Search Results (261)

Background: Blood donation deferral poses a significant challenge to transfusion services worldwide, threatening blood supply adequacy and donor retention. Population-specific data on deferral epidemiology and subsequent donor return behavior in Saudi Arabia remain limited. This study aimed to characterize the prevalence, reasons, and demographic patterns of blood donation deferral at King Fahad Medical City (KFMC)—a major quaternary referral center in Riyadh—and to quantify the rate at which temporarily deferred donors re-engage with the donation process at the encounter level. Methods: A retrospective observational study was conducted on records of all registered volunteer blood donor encounters at KFMC from 1 January 2023 to 31 December 2024 (n = 60,290), extracted from the Hematos IIG blood bank information system. Donor demographics (age, sex, weight, nationality), deferral classification (temporary, permanent, indeterminate), deferral reason, pre-deferral donation frequency, and post-temporary-deferral donation frequency were analyzed. Inferential statistics employed the Chi-square test and Fisher’s exact test (significance threshold: p < 0.05). A multinomial logistic regression, restricted to the 10,681 encounters classified as temporarily deferred, identified correlates of post-deferral donation frequency, adjusted for donation frequency before deferral. Results: Of 60,290 registered donor encounters, 18,458 (30.6%) resulted in deferral. Male donors constituted 86.4% of deferrals; the 31–45-year age group accounted for 47.3%. The three leading deferral reasons were abnormal vital signs (39.4%), post-donation transfusion-transmitted infectious disease (TTID) screening reactivity (35.6%), and low hemoglobin (14.0%). Sex-stratified analysis revealed that among female donors, low hemoglobin (40.50%) exceeded abnormal vital signs (35.50%) as the leading reason. Among the 10,681 encounters classified as temporarily deferred, 86.70% did not return to donate within the observation window. In a multinomial regression restricted to this subgroup, donation frequency before deferral was the strongest correlate of return (OR 21.02, 95% CI 14.94–29.58 for three or more subsequent donations among donors with ≥3 prior donations vs. none), and deferral for abnormal vital signs was also associated with higher odds of return (OR range 3.55–4.60, all p < 0.001). Conclusions: Nearly one-third of blood donor encounters at this tertiary center resulted in deferral, with abnormal vital signs and TTID screening reactivity as the predominant reasons. The low re-engagement rate (13.30%) among temporarily deferred donors underscores a need for structured follow-up programs, particularly for first-time donors, for whom an established donation history was the strongest predictor of return. Sex-specific interventions—targeting hemoglobin optimization in female donors and cardiovascular risk factor awareness in male donors—are warranted to reduce the deferral burden and safeguard the blood supply. Full article

Healthy nutrition is pivotal for the prevention of atherosclerotic cardiovascular disease (ASCVD). In addition to traditional risk factors, other components, like low-grade chronic inflammation, play a pathogenetic role in ASCVD. Research efforts aim to identify low-grade chronic inflammation in patients with established ASCVD and in subjects with low ASCVD risk, and to validate effective nutritional strategies. Here, current nutritional approaches to counteract low-grade chronic inflammation related to ASCVD and possibly mitigated ASCVD risk are discussed, along with related molecular pathways and clinical biomarkers. Low-grade chronic inflammation results from a pro-inflammatory response promoted by large multiprotein complexes (inflammasomes). Within the ASCVD context, the nucleotide-binding oligomerization domain (NOD)-like receptor family pyrin domain-containing protein 3 (NLRP3) inflammasome is the most characterized protein complex, whose activation leads to increased release of downstream effectors (interleukin (IL)-1β, IL-18, IL-6). In the current clinical practice, high-sensitivity C-reactive protein (hsCRP) is used as a circulating biomarker for systemic inflammation, although it is not univocally associated with ASCVD. Some nutritional strategies have been shown effective to mitigate low-grade chronic inflammation and to reduce hsCRP, reducing in some cases ASCVD risk. The Mediterranean Diet and related trials showed that their beneficial effects on cardiovascular disorders could also be related to the anti-inflammatory properties of specific active compounds. Contradictory results have also been obtained, due to lack of standardization and to the specific nature of nutritional studies, which often rely on adherence and compliance of participants. Given the relevance of low-grade chronic inflammation for ASCVD risk, future work will need to increase awareness, identify and validate novel biomarkers, and implement novel effective nutrition strategies. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is caused by excessive fat accumulation in the liver (steatosis) and affects approximately 38% of adults globally. MASLD may progress from simple steatosis to fibrosis and cirrhosis and is closely related to other cardio-metabolic conditions (e.g., obesity and type 2 diabetes), posing a risk factor for cardiovascular disease. Currently, lifestyle modification and weight reduction remain the main initial treatment options. Existing data suggest that there is low awareness among patients regarding MASLD diagnosis and its subsequent management. Therefore, this study aimed to develop a rich understanding of the lived experiences, concerns, and support needs of adults with MASLD. Methods: A qualitative design was applied, utilizing semi-structured interviews. Adults living with MASLD were invited to talk about their diagnosis and discuss their lived experiences. Participants were interviewed by telephone or video call, and each interview was transcribed and analyzed with a reflexive thematic analysis approach. Results: Twenty-five adults with MASLD (age range: 24–79 years; 40% men) were interviewed. The emergent key themes related to communication and emotions at diagnosis; independently seeking further information; lived experiences post-diagnosis; support needs; and future concerns. Many participants reported receiving the diagnosis incidentally, and a number of issues were raised regarding lack of clarity at the point of diagnosis. Additional concerns included information obtainable via the internet, symptoms, social relationships, stigma, and lifestyle modification. Future anxieties related mainly to fears of disease progression, while support needs were predominantly focused on information and follow-up. Conclusions: The concerns and support needs identified by this study highlight key issues/themes that should inform education and support initiatives by relevant healthcare services aiming to improve the lived experiences and holistic management of adults with MASLD. Full article

Background: Increasing access to Electronic Health Records (EHRs) has enabled the development of Machine Learning (ML) models to predict early cardiovascular disease (CVD) risk. Nevertheless, real EHR data is usually limited in availability and distribution because of confidentiality issues, legal limitations, and insufficient access. Synthetic data generation has become a promising approach to overcome such difficulties. Objectives: This study proposes a Large Language Model (LLM)-guided retrieval-aware framework for generating realistic synthetic EHR data on a large scale to train ML models to predict cardiovascular risks accurately. Methods: The framework uses a Tabular Denoising Diffusion Probabilistic Model to learn the underlying distribution of the original dataset and generate an initial synthetic dataset. To improve the clinical plausibility of the generated data, a knowledge-guided refinement module with LLaMA 2 13B combined with Retrieval-Augmented Generation (RAG) is introduced. The LLM analyzes statistical trends in real and synthetic data while retrieving relevant medical information to detect and correct clinically implausible correlations. Results: Experimental findings show that the optimized synthetic dataset preserves important statistical features of the original data and achieves high performance in predicting CVD. Conclusions: Thus, the framework offers a scalable, privacy-conservative method for generating realistic synthetic healthcare data suitable for medical research. Full article

Background/Objectives: Suboptimal dietary patterns are among the leading modifiable contributors to global morbidity and mortality, particularly in cardiovascular disease, type 2 diabetes mellitus (T2DM), obesity, metabolic syndrome, and hypertension. Digital nutrition platforms have emerged to improve adherence to evidence-based dietary strategies; however, many systems lack structured optimization, processing-aware nutrient profiling, and explainable artificial intelligence (AI) mechanisms. The integration of large language models (LLMs) into digital health introduces conversational personalization but also risks hallucination and unsafe outputs without constraint enforcement. This study aimed to describe the system development, architecture, database infrastructure, optimization algorithms, explainability enforcement, and digital health implications of NutriSteppe-AI, a chatbot-first LLM-driven system for personalized health menu generation constrained by deterministic nutrient logic and processing-aware scoring. Methods: NutriSteppe-AI integrates: (1) a multi-source structured nutrient database of 20,000 food products with up to 130 tracked nutrients; (2) energy requirement estimation using the revised Harris-Benedict equation; (3) linear programming-based multi-objective optimization; (4) a Healthy Food Index (HFI; 0.5–5.0 scale) incorporating NOVA processing classification penalties; (5) traffic-light nutrient gating; and (6) a constrained LLM orchestration layer governed by structured API contracts. Algorithmic validation was performed using 10,000 simulated user profiles spanning diverse age, anthropometric, activity, dietary exclusion, and budget parameters. Results: The system achieved 96.8% full constraint satisfaction with macronutrient mean absolute errors of 11.60% (energy), 18.86% (protein), 16.26% (fat), and 20.91% (carbohydrates). Incorporating NOVA processing penalties reduced ultra-processed food HFI scores by 0.73 points (p < 0.001). Median optimized menu HFI improved from 3.6 to 4.3. Median system latency was 1.8 s. Explainability validation confirmed 100% deterministic alignment with zero hallucinated numeric claims. Conclusions: NutriSteppe-AI demonstrates that LLM-driven nutrition chatbots can achieve deterministic, explainable, and clinically aligned performance when governed by structured optimization, processing-aware scoring, and explainability enforcement. This architecture provides scalable digital health infrastructure for cardiometabolic disease prevention in diverse populations. Full article

Background/Objectives: Previous publications have primarily examined the individual roles of nutrients during fetal development. However, growing evidence suggests that one-carbon (1C) metabolism nutrients, including choline and key B vitamins, act synergistically within interconnected metabolic pathways that modulate epigenetic regulation and may have implications for the health of future generations. Methods: This narrative integrative review examined evidence relating to the roles of choline and B vitamins (B1, B2, B6, folate (B9) and B12) in fetal development and offspring health. Peer-reviewed literature was identified through PubMed, Science Direct and Semantic Scholar. Results: Current evidence indicates that periconceptional and maternal intake and status of 1C metabolism nutrients are associated with DNA methylation processes involved in developmental programming and the risk of non-communicable diseases (NCDs) in childhood and adulthood. Habitual intakes of several 1C metabolism nutrients are frequently below recommended levels during pregnancy and lactation, particularly for choline and folate. Inadequate intakes, each contributing differently to 1C metabolism, may disrupt 1C metabolic pathways and alter DNA methylation patterns during critical windows of fetal programming. Homocysteine metabolism is intricately linked to 1C metabolism and is modulated by choline and B vitamins. Collectively, these pathways have potential implications for the health of the next generation, including effects on growth, neural tube closure, brain development and increased susceptibility to diseases later in life, e.g., cardiovascular disease, diabetes, obesity and other chronic conditions. Adequate maternal intakes of choline and B vitamins may help mitigate the ‘early life origin’ of certain NCDs by promoting healthy neurodevelopment, reducing inflammation, and regulating central metabolic pathways. Conclusions: Greater awareness of the roles and importance of 1C metabolism nutrients, including choline and key B vitamins (B1, B2, B6, folate and B12), during the early life course is warranted. Furthermore, there is also a need for organizations and policy makers to formalize intake recommendations for 1C metabolism nutrients beyond the individualized simplicity of folate/folic acid, and to extend this to include other methyl-donor nutrients with epigenetic effects, such as choline and key B vitamins, given their interconnected roles in 1C metabolism and fetal development. Full article

Background: Cardiovascular diseases (CVDs) are the leading cause of death in Saudi Arabia, and public knowledge of risk factors and warning signs supports early detection and prevention. This study aimed to assess CVD knowledge and its demographic predictors among adults in the Jazan region. Methods: A cross-sectional study was conducted among 382 adults (≥18 years) between February and April 2025. A questionnaire adapted from prior validated instruments assessed CVD awareness, knowledge of 11 risk factors and 10 warning signs, perceptions, and practices. Total knowledge scores (0–21) were dichotomized as adequate (≥8) versus inadequate (<8). Mann–Whitney U and Kruskal–Wallis tests were used for bivariate analysis, followed by binary logistic regression. Results: Most participants (89.5%) had heard of CVD, yet 53.7% had inadequate knowledge, and only 9.9% demonstrated good knowledge (≥15). The median total knowledge score was 7 (IQR 2–11) out of 21, with warning-sign knowledge (2.96/10) lower than risk-factor knowledge (3.95/11). Overweight/obesity (52.6%), hypertension (51.3%), and smoking (49.5%) were the most recognized risk factors; chest pain (47.6%) and shortness of breath (46.1%) were the most recognized warning signs. University education (aOR = 2.44, 95% CI 1.23–4.85, p = 0.011) and family history of chronic disease (aOR = 2.26, 95% CI 1.32–3.85, p = 0.003) were the only independent predictors of adequate knowledge. Conclusions: More than half of the surveyed adults in the Jazan region had inadequate CVD knowledge despite high general awareness. These findings suggest that targeted education using digital platforms and primary care providers may help improve knowledge of risk factors and warning signs in the region. Full article

Background/Objectives: Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide. Individuals with hypertension (HTN) and type 2 diabetes mellitus (T2DM) are at particularly high risk; however, awareness of cardiovascular risk within the broader community and among high-risk subgroups remains suboptimal. This study aimed to assess CVD risk awareness and its correlates among adults in the Northern Border Region of Saudi Arabia, with a particular focus on individuals with HTN and/or T2DM. Methods: A descriptive, quantitative, cross-sectional survey was conducted among adults aged 18–50 years residing in the Northern Border Region of Saudi Arabia. An anonymous online questionnaire was distributed via social media between October 2025 and January 2026. The survey incorporated a 22-item scale assessing HTN knowledge, T2DM knowledge, and CVD risk awareness (Heart Disease Fact items). Participants were categorized according to self-reported diagnosis (no diagnosis, HTN, T2DM, or both). Descriptive statistics, non-parametric tests, and multivariable regression analyses were used to evaluate knowledge scores and predictors of CVD risk awareness. Results: A total of 458 participants completed the survey. Overall knowledge was moderate (mean 12.40/22; 56.4%), with relatively higher scores for HTN (73.2%) and T2DM knowledge (68.8%), but markedly lower CVD risk awareness (30.8%). Fewer than half of participants correctly answered key CVD items, particularly those related to asymptomatic disease progression and lipid (HDL) concepts. Only 21.6% achieved good awareness (≥75%). In multivariable analyses, higher educational level, positive family history of cardiometabolic disease, and the presence of HTN and/or T2DM were independent predictors of higher awareness. Conclusions: CVD risk awareness is suboptimal among adults in the Northern Border Region, including those with established HTN and T2DM. The observed gap between disease-specific knowledge and CVD risk awareness highlights the need for targeted, structured risk communication strategies in primary care, particularly for individuals with lower educational attainment and no family history of CVD. Full article

Background: Older adults undergoing non-cardiac surgery are vulnerable to perioperative complications, but the prognostic value of routine echocardiographic markers in high-acuity cohorts remains incompletely defined. Methods: This secondary analysis of a prospective cohort included 503 consecutive adults with known cardiovascular disease undergoing non-cardiac surgery, characterized by a high proportion of urgent presentations. Patients were stratified by age (geriatric, ≥65 years; non-geriatric, <65 years). The primary endpoint was major in-hospital adverse events (MIAEs), defined as a composite of in-hospital death, surgical reintervention, and postoperative acute kidney injury (AKI). Postoperative creatinine was not routinely measured in stable patients discharged early; therefore, renal outcomes were interpreted strictly as available-case analyses (n = 364). Results: MIAEs occurred more frequently in geriatric than in younger patients (45.5% vs. 30.8%). Within the geriatric cohort, patients with reduced LVEF (<50%) had lower MAPSE values and higher crude rates of AKI, death, and MIAE than those with LVEF ≥ 50%. In multivariable analyses, reduced LVEF was associated with MIAE, although this small subgroup was susceptible to statistical overfitting. MAPSE reflected longitudinal systolic dysfunction but did not retain independent prognostic value after adjustment. Conclusions: In this pilot subgroup analysis of high-acuity patients, reduced preoperative LVEF (<50%) served as a clinical flag identifying a high-risk geriatric phenotype with increased cardiorenal vulnerability. Given the event-enriched available-case denominator, these findings should be considered hypothesis-generating observations intended to increase clinical awareness. Full article

Background: Anaplasmosis is an emerging tick-borne infection that typically presents as a non-specific febrile illness, with variable degrees of cytopenias and liver tests abnormalities. Severe complications remain atypical and uncommon. Case Report: We report a case of acute pulmonary embolism (PE) occurring during confirmed anaplasmosis in a 73-year-old male with no traditional thromboembolic risk factors. The patient presented with fever, constitutional symptoms, thrombocytopenia, leukopenia, and abnormal liver tests, raising suspicion for a tick-borne illness. Despite early clinical improvement on doxycycline, persistent tachycardia triggered further evaluation and uncovered an acute PE. Comprehensive workup at admission and repeated 14 months later excluded inherited and acquired thrombophilias, malignancies, autoimmune diseases, and alternative infectious etiologies. The patient was treated with doxycycline 100 mg orally twice daily for 10 days and anticoagulation with unfractionated heparin followed by 6 months of apixaban for a first episode of provoked PE. He attained complete clinical recovery without recurrence of thrombosis at the two-year follow-up. Discussion: Infectious diseases are increasingly recognized as contributors to thrombosis through inflammation-mediated hypercoagulability and endothelial dysfunction. Pulmonary involvement in anaplasmosis typically manifests as pneumonitis, pneumonia or acute respiratory distress syndrome, but thrombotic complications such as PE are exceedingly rare. This case highlights a rare but clinically significant vascular complication of anaplasmosis and underscores the importance of considering thromboembolic events in patients with persistent or unexplained tachycardia. Conclusions: As the incidence of anaplasmosis continues to rise, greater awareness of its potential cardiovascular manifestations is essential. Early recognition and prompt treatment with doxycycline remain critical, while further studies are needed to better define the thrombotic risk associated with this infection. Full article

Ischemic Heart Disease (IHD) is the leading cause of cardiovascular mortality worldwide. Early detection of ischemic changes using electrocardiogram (ECG) signals is vital for timely intervention and enhanced clinical outcomes. However, the diagnosis of IHD varies significantly between men and women. Women often present with atypical symptoms, and their cardiovascular risk is frequently underestimated, which leads to delayed diagnosis. Also, existing approaches face challenges in subtle early-stage abnormalities, single-lead ECG presentation, and the limited interpretability of deep learning models. These cause significant challenges to the accurate diagnosis of IHD. To address these, this study proposes a gender-aware framework, Gender-Aware Morphology Encoder Network (GAMENet), for early ischemic heart disease detection using 12-lead ECG signals with clinical metadata. A novel GAMENet is developed using the PTB-XL database. The Adaptive Morphology Deviation Encoder (AMDE) through Morphology Segment Extraction (MSEG-R) using R-Peak anchoring, isolates clinically relevant waveform components (P-wave, QRS complex, ST-segment, and T-wave) from the preprocessed ECG signals. The feature vector of morphology features is passed through dense layers with dropout regularization and a SoftMax classifier. Statistical and comparative analysis ensures that the proposed framework enables accurate IHD classification and improved interpretability. Full article

Diabetes mellitus is a complex metabolic disorder whose management has moved from glycemic control to the control of risk factors through the use of new antihyperglycemic drugs with pleiotropic effects. Despite the multiple cardio–renal benefits of sodium-glucose co-transporter 2 (SGLT2) inhibitors, their prescription is often avoided due to concerns regarding side effects. This review aims to discuss the multiple benefits of SGLT2 inhibitors in balance with one of the most concerning side effects, the risk of euglycemic diabetic ketoacidosis (EDKA). A literature search was performed to identify and select articles relevant to this topic. We accessed several databases, including PubMed, Web of Science and Scopus, using appropriate keywords. We selected and evaluated randomized controlled trials, retrospective studies, systematic reviews and meta-analysis published between 2014 and 2024 supporting the multifaceted benefits of SGLT2 inhibitors and the limitations of their recommendations and focusing on the risk of EDKA. Initially designed as antidiabetic agents, SGLT2 inhibitors have demonstrated important cardio–renal benefits, these drugs being the first-line medication in patients with established cardiovascular disease, heart failure and chronic kidney disease. SGLT2 inhibitors are associated with some potential side effects, but with contradictory data concerning their prevalence and clinical relevance. From the possible side effects, EDKA is a life-threatening metabolic emergency whose incidence and recognition has increased, in particular with the use of SGLT2 inhibitors. These drugs can cause this disorder through several mechanisms, including reduced insulin secretion and increased glucagon levels, leading to free fatty acid production, which generally occurs in the presence of some risk factors such as reduced dietary carbohydrates, intercurrent illnesses, surgical stress and alcohol consumption. Through awareness of these risk factors as well as of the clinical symptoms, this condition could be promptly avoided or managed and SGLT2 inhibitors could be safely used. Full article

Adverse childhood events (ACEs) represent a major public health burden in the United States, as exposure to ACEs increases the risk of mental health disorders, cardiovascular disease, obesity, and cancer and can greatly affect quality of life. Although the effects of ACEs on physiology are complex, significant evidence suggests that ACEs may affect the immune system later in life. As the field of immunotherapy gains prominence in cancer treatment, it becomes imperative to explore how ACEs may impact cancer immunotherapy. Brain cancer, especially glioblastoma multiforme (GBM), has a very poor prognosis and remains a challenging disease to treat. Immunotherapy approaches are being actively investigated. To address this, we aim to raise awareness of the potential connection between ACEs, brain cancer, and cancer immunotherapy. Through a review of the current biomedical literature, we synthesized current findings into a commentary on how early-life adversity may influence the immune response within the central nervous system. It is the intention of this commentary to generate hypothesis-driven research within the nascent and emerging field of neuro-psycho-immunology in neuro-oncology. Given that the relationship between ACEs and brain cancer immunotherapy remains vastly understudied, this commentary has significant potential to generate insightful discussions among clinicians and scientists to guide further clinical and basic research towards anticipating which patients stand to receive the most benefit from immunotherapy. Full article

Heart disease remains one of the leading causes of mortality worldwide, creating a strong need for reliable population-scale risk prediction models for large-scale screening and preventive monitoring. However, existing machine learning and deep learning approaches often struggle under severe class imbalance, data leakage risks, and unstable precision–recall trade-offs, limiting reliability in population-scale health-monitoring settings. To address these challenges, this study proposes a precision-aware Dual-Branch FT-Transformer framework for cardiovascular risk prediction using the BRFSS-2024 dataset. The proposed architecture separates recall-oriented detection and precision-oriented verification through two specialized prediction heads and integrates them using a lightweight gating mechanism trained strictly within training folds to prevent information leakage and enable controlled error arbitration. Under a strict leakage-safe 5-fold cross-validation protocol, the proposed model achieves an F1-score of 0.43, recall of 0.59, and AUPRC of 0.38 at a fixed threshold of 0.50 while reducing false negatives by more than 50% compared to LightGBM without excessive false positives. Although some baseline models achieve higher AUROC values, the proposed framework demonstrates more balanced and clinically meaningful precision–recall behaviour at operational screening thresholds. Additional evaluation on an independent NHANES cohort under the same leakage-safe re-training protocol further suggests robustness across heterogeneous population-health settings. Overall, the proposed dual-objective learning framework provides a practical and robust approach for imbalanced tabular prediction in population-scale cardiovascular risk assessment. Full article

Background: Hypertension is one of the most common noncommunicable diseases. Objectives: This research assessed the magnitude of hypertension among young adults, identified its key determinants, and explored potential strategies adopted for prevention. Methods: A cross-sectional design was employed, including 1606 participants aged 18 years and older, recruited through convenience sampling from universities and community settings. Data were collected using a content-validated questionnaire covering sociodemographic information, personal and family medical history, and lifestyle habits. Results: Of the participants, 993 (61.8%) reported hypertension, nearly double previous national estimates. Male gender, age ≥ 30 years, and family history were significant risk factors, along with smoking, alcohol use, sedentary lifestyle, and unhealthy diet, while physical activity and dietary modification were protective. Despite high prevalence, only 22.1% had controlled blood pressure and 17.8% adhered to medication, with 51.5% relying on herbal remedies. Conclusions: These findings highlight the urgent need for early screening, youth-focused awareness, and culturally tailored interventions to reduce hypertension and prevent long-term cardiovascular complications. Hypertension among young adults in the UAE is a major public health concern, requiring integrated strategies combining education, lifestyle modification, and medical management to improve outcomes. Full article