Search Results (5,062)

To investigate the predictive factors for resistance to VEN combined with HMAs in the treatment of AML, construct a drug resistance prediction model, and visualize the model. A retrospective analysis was conducted on 74 AML patients. Multivariate logistic regression was used to identify independent predictors of primary resistance, based on which a nomogram model and a risk scoring system for drug resistance were constructed. The results showed that KIT (p = 0.012), TP53 (p = 0.010), and FAB-M5 (p = 0.059) were significantly associated with primary resistance to VEN. A nomogram prediction model incorporating FAB-M5, KIT, and TP53 was established. Based on the nomogram model, a drug resistance prediction scoring tool comprising three variables was developed, categorizing patients into high-risk (6–10 points), intermediate-risk (3–5 points), and low-risk (0–2 points) groups. Significant differences in NR rates were observed among the three risk groups (p < 0.001). KIT, TP53, and FAB-M5 are independent factors influencing VEN resistance. The constructed nomogram prediction model and scoring system may provide valuable references for predicting primary resistance to VEN. Full article

The economic resilience of agricultural enterprises is increasingly relevant for maintaining processing continuity and food quality in highly perishable agro-food chains. This study examines the associations between financial knowledge, financial management competency, business liquidity, and operational food-processing continuity in Türkiye’s tea sector. A quantitative cross-sectional design was employed, using structured survey data from 203 senior managers across 86 public and private tea-processing firms in Rize Province. The data were analysed using Ordinary Least Squares regression, mediation analysis, exploratory factor analysis, and robustness checks in accordance with OECD/INFE guidelines. Results indicate a significant deficit in theoretical financial knowledge (mean score: 4.47/10) alongside widespread overconfidence among 85% of managers. Applied financial management competency is positively associated with perceived business liquidity (β = 0.336, p < 0.001), suggesting that practical budgeting, cash-flow planning, and financial decision-making capabilities are relevant to maintaining operational funding capacity. In contrast, cash-flow difficulties are not significantly explained by firm-level financial knowledge, managerial competency, liquidity, or ownership structure (R² = 0.014, p = 0.722), indicating that these difficulties may reflect broader seasonal and sector-wide financing constraints. The findings challenge the assumption of a linear relationship between theoretical financial knowledge and managerial outcomes. They suggest a dual policy approach that combines applied financial management training with structural financing mechanisms to ensure the continuity of fresh leaf procurement and processing. While the study does not directly measure food safety, post-harvest losses, or SDG outcomes, the results have potential implications for reducing processing disruptions and supporting more resilient agro-food processing systems. Full article

Triple-negative breast cancer (TNBC) is characterized by aggressive clinical behavior and limited targeted therapeutic options. Hypoxia signaling mediated by hypoxia-inducible factor-1α (HIF-1α) and mitochondrial antioxidant defense driven by superoxide dismutase 2 (SOD2) represent biologically interconnected stress-adaptation pathways that may contribute to tumor progression. However, their combined prognostic impact in TNBC remains insufficiently defined. This retrospective study included 70 patients with surgically treated TNBC. Immunohistochemical expression of HIF-1α (nuclear) and SOD2 (cytoplasmic) was semi-quantitatively scored and analyzed individually and in combination. Patients were stratified as both-low, single-high, or both-high expression. Associations with clinicopathological parameters were evaluated, and overall survival (OS) and disease-free survival (DFS) were analyzed using Kaplan–Meier and Cox regression models. Stage-adjusted and stage-free multivariable analyses were performed, and sensitivity analyses using penalized Cox regression were conducted. High SOD2 expression was observed in 68.6% and high HIF-1α expression in 24.3% of cases. Neither marker was independently associated with survival outcomes in Kaplan–Meier or multivariable analyses. HIF-1α-high tumors showed a nominally lower Ki-67 proliferation index compared with HIF-1α-low tumors (median 30.0% vs. 60.0%, p = 0.023); however, given the number of comparisons performed, this finding should be regarded as exploratory and interpreted cautiously. Advanced stage and distant metastasis were the strongest predictors of both OS and DFS. In post hoc exploratory analyses, increasing SOD2 (HR 1.36 per point, p = 0.039) and HIF-1α scores (HR 1.80 per point, p = 0.022) showed nominal associations with worse OS; these findings are hypothesis-generating and should not be interpreted as evidence of independent prognostic value. Combined biomarker stratification showed a numerical stepwise pattern of OS curves, with the poorest survival observed in the both-high group, although statistical significance was not reached. High SOD2 expression is frequent in TNBC and may reflect underlying tumor biology; however, this was not independently confirmed in survival analyses. Continuous biomarker scoring suggests an incremental association with overall survival. Combined HIF-1α/SOD2 assessment did not demonstrate independent prognostic value in this cohort. These observations are hypothesis-generating and require validation in larger, prospectively designed cohorts before any clinical application can be considered. Full article

This paper develops a boundary-sensitive asymptotic theory for nonparametric conditional U-statistics smoothed by support-adapted asymmetric kernels when the response variable is subject to Missing-at-Random observation. The problem lies at the intersection of three well-established but traditionally separate lines of research: conditional U-statistics, asymmetric smoothing on constrained supports, and incomplete-data inference under MAR sampling. The contribution of the paper is not a novelty claim concerning any of these components in isolation. Rather, it consists in deriving a kernel-specific and MAR-aware limit theory for their simultaneous occurrence, where the estimators are nonlinear complete-case ratios of localized U-statistics and the localization devices are point-dependent approximate identities adapted to the geometry of the covariate support. The analysis covers three principal classes of support-respecting smoothers: Dirichlet kernels on the simplex, Bernstein polynomial smoothers, and multivariate beta kernels on hypercubes, with an additional extension to mixed continuous–categorical regressors. These smoothing schemes are not translation-invariant, and their local moments, effective support, normalizing constants and $L^2$-masses vary with the evaluation point, especially near the boundary. Consequently, their incorporation into conditional U-statistics requires more than a direct transfer of ordinary asymmetric-kernel regression theory. The numerator and denominator of the estimators are localized U-statistics whose stochastic expansions are governed by Hoeffding projections, including canonical components that must be controlled uniformly over the conditioning domain. Under regularity, smoothness and positivity assumptions adapted to the MAR setting, we establish uniform consistency, weak and strong uniform convergence rates, stochastic expansions and asymptotic normality. The results are obtained both on fixed compact subsets and on interior regions approaching the boundary, thereby identifying how support geometry enters the bias and stochastic normalizations. A central feature of the theory is the separation between the deterministic effect of complete-case sampling and its stochastic effect. For the complete-case estimator, the natural deterministic equivalent is obtained by replacing the design density f with the effective complete-case density $pf$, where p is the propensity score. Thus, the MAR mechanism may enter higher-order deterministic bias constants through the local design tilt, whereas the leading stochastic dispersion reflects the loss of effective information through propensity score factors. The precise variance constants and normalizing rates remain kernel-specific, depending on the local $L^2$-structure of the Dirichlet, Bernstein or beta smoothing device. The paper should therefore be viewed as a MAR extension and refinement of the complete-data asymmetric-kernel conditional U-statistic theory. It provides a common probabilistic architecture for several boundary-adapted smoothing schemes while retaining the kernel-dependent bias operators, variance constants, boundary regimes and Hoeffding-projection structures required for sharp asymptotic interpretation. Numerical experiments illustrate the finite-sample behavior predicted by the theory and highlight the interaction between support-adapted smoothing, boundary effects and incomplete response observation. Full article

Background/Objectives: Lifestyle Modification Programs (LMPs) based on exercise and nutrition aim to prevent/manage chronic diseases and foster well-being. However, moving LMPs from research to medical practice can be challenging, as programs must be both effective and feasible. The primary goal of this study was to assess cardiorespiratory fitness (CRF) changes according to an LMP, measured through VO_2max, as a key indicator of health outcomes and intervention efficacy. Methods: In this single-arm intervention study, 100 subjects were enrolled; per-protocol analysis of main parameters was performed on 85 participants (15 were excluded due to medical/technical reasons). A feasible intervention program (of low resource intensity with only two physician/patient encounters) provided personalized exercise prescription, optimized nutritional habits based on the Mediterranean diet and Healthy Eating Plate principles, and supported behaviour change. We assessed CRF through VO_2max, a key indicator of health outcomes and intervention efficacy. We also analyzed, using regression analysis, the relationship between VO_2max (the gold-standard measure of CRF) and MET_Speak, a simpler, feasible parameter of CRF derived from Exercise Stress Testing. Body composition (BC) and AHA diet score were also measured at baseline and post-6-month intervention. Statistical analyses included paired comparisons and multivariable regression to explore factors influencing CRF changes. Results: Analysis on the primary outcome, VO_2max, was performed according to the intention-to-treat principle and per-protocol. This feasible protocol resulted in a significant increase in VO_2max, improvements in fat-free mass, and a reduction in fat mass. Overall, 42.4% of participants achieved an improvement of ≥1 MET, a change previously associated with reduced mortality risk. Older participants tend to experience smaller improvements in VO_2max. Conclusions: Although observing an improvement in CRF and BC following an LMP is not surprising, the strength of the study is to show the feasibility of implementing an effective, feasible LMP into clinical routine, supporting the integration of such programs into clinical practice. Full article

Population-based evidence on sleep quality in Kazakhstan remains limited. This study describes sleep quality as a multidimensional construct among adults in Kazakhstan using data collected during the first national survey wave after the adoption of a single national time zone. The survey was designed as a national post-transition baseline assessment and not as an evaluation of the causal impact of the time-zone reform. Associations with socio-demographic, behavioural, clinical, and regional factors were examined. We conducted a nationally representative cross-sectional survey of adults aged 18–69 years in Kazakhstan from May to October 2025 using a multistage stratified cluster design. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as a global PSQI score > 5. Complete PSQI data were available for 5872 participants. Descriptive analyses examined the global PSQI score and the seven component scores. Survey-weighted multivariable logistic regression was used to identify factors independently associated with poor sleep quality. The weighted prevalence of poor sleep quality was 28.1%, and the weighted mean global PSQI score was 4.43. The greatest component burden was attributable to sleep latency (mean 0.87), subjective sleep quality (0.82), and sleep disturbances (0.80), whereas use of sleep medication contributed minimally (0.11). Poor sleep quality was more common among women, older adults, urban residents, and participants with diabetes, current smoking, heavy episodic drinking, and depressive symptoms. In the adjusted model, female sex (aOR 1.37, 95% CI 1.19–1.57), age 55 years or older versus 18–24 years (1.98, 1.53–2.55), diabetes (1.47, 1.22–1.78), current smoking (1.28, 1.10–1.50), heavy episodic drinking (1.43, 1.16–1.76), and depressive symptoms (4.26, 3.52–5.15) were independently associated with higher odds of poor sleep quality. Rural residence was inversely associated with the outcome (0.71, 0.61–0.84). Compared with the North, higher odds were observed in the Central region (2.00, 1.46–2.74), East (1.94, 1.48–2.53), West (1.48, 1.17–1.88), and Almaty city (2.18, 1.72–2.76). Poor sleep quality is common among adults in Kazakhstan and is characterized primarily by difficulties with sleep initiation, perceived sleep quality, and nocturnal disturbances. The findings provide national post-transition baseline evidence and suggest that sleep health surveillance in Kazakhstan should prioritize demographic, mental health, behavioural, and regional inequalities while avoiding causal interpretation of the time-zone reform itself. Full article

This study investigated the influence of carrot cryopowder, obtained by cryogenic grinding, on the rheological, physicochemical, and structural characteristics of a structured curd product. The experiment was conducted using a three-factor Box–Behnken design, varying the mass fraction of curd (70–90%), carrot cryopowder content (2–6%), and fat content in cream (7–33%). Viscosity values ranged from 914 to 2810 mPa·s, with the highest value of (2810 mPa·s) recorded in experimental sample No. 5. The best overall characteristics were observed in this sample, which showed a β-carotene content of 2.76 ± 0.03 µg/g, while the concentrations of vitamins B1, B2, B3, B5, B6, and folic acid were 20–31% higher compared to the control sample. The regression model (R² = 0.9164) identified the optimal formulation: 89.6% curd, 5.4% carrot cryopowder, and 31.3% fat in cream. Storage stability studies conducted over 28 days at 4 ± 1 °C demonstrated additional practical advantages. The addition of carrot cryopowder significantly reduced syneresis to 12.4 ± 1.1% on day 28 (compared to 28.7 ± 2.3% in the control), improved microbiological stability, and maintained acceptable sensory properties with an overall acceptability score of 6.8 ± 0.6 points after 28 days. FTIR analysis confirmed that the carrot cryopowder was not merely mechanically dispersed within the matrix but actively participated in the formation of new intermolecular interactions, leading to the modification of the product’s chemical structure. The obtained results showed that the incorporation of carrot cryopowder not only increased the nutritional and functional value of the curd product but also enhanced its structural stability and potential shelf life without negatively affecting the main technological indicators. Full article

Background/Objectives: Bariatric surgery is an effective intervention for severe obesity; however, long-term outcomes may be influenced by postoperative dietary behaviors, nutritional status, and complications. In Saudi Arabia, longitudinal evidence on weight trajectories and postoperative diet quality remains limited. The present study aimed at evaluating three-year weight status trends; assessing sociodemographic factors, baseline BMI, and postoperative diet quality; and examining nutrition-related complications following bariatric surgery. Methods: This retrospective longitudinal study included 189 adults who underwent sleeve gastrectomy at two tertiary hospitals in Jeddah, Saudi Arabia. Anthropometric data were obtained from medical records at six time points: preoperative, two weeks, six months, one year, two years, and three years postoperatively. Diet quality and postoperative complications were assessed via structured telephone interviews. Weight outcomes were expressed as percentage of total body weight loss (%TBWL), excess body weight loss (%EWL), excess body mass index loss (%EBMIL), and weight regain. Statistical analyses included Friedman’s test, Mann–Whitney U test, and multiple linear regression. Results: Significant improvements in all weight loss indicators were observed over three years (p < 0.001). Diet quality score was the only significant variable associated with weight loss at three years, with higher scores associated with greater %EWL and %EBMIL. Baseline BMI and DQS were significantly associated with %EWL (Beta = −0.17, 95% CI: −1.72 to −0.13 and Beta = 0.21, 95% CI: 1.37 to 7.12, respectively) and %EBMIL (Beta = −0.15, 95% CI: −1.68 to −0.07 and Beta = 0.24, 95% CI: 1.90 to 7.66, respectively). Age was significantly associated with weight regain (Beta = 0.20, 95% CI: 0.02 to 1.08). Conclusions: Bariatric surgery resulted in sustained weight reduction over three years. Postoperative baseline BMI and diet quality were significantly associated with %EWL and %EBMIL, underscoring the importance of structured nutritional follow-up and counseling. Full article

Background/Objectives: Standard mechanical compression applied during screening mammography is a primary barrier that reduces patient compliance. Current guidelines attempt to standardize compression based solely on the one-dimensional “breast thickness” measured by the device. This study aimed to investigate the effects of three-axis anatomical breast dimensions, applied compression force, menstrual cycle phases, and BI-RADS breast density patterns on pain scores during mammography within a comprehensive biomechanical model. Methods: This retrospective cohort study included 443 female patients who underwent routine screening or diagnostic mammography. Patients with a history of breast implants, lactation, or prior breast surgery that could alter tissue biomechanics were excluded. Maximum pain scores (1–10 on a Visual Analog Scale [VAS]) were recorded. Transverse, anteroposterior, and superoinferior breast biometric measurements for each patient were calculated using advanced radiological workstations. Data were analyzed using One-Way ANOVA and Multiple Linear Regression (OLS) models. Results: The mean age of the participants was 49.7 ± 9.4 years, the mean applied compression force was 62.4 ± 10.3 N, and the mean pain score was 2.03 ± 2.12 (range: 1–10). The multiple linear regression analysis was statistically significant overall (F = 2.516, p = 0.015). Having a BI-RADS Type D (extremely dense) breast pattern was identified as the strongest independent factor associated with an increased pain score (p = 0.082, coefficient = 1.219). Age showed a trend toward a negative effect on pain (p = 0.072), while compression force showed a trend toward a positive effect (p = 0.067). Conversely, breast thickness (p = 0.231) and the three-dimensional mean breast size index (p = 0.568) demonstrated no independent predictive power. The menstrual cycle phase did not reach independent significance in the multivariate regression model (p = 0.117); however, non-parametric univariate analysis revealed a significant difference in pain across hormonal groups (Kruskal–Wallis H = 10.04, p = 0.039), with actively menstruating and luteal-phase women reporting higher pain than menopausal women. Conclusions: The pain experienced during mammography depends on the internal fibroglandular architecture (elasticity and stiffness) of the tissue rather than its external volumetric dimensions. Notably, neither device-measured breast thickness nor manually calculated three-dimensional breast dimensions independently predicted pain, challenging the widespread assumption that breast size drives mammographic discomfort. “One-size-fits-all” or thickness-based compression strategies should be abandoned in routine practice. Instead, “personalized compression” protocols that prioritize patient comfort without compromising image quality should be developed, particularly for younger patients and those with BI-RADS Type D, and to a lesser extent Type C, density patterns. Full article

Background/Objectives: Acute respiratory failure (ARF) encompasses heterogeneous etiologies, and early bedside prognostication remains challenging. Cytokines and chemokines may capture underlying biological severity and identify high-risk patients. We evaluated whether admission cytokine/chemokine profiles add incremental prognostic value over clinical risk factors in unselected ARF patients. Methods: This prospective, single-center cohort study enrolled adult patients admitted to medical ICUs with ARF requiring high-intensity respiratory support. Plasma samples were collected within 24 h of ARF diagnosis, and 19 cytokines/chemokines were measured using multiplex immunoassays. The primary outcome was ICU mortality. Univariate and multivariable logistic regression models assessed associations between biomarkers and mortality, with discrimination evaluated by the area under the receiver operating characteristic curve (AUC). Results: Among 41 patients, 15 (37%) died in the ICU. Non-survivors had higher rates of immunosuppression (80% vs. 38%, p = 0.010) and hematologic malignancy (67% vs. 31%, p = 0.026). CXCL10 (IP-10), IL-18, and CCL2 (MCP-1) were significantly higher in non-survivors, and IL-1Ra showed a marked numerical increase with a significant univariable association with ICU mortality, despite comparable severity scores and oxygenation indices at admission. A clinical core model (SOFA, immunosuppression, hematologic malignancy) achieved an AUC of 0.74 (95% CI 0.58–0.90); adding cytokines improved discrimination modestly (AUC 0.76–0.80). In highest-quartile survival analyses, IL-1Ra (p = 0.002), CXCL10 (p = 0.005), and CCL2 (p = 0.009) demonstrated significant survival separation. Conclusions: At ICU admission, CXCL10 (IP-10), IL-18, CCL2 (MCP-1), and IL-1Ra showed exploratory associations with ICU mortality and were prioritized as candidate inflammatory biomarkers. These findings require validation in larger multicenter cohorts. Full article

Background: Heart failure (HF) remains a major complication of acyanotic congenital heart disease (CHD) in children. Evidence integrating clinical and echocardiographic variables for HF severity stratification in pediatric acyanotic CHD remains limited. This study aimed to identify factors associated with moderate HF and develop an exploratory internally validated prediction model. Methods: This retrospective single-center outpatient study included 219 children aged 0–16 years with acyanotic CHD, identified from medical records spanning January 2023 to December 2025. Moderate HF was defined as Ross score 7–9 (≤5 years) or NYHA class III (>5 years). Multivariable analysis was performed using Firth’s penalized logistic regression. Internal validation used bootstrap optimism correction and leave-one-out cross-validation (LOOCV). Model discrimination was assessed using area under the receiver operating characteristic curve (AUC). Results: Moderate HF was identified in 131 patients (59.8%). LV remodelling defined by LVIDD z-score > +2 (adjusted OR 3.70, 95% CI 1.22–11.24; p = 0.021) and higher mean pulmonary arterial pressure (MPAP) (adjusted OR 1.03 per mmHg, 95% CI 1.00–1.06; p = 0.049) were independently associated with moderate HF. Premature birth showed an inverse association with moderate HF (adjusted OR 0.25, 95% CI 0.13–0.48; p < 0.001). The exploratory five-variable model demonstrated acceptable discrimination (apparent AUC 0.780, 95% CI 0.728–0.849; bootstrap-corrected AUC 0.760; LOOCV AUC 0.749, 95% CI 0.681–0.811), with adequate calibration. An MPAP threshold of ≥26.4 mmHg yielded 78.6% sensitivity for moderate HF identification. Conclusions: LV remodelling and elevated MPAP were independently associated with moderate HF in children with acyanotic CHD. The exploratory internally validated model demonstrated acceptable discrimination using routinely available variables. This model is exploratory and not yet ready for clinical use; prospective multicenter external validation is required before any clinical implementation. Full article

Background/Objectives: Children of families facing unmet social needs experience higher rates of adverse outcomes compared to those not experiencing unmet social needs. This study aimed to identify factors associated with families’ unmet social needs as reported by parents or guardians at their children’s primary care visits. Methods: This cross-sectional study recruited English-speaking primary caregivers of children less than 18 years of age from the Southwestern Ohio Ambulatory Research Network (SOAR-Net) who were surveyed between January 2023 and August 2024. Surveys included the Maternal Social Support Index, Social Capital Scale, RAND Depression Screener, Children with Special Health Care Needs Screener, Medical Expenses of Children Survey, a 10-item social needs screener, and demographics. Data were analyzed with chi-square or Fisher’s exact tests, adjusted logistic regression, and ANOVA. Results: Among 1167 respondents (78% response rate), 1114 provided complete data. Primary caregivers were predominantly mothers (79.9%) or fathers (13.6%), White (72.0%) or Black (16.0%), and had an associate’s degree or less (65.1%). The mean (SD) index child’s age was 6.4 (5.3) years, and 52.4% were female. Underinsurance, positive depression screens, and poor child health were positively associated with unmet social needs. Higher scores for social support and social capital were associated with fewer social needs. Multinomial logistic regression revealed significant relationships with reporting two or more unmet social needs with the following variables: childhood underinsurance, household annual income < $50,000, positive depression screens, raising a child with a chronic health condition, and Black race/ethnicity. Conclusions: Several significant social factors were independently associated with a greater number of unmet social needs. These findings highlight the complex interplay among social factors in children’s healthcare. Future research should explore the putative longitudinal stability of these relationships. Full article

Early detection of dental caries remains a significant clinical challenge, as conventional diagnostic methods lack sensitivity for incipient lesions. Raman spectroscopy offers high chemical specificity for enamel characterization; however, clinical translation is hindered by the complexity of conventional polarized confocal systems. In this work, we present a Raman-based fiber-optic sensing approach for the detection and classification of dental enamel conditions, including sound, affected, and carious tissues. A custom fiber-optic probe was developed for remote measurements and evaluated against a reference polarized confocal Raman system. In addition to spectral discrimination, key factors affecting sensing performance were investigated, including spatial variability across enamel surfaces and angular sensitivity due to probe misalignment. Raman-derived features (carbonate-to-phosphate ratio, phosphate peak intensity, position, and bandwidth) were analyzed using a multinomial logistic regression classifier. The fiber-optic sensor achieved an overall classification accuracy of 73% (F1-scores: 0.55 sound, 0.63 affected, 0.9 carious), confirmed by leave-one-tooth-out cross-validation. Probe misalignment studies revealed robustness up to 10° angular deviation. These results demonstrate that a simplified non-polarized fiber-optic Raman system provides competitive diagnostic performance and clinically relevant robustness, supporting its development as a point-of-care sensing platform for early dental caries detection. Full article

Background: The increasing use of e-cigarettes among adolescents is a growing public health concern in Thailand, where they are prohibited but remain accessible. This study aimed to examine the psychosocial correlates of preventive behaviors regarding e-cigarettes among adolescents in central Thailand. Methods: A cross-sectional correlational study was conducted with 383 secondary school students (Grades 7–12) selected through proportionate stratified random sampling from two government schools in Ongkharak District, Thailand. Data were collected using a validated self-administered online questionnaire assessing attitudes toward e-cigarettes, peer influence, family attachment, and preventive behaviors. Item analysis, confirmatory factor analysis (CFA), and factor-score regression with bootstrapped indirect-association analysis (k = 5000) were performed to examine direct and indirect associations. Results: The four-factor measurement model demonstrated acceptable absolute fit (SRMR = 0.069) but weaker incremental fit (CFI = 0.70), expected given the large number of ordinal indicators estimated via maximum likelihood, with standardized factor loadings ranging from 0.621 to 0.926 (p < 0.001). The structural model explained 44.2% of the variance in preventive behaviors (R² = 0.442). Family attachment showed the strongest total association (β = 0.456), including both direct and indirect associations through attitudes (β = 0.116) and peer influence (β = 0.162), consistent with a pattern of statistically significant indirect associations. Conclusions: Family attachment was associated with self-reported e-cigarette preventive behavior, with statistically significant indirect associations through attitudes and peer influence. Given the cross-sectional design, these findings should be interpreted as model-consistent associations rather than causal mediation, and may inform future family- and peer-oriented prevention research in comparable settings. Full article

Background: Traumatic brain injury (TBI) and substance use disorder (SUD) frequently co-occur due to shared risk factors and a potentially bidirectional relationship. However, epidemiological patterns in rural populations remain understudied despite known disparities in access and outcomes. This study aimed to characterize the relationship between TBI and SUD in a rural Southwestern population, including demographic and clinical patterns of diagnostic sequencing. Methods: A retrospective observational study was conducted using electronic health records and trauma registry data (2022–2023) from a rural trauma center. Cohort one included 24,389 emergency department encounters with ICD-10 codes for TBI or SUD. Cohort two included 248 trauma registry patients with TBI and SUD diagnoses. Descriptive statistics and multinomial logistic regression models were used to evaluate diagnostic patterns and associated demographic factors. Results: Males were more likely to have co-occurring TBI and SUD (Relative Risk Ratio [RRR] = 1.35), while increasing age was associated with TBI-only diagnoses. Among patients with multiple visits and diagnoses, 16% had co-diagnoses, while 9% had sequential diagnoses. American Indian/Alaska Native patients had higher co-diagnosis risk compared to White patients (RRR = 2.21, p < 0.001). Higher blood alcohol concentration was associated with lower Glasgow Coma Scale scores (r = −0.15, p = 0.022), indicating greater severity. Conclusions: TBI and SUD frequently co-occur in rural populations, with notable disparities by sex and race/ethnicity. Emergency Departments are critical points of care for interventions such as screening for both substance use and head injury when either is suspected, and employing culturally responsive education and referral pathways upon discharge. Full article