fear of falling (FOF), thereby informing individualized rehabilitation strategies. A convenience sample was drawn from elderly patients admitted to the Department of Traumatology and Orthopedics at a tertiary general hospital in Beijing between September 2024 and July 2025 due to fall-related fractures. A total of 213 older adults aged 60 and above with fall-related fractures were included. Psychological resilience was assessed using the Connor-Davidson Resilience Scale (CD-RISC), and FOF was measured with the Falls Efficacy Scale-International (FES-I). Latent Profile Analysis (LPA) was used to identify resilience profiles. Logistic and linear regression analyses, adjusting for age, sex, comorbidities, pain level, functional status, and time since fracture/surgery, were performed to explore the relationship between resilience subtypes (entered as a continuous CD-RISC score), demographic and clinical factors, and FOF levels. The age of elderly patients with fall-related fractures was 60–98 (75.28 ± 8.73) years old, and the median age was 74 years old. Three latent resilience profiles were identified: low (33.5%), moderate (22.7%), and high (43.8%) resilience groups. Patients in the high-resilience group exhibited significantly lower FOF scores than those in the other two groups ( Psychological resilience is independently associated with fear of falling among elderly fracture patients, with a clear gradient across resilience profiles. Enhancing resilience, particularly in low-resilience individuals, may be a potential target for intervention, though causal inference is limited by the cross-sectional design and single-center, convenience sampling strategy. Integrating resilience assessment into clinical evaluation could support more holistic rehabilitation planning. ChiCTR2400089221, September 4, 2024. Show less

Lipoprotein(a) [Lp(a)] is an independent risk factor for atherosclerotic cardiovascular disease. Although Lp(a) levels are generally stable, the extent of intraindividual variation and the need for repeat Lp(a) testing remain unclear. To evaluate the intraindividual variation in Lp(a) levels assess the clinical impact of repeat testing on cardiovascular risk classification. This retrospective study analyzed 250 patients from a tertiary care lipid clinic with ≥2 Lp(a) measurements over a mean of 17.1 ± 15.5 months. Baseline levels were positively skewed (median of 56.0 nmol/L; interquartile range 21.0-154.3 nmol/L). Intraindividual coefficients of variation (CV) were 19.0% (mean-based) and 33.6% (log-transformed), exceeding the European Federation of Clinical Chemistry and Laboratory Medicine database CV (10.2%; 4.3%-26.7%). Cardiovascular risk reclassification occurred for 12.4% using the National Lipid Association thresholds (75 and 125 nmol/L) and 6.8% using the European Society of Cardiology threshold (105 nmol/L). Variability was not associated with time between measurements, medications, or biochemical parameters on multivariable analysis. Hence, repeat Lp(a) testing is generally unnecessary but could be considered in those near risk thresholds or those being evaluated for Lp(a)-lowering therapies. Show less

Lipoprotein apheresis (LA) is the only approved treatment for patients with elevated lipoprotein(a) [Lp(a)]. The Lp(a)FRONTIERS APHERESIS trial investigated whether pelacarsen reduces the need for LA in patients from Germany with elevated Lp(a) and established cardiovascular disease (CVD). Adult patients with Lp(a) levels >60 mg/dl who had undergone ≥35 LA sessions in the prior year were randomized to receive pelacarsen 80 mg or placebo every 4 weeks for 52 weeks. Weekly LA sessions were performed if the Lp(a) measurement from the prior visit was >60 mg/dL. The primary endpoint was the rate of performed LA sessions normalized to the weekly LA schedule (the number of actual LA sessions divided by the number of planned LA sessions during the 52-week period). Secondary endpoints were time to LA avoidance (for ≥24 consecutive weeks) and total LA avoidance from week 12 to week 52. Fifty-one patients were randomized (mean age 61.7 years, mean Lp(a) at baseline 85.4 mg/dL, and mean 44.0 LA sessions in the past 12 months), with 25 of 26 (96.2%) in the pelacarsen arm and 23 of 25 (92.0%) in the placebo arm completing the study. Baseline characteristics were generally balanced between treatment arms. Pelacarsen reduced the mean rates of LA (0.16 vs 0.93 in placebo, odds ratio 0.006, 95% confidence interval [CI] 0.003, 0.013; P < .0001) and substantially increased the hazard of achieving LA avoidance (hazard ratio: 88.3; P = .0014; median time to achieve LA avoidance: 6.1 weeks) and total LA avoidance (odds ratio: 163.2; P = .0005). The placebo-adjusted Lp(a) change from baseline at week 52 was -72% (95% CI: -79%, -61%; P < .0001). Treatment emergent adverse events were similar between arms, except for mostly mild injection site erythema (pelacarsen 38.5%; placebo 0%). Pelacarsen is a highly effective and well-tolerated Lp(a)-targeted therapy that substantially reduces the need for LA in patients with elevated Lp(a) and established CVD. NCT05305664. Show less

Lipoprotein(a) [Lp(a)] and LDL cholesterol (LDL-C) are causally linked to aortic valve calcium (AVC) and aortic stenosis (AS). Lipoprotein(a) has anti-fibrinolytic properties; therefore, aspirin may reduce cardiovascular disease risk among individuals with high Lp(a). This analysis sought to determine the association of aspirin with incident AVC and AS across Lp(a) and LDL-C levels. This observational study included up to 6598 participants in the Multi-Ethnic Study of Atherosclerosis. Aortic valve calcium was measured on non-contrast cardiac computed tomography. Multivariable Cox hazards regression assessed the association of self-reported regular aspirin use (≥3 days/week) with incident AVC and severe AS, stratified by Lp(a) and LDL-C. Aortic valve calcium and Lp(a) values were not reported to participants. Mean age was 62 years, 53% were women, 23% reported regular aspirin use, 8% developed AVC (median 8.9 years), and 1% developed severe AS (median 16.7 years). Among individuals with elevated Lp(a), regular aspirin use was associated with a lower risk of incident AVC (Lp(a) ≥75 mg/dL: hazard ratio (HR) .42, 95% confidence interval (CI) .19-.93; Lp(a) ≥100 mg/dL: HR .17, 95% CI .04-.67) and severe AS (Lp(a) ≥50 mg/dL: HR .13, 95% CI: .04-.47; Lp(a) ≥75 mg/dL: HR .02, 95% CI .001-.29). For participants with elevated LDL-C, there was no association of regular aspirin use with incident AVC (LDL-C ≥130 mg/dL: HR 1.02, 95% CI .66-1.58; LDL-C ≥160 mg/dL: HR 1.51, 95% CI .53-4.28) or severe AS (LDL-C ≥100 mg/dL: HR .70, 95% CI .39-1.26; LDL-C ≥130 mg/dL: HR .46, 95% CI .14-1.47). In this exploratory analysis of prospective observational cohort data, regular aspirin use was associated with a lower risk of AVC and severe AS in persons with high Lp(a), but not high LDL-C. Confirmatory studies are required to determine the role of aspirin in the prevention of AVC and AS for persons with high Lp(a). Show less

This study aims to examine the health characteristics of female sex workers (FSWs) in entertainment venues and to investigate the relationship between these characteristics and sleep quality. This study employed a cross-sectional design and was conducted from January to April 2024 in Wuhan, China. Participants were FSWs recruited through snowball sampling from entertainment venues, including hotels, restaurants, nightclubs, karaoke bars and dance halls. Data were collected via structured questionnaires covering sociodemographic information, work experience, psychological stress, health status, sleep quality and circadian rhythms. Latent profile analysis (LPA) was employed to identify health characteristic profiles among FSWs, and multivariate logistic regression was used to examine the associations between these profiles and sleep quality. Among the 1,036 FSWs surveyed, 45.1% had poor sleep quality. LPA classified FSWs’ health characteristics into three profiles: the high overall functioning group, the lower physical–emotional functioning group and the lower psychosocial functioning group. Multivariate logistic regression analysis showed that FSWs in the lower physical–emotional functioning group had higher odds of poor sleep quality (OR = 2.184) compared with those in the high overall functioning group. FSWs in the lower psychosocial functioning group had substantially higher odds of poor sleep quality (OR = 7.755) than that in the high overall functioning group. FSWs demonstrate substantial heterogeneity in health characteristics and exhibit lower overall sleep quality compared with the general population. Psychological and physiological factors are major influencing factors for their sleep quality, suggesting the importance of prioritising mental and physical health in this population. Show less

Drug resistance is a major challenge in colorectal cancer (CRC) treatment. Overcoming drug resistance and improving therapeutic outcomes are crucial issues for patients with drug-resistant CRC. Crassocephalum rabens (Benth.) S. Moore (CR) is an edible plant and a folk medicine. Its galactolipids have anti-inflammatory and antitumor potential. This study explored the pharmacological mechanism and therapeutic efficacy of galactolipids isolated from CR (designated CRA) for treating drug-resistant CRC in vitro and in vivo. The antitumor activity and molecular mechanisms of CRA were investigated using cytotoxicity, reactive oxygen species (ROS) production, RNA sequencing, quantitative PCR (qPCR), Western blotting, and LPA concentration assays. Virtual molecular docking was conducted to identify CRA's action site on the target protein. The therapeutic effectiveness of CRA was evaluated using HT-29 xenograft mice. CRA induced ROS-mediated cytotoxicity by inhibiting the expression of interferon-α-induced protein 6 (IFI6). IFI6 suppression by CRA led to ROS accumulation and oxidative DNA damage, ultimately resulting in cell death. CRA antagonistically targeted lysophosphatidic acid receptors (LPAR), specifically LPAR2, and blocked their downstream signaling pathways, including PI3K/AKT/mTOR, Ras/Raf/p38, PLC/PKC, Rho/PKA, and NF-κB, which inhibited cell survival. Furthermore, CRA also inhibited the intracellular synthesis of LPA. In HT-29 tumor-bearing mice, CRA significantly reduced tumor growth. The antitumor activity of CRA, through inhibiting LPAR2 expression and inducing IFI6-mediated oxidative stress, was also observed in tumors. CR galactolipids directly targeted LPAR2, inhibited the LPAR2 signaling pathways, and induced IFI6-mediated ROS accumulation to combat drug-resistant CRC. Show less

Observational studies have yielded conflicting evidence regarding the interdependence between lipoprotein(a) [Lp(a)]-related cardiovascular risk and systemic inflammation. It remains unclear whether combined targeting of Lp(a) and inflammation provides additive cardiovascular benefits. This study aimed to investigate the associations between genetically predicted lower Lp(a) and cardiovascular disease (CVD) across interleukin-6 (IL-6) signalling levels and the combined effects of lower Lp(a) and IL-6 signalling activity on CVD risk. This study included UK Biobank participants of European ancestry. Genetic scores for LPA and IL-6 receptor (IL6R)-mediated signalling were calculated to mimic the effects of therapies targeting Lp(a) and IL-6 signalling, respectively. We investigated the associations of separate and combined exposure to lower Lp(a) and IL-6 signalling with coronary heart disease (CHD), ischaemic stroke (IS), heart failure (HF), atrial fibrillation (AF), peripheral artery disease (PAD), and aortic aneurysm (AA), using Mendelian randomization analyses and validating the findings in observational analyses. This study included 408 687 UK Biobank individuals (mean age, 57 years; 54% women). Genetically predicted lower Lp(a) was associated with reduced risks of CHD [odds ratio (OR) per 50 mg/dL reduction in Lp(a) levels, 0.68; 95% confidence interval (CI), 0.65-0.71], IS (0.89, 0.80-0.98), PAD (0.68, 0.62-0.76), HF (0.82, 0.77-0.88), and AA (0.71, 0.61-0.82). Genetically lower IL-6 signalling was associated with lower risks of CHD (OR per 0.5 log[mg/L] reduction in log-transformed C-reactive protein levels, 0.67; 95% CI, 0.55-0.82), AF (0.72, 0.55-0.94), and AA (0.43, 0.23-0.83). The genetic association between Lp(a) and CVD was consistent among individuals with different IL-6 signalling activity (P for difference > 0.05). Combined exposure to genetically predicted lower Lp(a) and IL-6 signalling was associated with an additive decrease in CHD risk (lower Lp(a): 0.67, 0.63-0.71; lower IL-6 signalling: 0.61, 0.46-0.80; combined: 0.25, 0.21-0.30; P for interaction = 0.144). In observational analyses, IL-6 levels below the median and Lp(a) concentrations below 50 mg/dL were also independently and additively associated with lower CHD risk (Lp(a) < 50 mg/dL: hazard ratio, 0.82; 95% CI, 0.72-0.93; IL-6 < median: 0.79, 0.65-0.96; combined: 0.65, 0.56-0.74; P for interaction = 0.102). Lower Lp(a) levels were associated with a reduced risk of CVD, independent of IL-6 signalling activity. Combined exposure to genetic variants lowering Lp(a) and downregulating IL-6 signalling was associated with an additive reduction in cardiovascular risk. These findings indicate that concurrent Lp(a)-lowering and anti-inflammatory therapies may reduce residual cardiovascular risk through additive effects. Show less

Resistance-conferring mutations in Drug resistance mutations vary by location, effectiveness of the national control programs, and the diagnostic methods employed. Rapid molecular diagnostic tests are the primary methods used to detect drug-resistant tuberculosis. Comprehensive resistance mutation profiles are often lacking in low- and middle-income countries. The goal of this study was to assess the patterns and frequencies of mutations conferring first-line drug resistance in Ethiopia using isolates collected from the drug resistance survey. The isolates were obtained before the implementation of rapid molecular tests. The findings will enhance our understanding of the patterns and frequencies of mutations that confer resistance, which is crucial for developing a comprehensive catalog of mutations. Show less

Reflective practice has emerged as a critical competency for psychiatric nurses, enabling them to critically evaluate and adapt their care approaches. Growing evidence suggests that reflective practice may serve as a key driver of high-quality caring behaviors, which are essential for establishing therapeutic relationships and improving outcomes in mental health settings. This study aimed to classify latent profiles of reflective practice among psychiatric nurses and examine their effects on caring behaviors. This cross-sectional study was conducted to recruit psychiatric nurses from ten mental health treatment centers across ten hospitals in Sichuan Province, China, between January and March 2024. Psychiatric nurses completed an online investigation encompassing the Reflective Practice Questionnaire and the Caring Behaviors Inventory (CBI). Latent profile analysis (LPA) and hierarchical regression analysis were employed to achieve the study objectives. A total of 346 psychiatry nurses were included in this study. The reflective practice of psychiatric nurses was classified into three subgroups in this study: "passive reflective participants" (n=48, 13.9%), "moderately balanced reflective practitioners" (n=175, 50.6%), and "high-achieving reflective leaders" (n=123, 35.5%). The hierarchical regression analysis revealed a significant positive association between distinct profiles of reflective practice and psychiatric nurses' caring behaviors (ΔR The identification of three distinct reflective practice profiles ("passive reflective participants", "moderately balanced reflective practitioners", and "high-achieving reflective leaders") provides a nuanced understanding of the reflective practice among psychiatry nurses. Targeted development programs, such as peer mentoring for the "passive" group and the "moderate" group, could be designed based on individual profile membership to optimize caring behaviors in psychiatric nursing. Show less

Using latent profile analysis (LPA) based on Self-Determination Theory (SDT), this study aimed to explore the profiles of health behavior motivation among Chinese patients with prediabetes and examine the relationship between these profiles and self-management ability. A cross-sectional study was conducted involving 335 patients with prediabetes. The questionnaires were used to assess health behavior motivation, self-management ability, satisfaction of basic psychological needs and disease knowledge level. Latent profile analysis was performed based on five subscale scores of the health behavior motivation measure. Three distinct latent profiles were identified: a "Self-Determined" profile (C1,29.55%, n=99), a "Non Self-Determined" profile (C2, 55.82%, n=187), and a "Conflicted" profile (C3, 14.63%, n=49). Patients in the C1 profile demonstrated higher levels of autonomy and competence. Patients in the C2 profile were characterized by better disease knowledge and lower relatedness. Compared to patients in the C3 profile, patients in both the C1 and C2 profiles exhibited significantly lower self-management ability. The heterogeneity in health behavior motivation profiles must be considered in the design and clinical practice of personalized interventions for prediabetes. Profile-specific strategies serve as the foundation for enhancing patients' self-management ability and sustaining healthy behaviors. Show less