Cervical cancer ranks as the fourth leading cause of cancer-related morbidity and mortality among women worldwide. Despite its global significance, evidence on cervical cancer risk factors in Kuwait remains limited. This case-control study aimed to identify factors associated with cervical cancer among women in Kuwait. A total of 50 cervical cancer cases were recruited from the Kuwait Cancer Control Center, and 155 controls were selected from public-sector employees in a 1:3 ratio. Data were collected using a structured questionnaire. Adjusted odds ratios (ORadj) and 95% confidence intervals (CI) were estimated through multivariable logistic regression analysis. Compared with controls, cases were more likely to have first marriageat a younger age (< 25 vs. ≥ 25years) (ORadj = 5.52; 95% CI: 1.34-22.82, p = 0.018), to be unaware of HPV vaccine availability (ORadj = 7.63; 95% CI: 1.60-36.39, p = 0.011) or tended to be in menopause (ORadj = 5.17; 95% CI: 1.64-16.33, p = 0.005). These associations were adjusted for the smoking status (ever vs. never). Younger age at firstmarriage, being in menopause, and unawareness of HPV vaccine availability were independently associated with an increased risk of cervical cancer. These findings should be regarded as preliminary and hypothesis-generating, offering a foundation for further research on this important women's health issue in Kuwait and comparable settings. Larger studies are warranted to confirm these results and to identify additional determinants of cervical cancer risk.

Purpose Following reports of an adverse link between glyphosate and bone mineral density (BMD), this cross-sectional study extended the investigation between glyphosate exposure and BMD to include osteoporosis, and fractures, with a focus on the high risk, post-menopausal female subgroup.MethodsCross-sectional data from 2,710 participants of the US National Health and Nutrition Examination Survey aged 8–59 years from 2013 to 2018 were used to assess associations between urinary glyphosate concentration (µg/L) and BMD (g/cm2) was measured using dual-energy X-ray absorptiometry (DXA), while osteoporosis and fractures were self-reported. Linear and logistic regression analyses were adjusted for age, race/ethnicity, BMI, smoking status, and income.ResultsThere was a negative association between glyphosate and BMD in the entire population (Whole Body BMD slope = -0.018; 95% CI = -0.027, -0.010; p < 0.001; Lumbar Spine BMD slope = -0.019; 95% CI = -0.030, -0.007; p = 0.002). In the high-risk, post-menopausal female subgroup, there was an inverse relationship (Whole Body BMD slope = -0.044; 95% CI = -0.076, -0.012; p = 0.009; Lumbar Spine BMD slope = -0.048; 95% CI = -0.101, 0.004, p = 0.069). Additionally, post-menopausal females with higher glyphosate had greater odds of self-reported osteoporosis (adjusted odds ratio (AOR) = 2.57; 95% CI = 1.24, 5.34; p = 0.011) and of self-reported fracture (AOR = 2.14; 95% CI = 1.28, 3.58, p = 0.004).ConclusionsResults are internally consistent and align with existing literature concerning toxicity of glyphosate on bone and extend it to include adverse impact on osteoporosis and fractures. Given the cross-sectional design and single point of sampling, longitudinal studies with repeated sampling are recommended to evaluate causation.

Background/Objectives: Type 2 diabetes (T2D) is a chronic metabolic disorder closely linked to cardiovascular disease and obesity and notably influenced by lifestyle and dietary patterns. The Mediterranean diet has well-established benefits across multiple cardiometabolic risk factors, including those relevant to diabetes. This study aimed to investigate the degree to which adults with T2D adhere to a Mediterranean dietary pattern and to examine how such adherence relates to glycemic and lipidemic regulation. Methods: This cross-sectional study included 100 adults with T2D (54 men and 46 women). Adherence to the Mediterranean diet was assessed using the Mediterranean Diet Score (MDS). Demographic, anthropometric, lifestyle, and clinical data were collected, and glycemic and lipid parameters were analyzed. Associations between Mediterranean diet adherence and metabolic outcomes were examined using correlation analyses and multivariable regression models adjusted for relevant confounders. Results: Most participants showed low adherence to the Mediterranean diet. A significant inverse association was observed between Mediterranean diet adherence and hemoglobin A1c (HbA1c) levels, with individuals scoring ≤35 on the MDS demonstrating higher HbA1c levels. Similar trends were observed in the lowest tertile of adherence. Notably, each one-point increase in MDS predicted a 0.13% reduction in HbA1c. In multivariable regression analyses, Mediterranean diet adherence remained the strongest predictor of glycemic control, independent of age, body mass index (BMI), sex, smoking status, physical activity and the number of antidiabetic treatments. Higher adherence was also significantly associated with lower low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) levels, as well as higher high-density lipoprotein cholesterol (HDL) concentrations. Conclusions: Greater adherence to the Mediterranean diet is independently associated with improved glycemic regulation and a more favorable lipid profile in adults with T2D. These findings support the Mediterranean diet as a valuable non-pharmacologic strategy for optimizing metabolic outcomes in people with T2D.

Background: Precursor endometrial lesions and endometrial cancer are strongly influenced by lifestyle-related risk factors, including obesity, low physical activity, and unfavorable dietary patterns. Identifying these factors is essential for early prevention and for improving health literacy among women. Objective: The objective of this study was to evaluate the influence of modifiable lifestyle factors on the likelihood of developing EIN and endometrial cancer in comparison with leiomyoma. Materials and Methods: A cross-sectional analytical study was conducted among 50 women, divided into three groups: leiomyoma (n = 20), EIN (n = 15), and endometrial cancer (n = 15). BMI, physical activity, dietary habits, sleep duration, stress levels, and smoking status were assessed. Statistical analysis included the Kruskal–Wallis test, correlation analysis, and logistic regression. Results: BMI was identified as an independent predictor of EIN/EC (OR = 1.29; p = 0.015). Women with EIN/EC demonstrated significantly lower levels of physical activity (p = 0.018). A clustering of behavioral risks was observed: higher BMI was associated with higher stress and shorter sleep duration. Conclusions: Modifiable lifestyle factors play a key role in the development of precursor and malignant endometrial conditions. Targeted interventions focusing on weight management, increased physical activity, and improved health literacy may reduce risk and improve quality of life among peri- and postmenopausal women.

Triglyceride-glucose (TyG) index has emerged as a reliable surrogate marker for insulin resistance and an early indicator of metabolic dysfunction. However, its association with inflammatory markers and adipokine dysregulation in patients with metabolic syndrome (MetS) remains poorly understood. This study aimed to investigate the association of the TyG index with inflammatory biomarkers and adipokine profiles in adults diagnosed with MetS. This cross-sectional study included 190 adults (aged 20-50 years) with metabolic syndrome (MetS), recruited from primary healthcare centers in Iran. We collected anthropometric and biochemical data, and calculated the TyG index, classifying participants into quartiles based on their TyG values. Fasting serum glucose (FSG), insulin, and lipid profiles were measured. Insulin resistance was assessed using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). In addition, inflammatory markers including tumor necrosis factor alpha (TNF-α), Interleukin-6 (IL-6), and high-sensitivity C-reactive protein (hs-CRP) long with serum levels of adipokines including leptin, adiponectin, resistin, visfatin, vaspin, and omentin-1 were measured using standardized assays. Higher TyG quartiles were associated with increased levels of insulin, HOMA-IR, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), TNF-α, leptin, and resistin, and decreased levels of adiponectin (all p < 0.05). There were no significant differences in high-density lipoprotein cholesterol (HDL-c), IL-6, hs-CRP, visfatin, vaspin, or omentin-1. These associations remained significant even after adjusting for age, sex, body mass index (BMI), smoking status, and physical activity. Our findings suggest that the TyG index reflects not only insulin resistance and atherogenic dyslipidemia, but also low-grade inflammation and adipokine imbalance in patients with MetS. Due to its simplicity and cost-effectiveness, the TyG index could be a useful tool for early metabolic risk assessment and identifying adipose tissue dysfunction.

Advanced glycation end-products (AGEs) activate specific receptors (RAGE) promoting inflammation and oxidative stress. The lungs, with high RAGE expression, may be particularly susceptible to AGE-related injury. This study assessed whether baseline skin AGE levels, measured by skin autofluorescence (SAF), predict pulmonary function decline in middle-aged adults with cardiovascular risk factors. This ancillary analysis of the ILERVAS cohort included adults aged 45-70years with cardiovascular risk factors but without diabetes or chronic kidney disease. Baseline data included demographics, lifestyle, and fasting blood tests. SAF was measured using AGE Reader™, and spirometry performed at baseline and after a median follow-up of 4years. Associations between baseline SAF and annual declines in FEV1, FVC, and FEV1/FVC were analysed using adjusted models and generalized additive models, stratified by smoking status. Among 658 participants (median age 56years, 48% female), median baseline SAF was 1.90 AU [1.60; 2.20]. Baseline lung function was preserved, with median FEV1, FVC and FEV1/FVC of 2795mL [2270; 3,341], 3,525mL [2870; 4300], and 78.6% [74.4; 82.8]. Annual declines were - 81.9mL [- 120.6; - 43.3] for FEV1, - 99.6mL [- 159.3; - 37.9] for FVC, and - 0.04% [- 0.85; 0.70] for FEV1/FVC. No significant associations were found between SAF and spirometry changes. Results were consistent across smoking subgroups. Baseline skin AGE levels did not predict pulmonary function decline over four years in middle-aged adults with cardiovascular risk factors. While SAF reflects cumulative AGE exposure, it has limited prognostic value for lung function in this population.

Abstract Introduction: Dysphonia, a disorder characterized by impaired vocal quality, pitch, loudness, or vocal effort, significantly impacts individuals’ communication abilities and overall quality of life (QoL). Aim: The current study aimed to assess the level of handicap due to dysphonia among patients visiting the laryngology clinic and to evaluate the factors affecting the impact of dysphonia. Methodology: This study examined adult patients with dysphonia at King Abdullah Medical City’s laryngology clinic from January 2021 to June 2024. Using the voice handicap index and structured questionnaires, data were collected on demographics, smoking status, duration of dysphonia, gastroesophageal reflux disease symptoms, choking, shortness of breath, dysphagia, and history of laryngeal surgery. Results: The patients ranged in age from 18 to 73 years, with a mean age of 43.5 ± 10.6 years. There were 43 (55.8%) female cases. In terms of education, 28 (36.4%) had not completed high school, and 28 (36.4%) had earned a bachelor’s degree. A total of 33.8% of participants reported that their dysphonia had a minor-to-moderate physical impact on the nature of their voice; 31.2% reported an emotional impact; and 27.3% reported a mild-to-moderate functional impact on their everyday activities. In 71.4% of cases, there was no effect on overall QoL. Conclusions: The study found that dysphonia significantly impacts QoL, particularly among smokers and urban residents, due to difficulties in communication and understanding. No gender-based differences were observed.

Background . The five-year survival rate of lung cancer patients remains extremely low, with the average rate of 22 %. Early detection of this disease can improve survival rates and reduce mortality. Lung cancer development is influenced by various risk factors, with smoking being the most significant, followed by other factors like occupational exposure, infections, genetic predisposition, presence of chronic diseases, etc. Considering risk factors is crucial for improving the efficacy of automated gas analysis complexes for lung cancer diagnosis. These complexes are promising for the application of scalable neural network data processing algorithms for noninvasive diagnosis of early stage lung cancer. Purpose of the study : to evaluate the effectiveness of the multimodal lung cancer detection method by analyzing the exhaled breath composition from 100 volunteers using simultaneous assessment of the exhaled breath composition and risk factors. Material and Methods. Along with exhaled breath samples, the study database also recorded all volunteers’ medical history data. Neural networks with a variety of architectures were used for data processing. The dataset for training neural network classifiers included exhaled breath samples from 100 volunteers, including 47 from healthy subjects and 53 from patients with morphologically confirmed lung cancer. Data determining the age group, smoking status and the presence of chronic lung diseases were analyzed as risk factors for lung cancer. Results . The integration of data, including exhaled breath composition and lung cancer risk factors, into a single neural network results in a 3 % increase in its original monomodal architecture. Taking into account a relatively small number of risk factors, such as age, gender, smoking status and COPD, increases the classifier’s sensitivity by 1.89 % and specificity by 6.39 %. The best generalization performance of the neural network classifier is achieved with a two-stream hybrid model with normalization. Conclusion. By incorporating diverse patient history data, such as age, smoking history, and chronic diseases, in addition to exhaled air composition data, into a unified neural network classifier, the accuracy of the exhaled air method for lung cancer diagnosis can be increased by an average of 4 %. This improvement, coupled with the expanded range of risk factors considered in the future application of the exhaled air method for lung cancer diagnosis in medical practice, will improve the reliability of population screening results.

Background: Cigarette smoking remains one of the most important preventable causes of respiratory morbidity, exerting detrimental effects even in young adults. Medical students represent a particularly relevant population, as the lifestyle habits they adopt during their training years may influence both their personal health and professional credibility. Methods: We conducted a cross-sectional analysis of 264 medical students from the University of Medicine, Pharmacology, Science and Technology of Târgu-Mures, aged 18–30 years, stratified according to smoking status, type of tobacco product used, and lifestyle characteristics (athletic vs. sedentary). Standardized spirometry was performed to assess FVC, FEV1, FEV1/FVC ratio, PEF, and small airway flow parameters (MEF25, MEF50, MEF75). Statistical comparisons between groups were performed using t-tests, Mann–Whitney U tests, chi-square tests, and correlation analyses, with p &lt; 0.05 considered statistically significant. Results: Smokers demonstrated significantly lower values for FEV1, PEF, and MEF parameters compared with non-smokers, confirming early functional impairment of both large and small airways. Within the smoking group, users of e-cigarettes or heated tobacco products exhibited more favorable FEV1 and small airway flow values than conventional cigarette smokers. However, differences in FVC were less pronounced. Significantly, athletes consistently outperformed their sedentary peers across all respiratory parameters, regardless of smoking status, with markedly higher FEV1, FVC, and MEF values and a lower prevalence of obstructive patterns. Cumulative smoking exposure (pack-years) was inversely associated with small airway function, whereas higher levels of physical activity were independently linked to a pronounced protective effect. Conclusions: Even in early adulthood, smoking is related to measurable declines in lung function, particularly affecting small airway dynamics. Although alternative products may appear less harmful than conventional cigarettes, they cannot be considered risk-free. Conversely, regular physical activity demonstrated a protective association in the case–control analysis, attenuating functional decline and supporting the preservation of long-term respiratory health. These findings underscore the importance of integrated prevention strategies in medical universities, combining smoking cessation initiatives with the systematic promotion of physical activity to safeguard the health of future physicians and reinforce their role as credible health advocates.

Despite the scale of prostate-specific antigen (PSA) testing for prostate cancer (PCa) screening, prediction models do not predict time-to-event end points or adjust for patient life expectancy. To develop, externally validate, and compare to existing tools a novel prognostic model for risk for prostate cancer-specific mortality (PCSM) after a PSA test. Prognostic model development in the PCa screening group of the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial; external validation in a Veterans Affairs (VA) population of patients undergoing PSA testing. United States. PLCO patients were enrolled from 1993 to 2001, and VA patients underwent PSA testing from 2002 to 2006. Survival follow-up was updated through 2022 in both cohorts. Male patients aged 55 to 74 years in the PLCO PCa screening group (n = 33 339) and the VA Healthcare System (n = 174 787). The model's predicted outcome is PCSM at a specified time point; predictors included PSA level, family history of PCa, and race. Predictors of other-cause mortality included age; body mass index; smoking status; and presence of hypertension, diabetes, or stroke. In the model development cohort, the area under the receiver operating characteristic curve (AUC) at 29.5 years from screening was 0.666 compared with 0.643 for a previously validated prostate biopsy risk model (Prostate Biopsy Collaborative Group [PBCG]) (P < 0.001). In the external validation cohort, the AUC at 20 years from screening was 0.776 for the PLCO model versus 0.749 for the PBCG model (P = 0.031). The model may not be generalizable to more contemporary PSA screening practices given the periods studied. This PCSM prognostic model was developed from long-term clinical trial data, was externally validated in a large national cohort, and may be used to improve interpretation of PSA results. None.

Introduction Clozapine (CLO) remains the gold standard for the treatment of drug-resistant schizophrenia. It is commonly accepted that there is a linear relationship between CLO dose and blood concentration, although deviations from this pattern are frequently observed in clinical practice. The aim of the present naturalistic study was to further investigate this relationship using a real-world database of CLO therapeutic drug monitoring (TDM) samples, with a particular focus on: i) identifying cases of “unexpected” CLO levels during repeated within-subject blood sampling in the process of CLO dose adjustment and ii) assessing linearity of the cross-sectional, between-subject CLO dose-concentration relationship and identifying potential breakpoints. Methods The study was based on a single-center TDM database derived from routine monitoring of CLO concentration in psychiatric inpatients, supplemented with data from medical records. The database was reviewed independently by a laboratory medicine specialist and psychiatrist to identify individual cases of “unanticipated” dose-concentration relationships. The study also employed the Multivariate Adaptive Regression Splines (MARS) to detect non-linear relationships in the prediction of CLO levels, as determined by high-performance liquid chromatography. Analyses incorporated variables such as daily CLO dose, smoking status, age, sex, and co-medications. Results Individual cases of “unanticipated” CLO concentrations supporting the partially non-linear within-subject dose-concentration relationship were unambiguously identified by both specialists. The MARS model revealed a breakdown in the between-subject CLO dose-concentration linear relationship identifying a hinge point around 400 mg/day, below which CLO concentrations were less dose-dependent. CLO dose and smoking were the most important predictive factors, but the model explained only about 25% of CLO concentration variability. Conclusion Our data suggest that the non-linear relationship between CLO concentration and its daily dose can be a real-life clinical problem with CLO doses of ∼400 mg/day as the provisional hinge point. Although preliminary, the present results warrant further investigations on non-linear aspects of CLO pharmacology, including “unexpected” CLO concentrations, toxicity, and lack of therapeutic activity.

AimThe extant literature on type 2 diabetes and cognitive decline is based on short cognitive follow-ups and assessments of baseline cognitive ability after diagnosis. The objective was to investigate the influence of type 2 diabetes on cognitive decline over a period of on average 44 years.Materials and methodsThis cohort study included 5,147 men from the Danish Aging and Cognition cohort consisting of a late mid-life (mean age 64.2 years) follow-up of men with intelligence test scores (IQ) available from statutory conscription board examinations in young adulthood (mean age 20.4 years). Follow-up included re-administration of the conscription board intelligence test and a comprehensive questionnaire. Exposure was self-reported but register-based type 2 diabetes and duration of disease were also calculated. Cognitive decline was defined as both IQ change (baseline-follow-up) and significant IQ decline based on the reliable change index (cut-off: 13.2 IQ-points). Associations were analyzed in linear and logistic regression models.ResultsMen having type 2 diabetes had a 1.81 IQ points (95%CI:1.14,2.49) larger decline compared to men without diabetes when adjusting for baseline IQ, years of education, follow-up age, retest interval, depression, and smoking status. Moreover, type 2 diabetes was associated with 1.42 times higher odds of a significant IQ decline and longer duration was associated with a larger, though not statistically significant, decline. The participation rate was 13.4%, and the participants were healthier and more well-educated than non-participants. To account for potential selection bias, inverse probability weights (IPW) were calculated based on baseline characteristics. The analyses applying these weights yielded similar estimates.ConclusionType 2 diabetes was associated with modestly greater cognitive decline and higher odds of a statistically significant (>13.2 IQ points) and clinically relevant decline. Finally, the alignment between main and IPW results indicates the findings are robust and likely generalizable.

TMPRSS2, a transmembrane serine protease and common partner in oncogenic TMPRSS2-ERG fusions, is regulated by androgen receptors and is implicated in prostate tumorigenesis. The nonsynonymous SNP rs12329760 (C > T; Val160Met) has been hypothesized to alter TMPRSS2 proteolytic activity, potentially enhancing AR signaling and contributing to aggressive tumor behavior. However, data on this variant in North African populations remain sparse. A case-control study was conducted including 50 Moroccan men diagnosed with prostate cancer (PCa) and 50 matched controls. Genotyping of rs12329760 was performed using TaqMan allelic discrimination assays. Genotype and allele distributions were analyzed and correlated with clinicopathological factors, including serum PSA levels, Gleason score, family history, smoking status, and other demographic or clinical variables. The CT (44% vs. 26%, P = 0.016) and TT (20% vs. 8%, P = 0.031) genotypes, as well as the T allele (43% vs. 21%, P = 0.002), were significantly more frequent in PCa patients than controls and were associated with increased disease risk. Carriers of the CT + TT genotypes exhibited significantly higher PSA levels (≥ 10 ng/mL, P = 0.004), Gleason scores (≥ 7, P = 0.018).Significant associations were also observed with positive family history (P < 0.001) and smoking (P < 0.001). No associations were found with age at diagnosis, T-stage. The TMPRSS2 rs12329760 T allele is associated with elevated prostate cancer risk and more severe clinicopathological features in Moroccan men. These findings highlight the potential prognostic relevance of the V160M variant and emphasize the need for further cellular and molecular studies to elucidate its functional role in AR signaling, TMPRSS2-ERG fusion biology, and ERG-related tumor aggressiveness. Such insights may contribute to the development of risk-stratified PCa management and tailored active surveillance strategies.

To evaluate whether cumulative smoking exposure and time since cessation are associated with perioperative morbidity after robot-assisted radical cystectomy (RARC). We retrospectively analysed 475 patients who underwent RARC with urinary diversion at a high-volume tertiary centre between 2004 and 2024. Outcomes of interest were postoperative early complications, postoperative readmission, overall risk of postoperative morbidity according to smoking status, cumulative smoking exposure, and time since smoking cessation. Multivariable logistic regressions were performed to explore the effect of smoking status, cumulative smoking exposure, and time since smoking cessation on perioperative morbidity after RARC. The locally estimated scatterplot smoothing (LOESS) function was used to graphically explore this relationship. Early complications occurred in 60% of current smokers, 50% of former smokers, and 37% of never smokers. Compared with never smokers, former (odds ratio [OR] 3.83, 95% confidence interval [CI] 1.73-9.38) and current smokers (OR 6.75, 95% CI 2.85-12.40) had significantly higher odds of perioperative morbidity. Each 10 additional pack-years increased complication risk (OR 1.20, 95% CI 1.05-1.40), whereas each year since cessation reduced risk (OR 0.84, 95% CI 0.76-0.91). The LOESS curves showed a steadily increasing risk with cumulative exposure and a gradual decline following cessation. Both lifetime smoking burden and time since cessation are strong and independent predictors of perioperative morbidity after RARC. Evaluating smoking exposure as a continuous variable improves risk stratification and provides more accurate information for preoperative counselling in patients undergoing RC.

This study aims to establish machine learning models using non-imaging data from health examinations of coal workers, which can screen the preclinical stage of CWP. Non-imaging data from two centers, totaling 34,362 coal miners, were collected. From 84 initial variables, 19 were preliminarily screened, and LASSO selected 8 key features. Six machine learning models were trained to predict the preclinical stage of CWP, evaluated using ROC curve. In the internal test set, GB achieved the best discrimination (AUC 88.19%), while DT yielded the highest accuracy (81.09%) and specificity (80.90%). In the external validation set, GB remained the top model by AUC (83.94%) and showed high sensitivity (87.67%). Age, FEV1, FEV1%, drinking status, smoking status, FVC, occupational category, and cumulative years of service are significant features for predicting the preclinical stage of CWP.

BackgroundInfluenza (flu) infection during pregnancy can lead to adverse maternal and fetal outcomes. Flu vaccination coverage among pregnant individuals remains low, and lack of health insurance may be a modifiable contributing factor to this trend. In 2021, 41.5% of pregnant individuals were covered by Medicaid—a government-sponsored insurance (GSI) that provides healthcare coverage for individuals with low income and specific conditions including pregnancy—while 3.6% were uninsured at the time of delivery.Table 1:Baseline Characteristics of Pregnant People Included in the Final Analysis using BRFSS 2022 and 2023 Data CombinedTable 2:Baseline Characteristics of Pregnant People Included in the Final Analysis using BRFSS 2022 and 2023 Data Combined by Health Insurance TypeMethodsWe utilized data from the 2022 and 2023 Behavioral Risk Factor Surveillance System (BRFSS), a national telephone survey in the US, to examine the relationship between health insurance type [employer-sponsored insurance (ESI), GSI, uninsured, or individual private/unknown] and self-reported flu vaccination within the past 12 months among pregnant individuals. Multivariable logistic regression was used to estimate adjusted odds ratios (aORs), controlling for age, income, comorbidities, smoking status, and having a primary care physician (PCP).Table 3:Multivariable Logistic Regression Analysis of Health Insurance Type and Flu Vaccination Using BRFSS 2022 and 2023 Data Combined.ResultsThe final analytic dataset included 3,059 pregnant respondents representing a weighted national sample of 3,151,027 pregnant individuals (Table 1). Overall, 37.3% reported receiving the flu vaccine within the last 12 months. Flu vaccination differed by insurance type: 48.4% for ESI, 37.8% for individual private/unknown, 32.5% for GSI, and 17.5% for uninsured individuals. In unadjusted analyses, those with GSI (OR 0.51; 95% CI: 0.38–0.69) and who were uninsured (OR 0.22; 95% CI: 0.13–0.39) had significantly lower odds of vaccination compared to those with ESI (Table 3). After adjusting for covariates, being uninsured remained significantly associated with lower odds of flu vaccination (aOR 0.48; 95% CI: 0.24–0.93).ConclusionPregnant individuals who are uninsured have a lower odds of flu vaccination, likely reflecting decreased access to prenatal care. Preserving access to Medicaid and the Children's Health Insurance Program (CHIP) for eligible pregnant individuals could be an important strategy to improve maternal flu vaccination coverage in the future.DisclosuresAll Authors: No reported disclosures

Enhancing forensic casework interpretation through DNA methylation-based analysis: A case study of pooled blood samples.

ABSTRACT Depressive symptoms are prevalent and impactful among patients with chronic kidney disease (CKD). However, traditional screening methods often yield high false positive and false negative rates in this population. This study aimed to develop a machine learning-based model to improve the early identification of depressive symptoms risk among CKD patients.Data were extracted from NHANES 2011–March 2020 (pre-pandemic) as the model development cohort and split into a training cohort and an internal validation cohort. A temporally independent NHANES cycle (August 2021–August 2023) was used as an external validation cohort. Predictors were selected using least absolute shrinkage and selection operator regression. Eight machine learning algorithms were trained. Given outcome imbalance, discrimination was primarily compared using recall, precision, and F1 score, with AUCs reported as secondary measures. Calibration was assessed using calibration curves and the Brier score, and clinical utility was evaluated using decision curve analysis. SHAP was used to interpret feature contributions in the selected model.In the internal validation cohort, the RF model achieved recall 0.826, precision 0.569, and F1 score 0.673, with an AUC of 0.941. In the external validation cohort, the RF model achieved recall 0.826, precision 0.136, and F1 score 0.234, with an AUC of 0.711. SHAP identified poverty-income ratio, smoking status, weight, and urine albumin-to-creatinine ratio as the top predictors, followed by marital status, education level, gender, BMI, albumin, and hypertension.This study provides a clinically actionable tool to stratify the risk of clinically significant depressive symptoms in patients with CKD, which may support targeted screening, timely mental health assessment or referral, and more efficient allocation of clinical resources. SHAP-based explanations help interpret individual risk estimates to inform patient-centered management.

Although support for tobacco smoking cessation provided by general practitioners (GP) has proven effective, such an approach remains quite rare. We designed a behavioural science-based intervention to improve GP support for patients to quit smoking. The present study aimed to evaluate the effectiveness of this in-office paper-based intervention by comparing it with a no-intervention control group. We conducted an online randomised controlled trial between January and May 2024 among GPs in France. The intervention consisted in sending a kit containing an information sheet for GPs outlining the main stages of brief advice for smoking cessation, questionnaires for patients asking them about their smoking status and, for those who smoked, their motivation to quit, as well as a poster to be displayed in each GP's waiting room to encourage people who smoke tobacco to complete the questionnaire. The primary outcome was the proportion of people who smoke with whom GPs had discussed smoking cessation on their last full working day five weeks after the kit had been sent out. The secondary outcome was the likelihood that GPs provided cessation support (e.g., prescribed nicotine replacement therapy (NRT), proposed a follow-up consultation, and/or referred patients to other professionals) on the same day. Of the 800 GPs recruited, 641 fully completed the final survey (333 in the intervention group and 308 in the control group). The proportion of people who smoke with whom GPs had discussed cessation was significantly higher in the intervention group (59.0% vs. 52.3%, p < 0.05). The likelihood of a follow-up consultation being offered to patients who smoke was also significantly higher in the intervention group (73.8% vs. 60.3%, p < 0.05). The likelihood of NRT prescription or referral were not significantly different between groups (82.4% vs. 77.9%, and 23.3% vs. 21.5%, respectively). Providing simple paper-based tools was associated with a greater likelihood of GPs discussing smoking cessation with their patients. This kind of intervention could usefully complement other primary care interventions, for example training, remuneration and financial incentives or care pathway reorganisation, with a view to significantly decreasing smoking prevalence. The study was retrospectively registered on 25 November 2024 (ISRCTN10207960).

Postprandial lipid testing is increasingly recognized as a marker of vascular health. However, its relationship with erectile dysfunction (ED) remains largely unexplored. Isolated postprandial dyslipidemia (IPD), in particular, may evade detection using conventional fasting-based assessments, despite potential atherogenic effects. To evaluate the association between IPD and erectile function, comparing the prevalence and severity of ED among men with IPD, combined dyslipidemia (CD), and those without dyslipidemia (WD). In this cross-sectional study, sexually active men aged ≥18 years underwent same-day fasting and postprandial lipid testing, as well as erectile function evaluation using the International Index of Erectile Function - Erectile Function domain (IIEF-EF) questionnaire. Dyslipidemia was defined according to the 2019 European Society of Cardiology/European Atherosclerosis Society criteria. Patients were categorized as WD (no dyslipidemia), IPD (postprandial abnormalities only), or CD (both fasting and postprandial abnormalities). Multivariable logistic regression was performed, adjusting for age, smoking status, BMI, and hypertension. The primary outcome was the prevalence of ED (IIEF-EF ≤25); secondary outcomes included ED severity and comparisons across lipid profile subgroups. Among 351 men, ED prevalence was higher in the IPD (55.1%) and CD (57.0%) groups compared to WD (32.8%; p < 0.001). Median (IQR) IIEF-EF scores were 26 (25-28) in the WD group, 22 (20-23) in the IPD group, and 21 (19-23) in the CD group. The differences between WD and both IPD and CD exceeded the minimal clinically important difference (4 points) and were statistically significant (p < 0.001). Adjusted analyses confirmed increased odds of ED in IPD (odds ratio [OR] = 2.36; 95% confidence interval [CI]: 1.41-3.96) and CD (OR = 2.58; 95% CI: 1.43-4.65) versus WD. ED severity was also greater in the IPD and CD groups. No differences emerged between IPD and CD in any outcome. Among IPD subtypes, elevated postprandial triglycerides were most common, but no single lipid abnormality was independently associated with ED severity. IPD is associated with both the prevalence and severity of ED, paralleling the impact of chronic dyslipidemia. Postprandial lipid testing may reveal hidden metabolic risks relevant to sexual health and should be considered in the evaluation of ED.