Search Results (463)

Background/Objectives: Direct oral anticoagulants (DOACs) are now the guideline-recommended alternative to vitamin K antagonists (VKAs) for long-term anticoagulation in patients with non-valvular atrial fibrillation. However, accurately assessing their impact on ischemic stroke outcomes remains challenging, primarily due to uncertainty regarding anticoagulation status at the time of hospital admission. This preliminary study addresses this gap by using point-of-care testing (POCT) to confirm DOAC activity at bedside, allowing for a more accurate comparison of 90-day functional outcomes between anticoagulated and non-anticoagulated stroke patients. Methods: We conducted a retrospective cohort study of 786 ischemic stroke patients admitted to the University of Pécs between February 2023 and February 2025. Active DOAC therapy was confirmed using the ClotPro^® viscoelastic testing platform, with ecarin Clotting Time (ECT) employed for thrombin inhibitors and Russell’s Viper Venom (RVV) assays for factor Xa inhibitors. Patients were categorized as non-anticoagulated (n = 767) or DOAC-treated with confirmed activity (n = 19). Mahalanobis distance-based matching was applied to account for confounding variables including age, sex, pre-stroke modified Rankin Scale (mRS), and National Institutes of Health Stroke Scale (NIHSS) scores at admission and 72 h post-stroke. The primary outcome was the change in mRS from baseline to 90 days. Statistical analysis included ordinary least squares (OLS) regression and principal component analysis (PCA). Results: After matching, 90-day functional outcomes were comparable between groups (mean mRS-shift: 2.00 in DOAC-treated vs. 1.78 in non-anticoagulated; p = 0.745). OLS regression showed no significant association between DOAC status and recovery (p = 0.599). In contrast, NIHSS score at 72 h (p = 0.004) and age (p = 0.015) were significant predictors of outcome. PCA supported these findings, identifying stroke severity as the primary driver of outcome. Conclusions: This preliminary analysis suggests that ischemic stroke patients with confirmed active DOAC therapy at admission may achieve 90-day functional outcomes comparable to those of non-anticoagulated patients. The integration of bedside POCT enhances the reliability of anticoagulation assessment and underscores its clinical value for real-time management in acute stroke care. Larger prospective studies are needed to validate these findings and to further refine treatment strategies. Full article

Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more complex models incorporating biomarkers (e.g., NT-proBNP, sST2), imaging, and artificial intelligence techniques. In acute HF, models like EHMRG and STRATIFY aid early triage, while in chronic HF, tools like SHFM and BCN Bio-HF support long-term management decisions. Despite their utility, most models are limited by poor generalizability, reliance on static inputs, lack of integration into electronic health records, and underuse in clinical practice. Novel approaches involving machine learning, multi-omics profiling, and remote monitoring hold promise for dynamic and individualized risk assessment. However, these innovations face challenges regarding interpretability, validation, and ethical implementation. For prognostic models to transition from theoretical promise to practical impact, they must be continuously updated, externally validated, and seamlessly embedded into clinical workflows. This review emphasizes the potential of prognostic models to transform HF care but cautions against uncritical adoption without robust evidence and practical integration. In the evolving landscape of HF management, prognostic models represent a hopeful avenue, provided their limitations are acknowledged and addressed through interdisciplinary collaboration and patient-centered innovation. Full article

Background: Despite significant advancements in diabetes care, many individuals with type 2 diabetes (T2D) do not receive optimal care and treatment. Digital interventions promoting behavioral changes have shown promising long-term results in supporting healthier lifestyles but are not implemented in most healthcare offerings, maybe due to lack of general practice support and collaboration. This study evaluates the efficacy of the Digital, Individualized, and Collaborative Treatment of T2D in General Practice Based on Decision Aid (DICTA), a randomized controlled trial integrating a patient-centered smartphone application for lifestyle support in conjunction with a clinical decision support (CDS) tool to assist general practitioners (GPs) in optimizing antidiabetic treatment. Methods: The present randomized controlled trial aims to recruit 400 individuals with T2D from approximately 70 GP clinics (GPCs) in Denmark. The GPCs will be cluster-randomized in a 2:3 ratio to intervention or control groups. The intervention group will receive one year of individualized eHealth lifestyle coaching via a smartphone application, guided by patient-reported outcomes (PROs). Alongside this, the GPCs will have access to the CDS tool to optimize pharmacological decision-making through electronic health records. The control group will receive usual care for one year, followed by the same intervention in the second year. Results: The primary outcome is the one-year change in estimated ten-year cardiovascular risk, assessed by SCORE2-Diabetes calculated from age, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol, age at diabetes diagnosis, HbA1c, and eGFR. Conclusions: If effective, DICTA could offer a scalable, digital-first approach for improving T2D management in primary care by combining patient-centered lifestyle coaching with real-time pharmacological clinical decision support. Full article

Background/Objectives: Protecting students’ mental health during university is essential for their future quality of life. Therefore, diet should be emphasized as a complementary and preventive strategy in supporting and maintaining mental health. This study aimed to examine the association between dietary inflammatory and antioxidant indices and mental health indicators (depression, anxiety, stress, and well-being) in university students. Methods: This cross-sectional study included 907 university students. We collected dietary data using a 24 h recall. Based on this data, we used 33 food parameters to calculate the Dietary Inflammatory Index (DII) and 6 antioxidant nutrients to calculate the Dietary Antioxidant Index (DAI). We evaluated mental health using the Depression, Anxiety, and Stress Scales-21 (DASS-21), and assessed well-being using the World Health Organization Five Well-Being Index (WHO-5). Results: Overall, 62.4% of participants reported symptoms of depression, 56.2% anxiety, and 40.7% stress. Anxiety and stress levels were significantly higher among females compared to males (p < 0.001 and p = 0.005, respectively). In fully adjusted models, depression scores were significantly higher in the highest DII tertile compared to the lowest (B = 1.74; 95% CI: 0.24–3.26), while well-being was lower (B = −0.82; 95% CI: −1.65 to −0.00). For DAI, participants in tertile 2 had significantly lower anxiety (B = −1.38; 95% CI: −2.63 to −0.14), depression (B = −1.69; 95% CI: −3.19 to −0.19), and stress (B = −1.70; 95% CI: −3.22 to −0.18) scores compared to tertile 1. No significant association was found between DAI and well-being. Conclusions: In this study, university students’ pro-inflammatory diets were associated with poorer mental health profiles. Enhancing the diet’s anti-inflammatory potential may be a promising strategy to support mental health in this population. Full article

Background: Many risk factors for cancer therapy-related cardiovascular toxicity overlap with risk factors for atherosclerosis. According to the ESC 2022 Cardio-Oncology Guidelines, coronary computed tomography angiography and coronary artery calcium score are not recommended as part of routine risk assessment prior to oncological treatment. The aim of this study was to prospectively assess the influence of coronary artery calcium score (CAC score) on cancer therapy-related cardiac dysfunction in patients with moderate and high risk of cardiovascular toxicity, qualified for anthracycline treatment. Methods: In all patients, risk factors were collected, laboratory tests, echocardiography with global longitudinal strain (GLS) assessment and coronary artery tomography with coronary artery calcium score were performed. A total of 80 patients were included in the study, of which 77 (96.25%) were followed for an average of 11.5 months. The mean age at baseline was 60.5 years and 72 (93.51%) were women. Results: During observation, five patients (6.49%) died, including two due to heart failure and three due to cancer progression. The majority of patients (59, 76.6%) had breast cancer, 11 (14.3%) were diagnosed with sarcoma and seven (9.1%) with lymphoma. According to the HFA-ICOS risk score, 40 patients (51.9%) were classified as moderate risk (MR), and 37 patients (48.1%) as high risk (HR) for cancer therapy-related cardiovascular toxicity. A CAC score greater than 100 was calculated in 17 (22.1%) patients and greater than 400 in three (3.9%) patients. The CAC score above zero was more common in older patients and in patients classified as high risk (p < 0.001). There was also a significant association between CAC score and hypertension, hyperlipidemia, chronic kidney disease, and the level of NT-proBNP. During 12-month follow-up, mild CTRCD occurred in 38 (49.4%) patients, moderate CTRCD was diagnosed in seven (9.1%), and severe in three (3.9%) patients. In the univariable analysis, CTRCD was more common in the high-risk group (p = 0.005) and in patients with a CAC score greater than zero (p = 0.036). In multivariable analysis, the incidence of CTRCD remains higher in the CAC score > 0 group, even after adjusting for age, hypertension, and hyperlipidemia. In this study group, the CTRCD rates increased with the HFA-ICOS risk score. Conclusions: In moderate and high-risk patients, a coronary artery calcium score greater than zero was identified as a significant risk factor for the development of cancer therapy-related cardiac dysfunction during anthracycline-based treatment. Furthermore, the HFA-ICOS risk score demonstrated good correlation with the incidence of CTRCD in this study, supporting its validity as a predictive tool in patients receiving anthracycline therapy. Full article

Addressing climate change requires not only knowledge but also psychological resilience. This study examined whether integrating Mental Mode Management (MMM) self-regulation training with climate education improves pro-environmental outcomes and emotional responses to climate change. In a randomised 2 × 2 design, 44 participants were assigned to either a control group (CG; n = 21), which received a six-week climate education programme, or an experimental group (MMM; n = 23), which received the same education plus MMM training. Pro-environmental attitudes, behaviours, carbon emissions, climate change anxiety, mindfulness, and executive functions were assessed at baseline and post-intervention. A follow-up was also conducted six months later. Both groups showed increased pro-environmental attitudes post-intervention (η² = 0.3) and reduced food-related emissions (η² = 0.107). No changes were observed in pro-environmental behaviour scores or global carbon footprint. While neither intervention affected overall climate anxiety or cognitive impairment, functional impairment increased in the CG and decreased in the MMM group (η² = 0.177), with mindfulness facet acting with awareness moderating this effect. These findings contribute to sustainability research by showing that integrating climate education with psychological training enhances environmental awareness and fosters emotionally resilient engagement with climate challenges, supporting individual-level contributions to broader sustainability goals. Full article

Background: Cognitive impairment (CI) is a common and disabling symptom in patients with relapsing–remitting multiple sclerosis (RRMS), potentially emerging at any stage, including preclinical phases. Despite its impact on quality of life, CI often goes unrecognized, as clinical follow-up typically focuses on motor and sensory symptoms. Validated tools, such as the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) and patient-reported outcomes (PROs), should be integrated into routine evaluations beyond the Expanded Disability Status Scale (EDSS). Objective: The objective of this study was to evaluate cognitive impairment and quality of life in patients with RRMS using the BICAMS and PROs. Methods: This cross-sectional, descriptive study included patients with RRMS under follow-up at a tertiary hospital in San Luis Potosí, Mexico. Participants underwent cognitive screening with the BICAMS battery and completed the MSQoL-54 (quality of life), FSMC (fatigue), and MSIS-29 (functional impact) scales. Statistical analyses included ANOVA, the Kruskal–Wallis test, and Pearson correlations. Results: Nineteen patients were evaluated (73.7% female, mean age 36.5 ± 8.9 years). BICAMS results showed variable cognitive performance, with no significant differences across treatment groups for processing speed (p = 0.222), verbal memory (p = 0.082), or visuospatial memory (p = 0.311). A significant correlation was found between verbal and visuospatial memory (r = 0.668, p = 0.002). Total quality of life differed significantly across treatments (F = 8.007, p = 0.029), with a strong correlation between overall quality of life and general health perception (r = 0.793, p < 0.001). Fatigue and MSIS scores showed no association with treatment. Conclusions: Cognitive impairment is common in RRMS and can be detected using brief assessment tools, such as the BICAMS. Incorporating cognitive screening and PROs into clinical practice is essential to guide comprehensive management. Full article

Ulcerative colitis (UC) is a subtype of inflammatory bowel disease (IBD) that has been associated with overconsumption of calories and lipids, compared to the healthy population, and summer temperatures have been reported to be closely related to the prevalence of UC. To evaluate the effects of dietary and lifestyle factors on UC, a combination of 2.0% dextran sulfate sodium (DSS), a high-fat/high-sugar diet, and exposure to high temperature and humidity was used to construct mouse models of UC. Changes in body weight, disease activity index (DAI) scores, histopathological analysis, serum lipid levels, serum diamine oxidase (DAO), and D-Lactate (D-LA) levels, as well as the expression of inflammatory cytokines and tight junction proteins in colonic tissue, were all assessed to study the impacts of the high-fat/high-sugar diet and high-temperature/high-humidity exposure on the progression of UC. The symptoms observed in the UC mouse model induced by 2.0% DSS alone were similar to those seen in patients with UC, while the high-fat and high-sugar diet, along with humid and hot exposure, exacerbated DSS-induced UC in the mice. This included more severe histopathological damage to the colon tissue, increased expression of pro-inflammatory cytokines (IL-6, IL-17A, and IL-1β), and a more significantly compromised intestinal barrier, characterized by the destruction of ZO-1 and elevated levels of DAO and D-LA. Additionally, the high-fat/high-sugar diet and high-temperature/high-humidity exposure led to further disturbances in glucose and lipid metabolism in the mice, which were not observed in those treated with DSS alone. This study is the first to investigate the effects of a high-fat/high-sugar diet and high-temperature/high-humidity exposure on the progression of UC. Full article

Background/objectives: The interplay between genetic factors and nutritional patterns is critical in understanding metabolic health. This analysis evaluated the potential reciprocal relationships between the TNF-α -308 G/A gene polymorphism, the Composite Dietary Antioxidant Index (CDAI), and insulin-related variables in Spanish adults with obesity. Methods: A cross-sectional analysis was conducted in 292 adults with obesity. Anthropometric, biochemical, and dietary variables were assessed. TNF-α -308 G/A genotyping was performed. Associations and potential interactions between CDAI and genotype on insulin and homeostatic model assessment for insulin resistance (HOMA-IR) were examined using multivariate regression and two-way ANOVA. Results: Higher CDAI scores were significantly associated with lower insulin levels (p < 0.001) and HOMA-IR (p < 0.001), regardless of genotype. Carriers of the A allele (GA/AA) showed a non-significant trend toward higher insulin levels (p = 0.087) and a steeper decrease in insulin levels with increasing CDAI, with a significant interaction observed between TNF-α genotype and CDAI (interaction p = 0.003). Multivariate analyses confirmed that CDAI and TNF-α genotype were independently associated with insulin and HOMA-IR levels. However, interaction terms were not consistently significant across all models. Conclusions: These findings emphasize the potential of antioxidant-rich diets to help modulate the influence of pro-inflammatory genotypes on insulin resistance, highlighting the relevance of integrating genetic and dietary factors in managing obesity-related metabolic risks. Further studies are warranted to confirm these preliminary findings and to better understand the mechanisms underlying gene–diet interactions in metabolic regulation. Full article

Background/Objectives: We aimed to identify the factors associated with clinically important changes in quality of life (QoL) of real-world heart failure (HF) patients. Methods: This is a single-centre, prospective cohort study including 419 patients at an HF clinic between January 2013 and February 2020. QoL was assessed regularly using Minnesota Living with Heart Failure Questionnaire (MLHFQ). We used five nested linear mixed-effects models to account for QoL measurements between patients and within-patient. Models were adjusted for time, sociodemographic factors, comorbidities, self-care adherence, and HF severity factors. Results: Median age was 78 years, 54.4% of patients were female, and 49.6% had left ventricle ejection fraction ≥ 50%. At baseline, 62.5% of patients were New York Heart Association (NYHA) class II. Median N-terminal-pro-B type natriuretic peptide level was 1454 pg/mL. Mean MLHFQ total score at baseline was 25 points (95%CI: 22.97–27.60). Having an implanted cardiac resynchronization therapy-pacemaker (CRT-P) was associated with moderate to large improvement in QoL (−13.55 points, 95%CI: −22.45–−4.65). NYHA class II and estimated glomerular filtration rate < 30 mL/min/1.73 m² were associated with small to moderate QoL deterioration (9.74 points, 95%CI: 6.74–12.75 and 5.82 points, 95%CI: 1.17–10.47, respectively). NYHA classes III or IV and a recent HF hospitalization were associated with large to very large QoL deterioration (28.39 points, 95%CI: 23.82–32.96; 60.59 points, 95%CI: 34.46–86.72; and 26.91 points, 95%CI: 21.80–32.03, respectively). Conclusions: CRT-P implantation, NYHA class and HF hospitalization are associated with the most clinically important QoL changes. Full article

Background: A growing body of evidence suggests that diet can modify Parkinson’s disease (PD) outcomes, although there is disagreement about what should be included and excluded in such a diet. Existing evidence suggests that adherence to the MIND and Mediterranean (MEDI) diets are associated with reduced PD symptoms, but only a few variables from the adherence scales are responsible for the statistically observed improvement. Objectives: The goal was to use patient-reported outcomes in a large cohort to identify the foods and dietary patterns (PRO diet) most strongly associated with the fewest PD symptoms over time, and to develop a composite adherence scale to enable comparisons between MEDI, MIND, and PRO. Methods: Data were obtained from the prospective longitudinal natural history study and from Modifiable Variables in Parkinsonism (MVP)—a study designed to identify behaviors associated with patient-reported outcomes (PRO-PD). Upon the completion of the binary and food frequency data collection, using various predictive models and considering congruence with historical data, the PRO diet was created via an iterative process. Our goal was to create a new scale and compare its performance to the existing MIND and MEDI scores. The comparison was made at baseline, using the regression models for PRO-PD and the different scales as the predictors. The models were compared via the Akaike Information Criterion (AIC). To examine whether baseline adherence levels predicted subsequent symptom trajectories, the baseline PRO diet adherence and subsequent slope of progression were evaluated. Results: Data from 2290 individuals with PD were available for this analysis. The Mediterranean and MIND diets showed almost identical effects. For both the diets, the effect they had on non-motor symptoms was about twice the effect on motor symptoms. The slopes for the total PRO-PD for MEDI, MIND, and PRO-21 were −64.20467, −64.04220, and −28.61995, respectively. The AIC value differences were substantial (>2), indicating meaningful improvements in the model fit for total PRO-PD, as follows: MEDI: 28,897.24, MIND: 28,793.08, and PRO-21: 27,500.71. The subset of individuals who were most adherent to the PRO-21 diet at baseline had the slowest subsequent progression, as measured by a 43% reduced PRO-PD slope, compared to the less adherent groups. Conclusions: The PRO-21 outperformed the MIND and MEDI diets in the model fit, overcoming the ceiling effects and showing orders of magnitude and superior explanatory power for variance in PD outcomes, despite the smaller per-unit effect sizes. However, its rigorous demands may introduce barriers related to cost, feasibility, and sustainability, underscoring the need for future intervention trials to assess real-world feasibility, adherence, side effects, and clinical impact. Full article

Background/Objectives: The tumor microenvironment (TME) plays a critical role in cancer progression by shaping immune responses and influencing patient outcomes. We hypothesized that the relative proximity of specific immune cell pairs to cancer cells within the TME could help predict their pro- or anti-tumor functions and reflect clinically relevant immune dynamics. Methods: We analyzed imaging mass cytometry (IMC) data from lung adenocarcinoma (LUAD) and triple-negative breast cancer (TNBC) cohorts. For each immune cell pair, we calculated a relative distance (RD) score, which quantifies the spatial difference in proximity to cancer cells. We assessed the prognostic and predictive significance of these RD-scores by comparing them with conventional features such as cell fractions, densities, and individual cell distances. To account for variations in cell abundance, we also derived normalized RD-scores (NRD-scores). Results: RD-scores were more strongly associated with overall patient survival than standard immunological metrics. Among all immune cell pairs, the RD-score comparing the proximity of B cells to that of intermediate monocytes showed the most significant association with improved survival. In TNBC, RD-scores also improved the distinction between responders and non-responders to immunochemotherapy and chemotherapy. Normalized RD-scores reinforced these findings by minimizing the influence of cell density and further highlighting the importance of immune cell spatial relationships. Conclusions: RD-scores offer a spatially informed biomarker that outperforms traditional metrics in predicting survival and treatment response. This approach provides a new perspective on immune cell behavior in the TME and has potential utility in guiding personalized cancer therapies and patient stratification. Full article

Traumatic brain injury (TBI) affects millions of people worldwide and often results in long-term disabilities. Clinical outcomes vary widely even among patients with similar injury severity, partly due to systemic neuroinflammatory responses mediated by pro- and anti-inflammatory cytokines. Genetic polymorphisms in cytokine-coding genes may influence cytokine expression, thereby affecting rehabilitation and prognosis. We analyzed genetic polymorphisms in the TNF-α, IL-6, IL-6 receptor, IL-1β, and IL-10 genes in 28 subacute TBI patients undergoing rehabilitation. Clinical outcomes were assessed using the Glasgow Outcome Scale Extended (GOSE) and domain-specific scales for cognitive, motor, and functional recovery. Results were correlated with genetic profiles to identify potential predictive biomarkers. The IL-6-174 (GG) and IL-6R 1073 (AA) genotypes correlated with worse GOSE scores (p = 0.02 and p = 0.01, respectively). Co-segregation of IL-6-174 - IL-6R 1073 G-A alleles was linked to poorer outcomes (p = 0.01). Patients with the TNF-α-308 (GA) genotype showed less improvement in Barthel and Mobility scores (p = 0.001 and p = 0.01, respectively) and had a higher incidence of post-traumatic confusional state after rehabilitation (p = 0.03). Overall, the TNF-α-308(GA), IL-6 -174(GG), and IL-6R 1073(AA) genotypes negatively impact rehabilitation outcomes, likely due to their role in enhancing neuroinflammation. Larger studies are needed to develop personalized therapies tailored to genetic profiles, aiming to improve rehabilitation outcomes for TBI patients. Full article

Background: Data accessibility remains a significant barrier in healthcare AI due to privacy constraints and logistical challenges. Synthetic data, which mimics real patient information while remaining both realistic and non-identifiable, offers a promising solution. Large Language Models (LLMs) create new opportunities to generate high-fidelity clinical conversations between patients and physicians. However, the value of this synthetic data depends on careful evaluation of its realism, accuracy, and practical relevance. Objective: To assess the performance of four leading LLMs: ChatGPT 4.5, ChatGPT 4o, Claude 3.7 Sonnet, and Gemini Pro 2.5 in generating synthetic transcripts of patient–physician interactions in plastic surgery scenarios. Methods: Each model generated transcripts for ten plastic surgery scenarios. Transcripts were independently evaluated by three clinically trained raters using a seven-criterion rubric: Medical Accuracy, Realism, Persona Consistency, Fidelity, Empathy, Relevancy, and Usability. Raters were blinded to the model identity to reduce bias. Each was rated on a 5-point Likert scale, yielding 840 total evaluations. Descriptive statistics were computed, and a two-way repeated measures ANOVA was used to test for differences across models and metrics. In addition, transcripts were analyzed using automated linguistic and content-based metrics. Results: All models achieved strong performance, with mean ratings exceeding 4.5 across all criteria. Gemini 2.5 Pro received mean scores (5.00 ± 0.00) in Medical Accuracy, Realism, Persona Consistency, Relevancy, and Usability. Claude 3.7 Sonnet matched the scores in Persona Consistency and Relevancy and led in Empathy (4.96 ± 0.18). ChatGPT 4.5 also achieved perfect scores in Relevancy, with high scores in Empathy (4.93 ± 0.25) and Usability (4.96 ± 0.18). ChatGPT 4o demonstrated consistently strong but slightly lower performance across most dimensions. ANOVA revealed no statistically significant differences across models (F(3, 6) = 0.85, p = 0.52). Automated analysis showed substantial variation in transcript length, style, and content richness: Gemini 2.5 Pro generated the longest and most emotionally expressive dialogues, while ChatGPT 4o produced the shortest and most concise outputs. Conclusions: Leading LLMs can generate medically accurate, emotionally appropriate synthetic dialogues suitable for educational and research use. Despite high performance, demographic homogeneity in generated patients highlights the need for improved diversity and bias mitigation in model outputs. These findings support the cautious, context-aware integration of LLM-generated dialogues into medical training, simulation, and research. Full article

Insulin-like growth factor-binding protein-3 (IGFBP-3) plays a vital role in cellular growth, development, and survival. Incorporating IGFBP-3 into baseline prognostic evaluations may enhance the prediction of mortality in patients with sepsis. In this study, serum levels of IGFBP-3, C-reactive protein, procalcitonin, lactate, interleukin-6, and mid-regional pro-adrenomedullin were measured upon admission to the internal medicine unit (IMU) in 139 patients with microbiologically confirmed sepsis. The objectives were as follows: (1) to classify septic patient phenotypes based on optimal thresholds of independent prognostic biomarkers and (2) to evaluate whether these biomarkers improve the predictive accuracy of a clinical model (Model 1), which includes the clinical predictors of 1-year mortality. Age, sequential organ failure assessment (SOFA) score, multiple sources of infection, and IGFBP-3 levels independently predicted 1-year mortality. Patients with IGFBP-3 levels below 10.64 had significantly lower median body temperature (p = 0.008), reduced lymphocyte count (p = 0.001), and higher 1-year mortality (p < 0.001). Model 1 included age, SOFA score, and the presence of multiple sources of sepsis as predictor variables. Model 2 incorporated the same variables as Model 1, with the addition of IGFBP-3 levels. When comparing their prognostic performance, Model 2 demonstrated superior predictive accuracy for mortality at 60, 90, and 365 days following admission to the IMU. Low IGFBP-3 levels at IMU admission are strongly associated with worse outcomes in septic patients, supporting its potential use as a prognostic biomarker. Full article