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Ischemic heart disease remains the leading cause of death despite substantial advances in diagnosis, revascularization therapies, and risk-factor control. Beta-adrenergic receptor blockers (Beta-Blockers, BBs), long used to control heart rate, blood pressure, and reduce arrhythmic risk, may also confer cardioprotection through mechanisms beyond hemodynamic unloading. This review integrates an extensive range of preclinical, translational, and clinical studies to present a comprehensive overview of the cardioprotective effects of BBs in the context of myocardial ischemia and reperfusion injury. Mechanistic domains include modulation of redox homeostasis, attenuation of inflammation and neutrophil activation, preservation of mitochondrial integrity and anti-apoptotic signaling, improvement of endothelial function, and stabilization of calcium handling. Third-generation compounds, carvedilol and nebivolol, demonstrate additional antioxidant and vasodilatory benefits compared with first- and second-generation agents; however, no consistent class-wide effect exists across most pathways. The evidence base remains fragmented, often derived from agent- or context-specific studies in heterogeneous populations, with uncertainty surrounding optimal timing of intervention. By bridging mechanistic understanding with clinical outcomes, this review highlights the importance of standardized assessment of BB effects, the development of personalized treatment approaches, and the pursuit of future research to address ongoing translational gaps.

Dietary sodium restriction is widely recommended in heart failure (HF) management; however, its benefits and risks remain a subject of ongoing debate. While moderate sodium reduction may improve symptoms and quality of life in selected patients, excessive restriction can trigger maladaptive neurohormonal activation, worsen renal function, and increase the risk of hyponatremia, malnutrition, and cachexia. Patient response is heterogeneous, influenced by clinical risk profile, salt sensitivity, comorbidities, and age, with some high-risk patients experiencing neutral or adverse outcomes. Additional challenges arise from hidden sodium in processed foods, medications, and meals, which complicate monitoring and adherence. Effective sodium management in HF therefore requires a nuanced, individualized approach that integrates risk stratification, dietary counseling, and public health measures targeting the food industry. Future research should refine patient selection criteria and establish optimal sodium targets to balance therapeutic efficacy with safety in real-world practice.

Background: Novel and accessible biomarkers may add to the existing risk stratification schemes in patients with acute coronary syndrome (ACS). The platelet-to-lymphocyte ratio (PLR) and glucose-to-lymphocyte ratio (GLR) have emerged as potential indicators of systemic inflammation and metabolic stress, both of which are pivotal in ACS pathophysiology. The aim of this study was to investigate the prognostic significance of the PLR and GLR in patients with ACS. Methods: We performed a retrospective cohort study of patients hospitalized with ACS between 2017 and 2023 at Hippokration Hospital of Thessaloniki, Greece. PLR and GLR were calculated from admission blood samples. The primary endpoint was all-cause mortality. Logistic and Cox regression models were used to investigate the associations of PLR and GLR with all-cause mortality. Receiver operating characteristic (ROC) analysis, Kaplan–Meier survival curves, and restricted cubic spline (RCS) modeling were also applied. Results: In total, 853 patients (median age: 65 years, 72.3% males) were included. Higher PLR and GLR were independently associated with increased risk of long-term mortality [adjusted Odds Ratio (aOR) for PLR: 1.007, 95% CI: 1.005–1.008; and for GLR: aOR = 1.006, 95% CI: 1.003–1.008]. The optimal cut-off values were 191.92 for PLR and 66.80 for GLR. Kaplan–Meier and Cox regression analyses confirmed significantly reduced survival in patients with GLR and PLR values exceeding these thresholds. RCS analysis revealed non-linear relationships, with mortality risk rising sharply at higher levels of both markers. PLR showed superior prognostic performance (AUC: 0.673, 95% CI: 0.614–0.723) compared to GLR (AUC: 0.602, 95% CI: 0.551–0.653). Conclusions: While PLR demonstrated greater predictive accuracy, both PLR and GLR were consistently associated with mortality and may provide complementary prognostic information. Incorporating those ratios into routine clinical assessment may improve risk stratification, particularly in resource-limited settings or for patients without traditional risk factors.

Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of acute coronary syndromes in younger women without typical atherosclerotic risk factors. Its distinct pathophysiology and vessel fragility create unique challenges for revascularization. Conservative management is preferred when hemodynamics and coronary flow permit, but selected cases necessitate intervention, primarily percutaneous coronary intervention (PCI). Despite growing insights into SCAD pathomechanics-the \"outside-in\" and \"inside-out\" hypotheses-and the central role of intracoronary imaging (OCT/IVUS), optimal device strategies remain under-researched. The present review covers contemporary SCAD-PCI pitfalls and limitations, expanding to the mechanistic underpinnings and procedural applications of drug-coated balloons (DCB) and bioresorbable scaffolds (BRS) as \"leave-nothing-behind\" alternatives. Both approaches have advantages and drawbacks but are attractive in selected scenarios: DCB delivers antiproliferative therapy without permanent caging, and BRS provides temporary scaffolding (amenable to overlap when required) with the potential to restore biomechanics/vasomotion after resorption. Acknowledging that definitive evidence is lacking and current data are largely observational, the review finally sets future research priorities including head-to-head trials of different DCB types and evaluation of next-generation, thinner-strut, predictably resorbing BRS. The overarching question is whether-and how-these modalities can be integrated into standardized, imaging-guided interventional algorithms for SCAD.

Background:Inflammation has recently been identified as a critical regulator of the pathophysiology and prognosis of acute coronary syndrome (ACS). The systemic immune–inflammation index (SII), derived from platelet, neutrophil, and lymphocyte counts, has gained attention as a potential marker for predicting adverse outcomes in cardiovascular diseases. However, the prognostic value of the SII, particularly in relation to gender differences, has not been extensively studied.Methods:Thus, we conducted a retrospective cohort study of 835 patients hospitalized for ACS at Hippokration Hospital, Thessaloniki, Greece, between 2017 and 2023. The SII was calculated using blood samples taken at admission. Logistic and Cox regression models were used to evaluate the relationship between the SII and all-cause mortality, with stratified analyses conducted according to gender. Receiver operating characteristic (ROC) analysis, Kaplan–Meier survival curves, and restricted cubic spline (RCS) modeling were also performed to assess the discriminative ability and non-linear associations of the SII with mortality.Results:A total of 835 patients were included, with a median follow-up of 25 months. An elevated SII was independently associated with increased long-term mortality, with patients in the highest SII quartile exhibiting a 2.3-fold higher risk of death compared to those in the lowest quartile (adjusted hazard ratio (aHR) = 2.31, 95% confidence interval (CI): 1.60–3.32; p < 0.001). The optimal cut-off value for the SII was identified as 1864.19. Gender-stratified analyses revealed a stronger prognostic value in women compared to men (area under the curve (AUC) = 0.70 vs 0.58; p = 0.018). The Kaplan–Meier and Cox regression analyses confirmed significantly worse survival for patients with SII levels above this threshold (p < 0.05). The RCS modeling demonstrated a non-linear relationship between the SII and mortality, with a marked increase in risk at higher levels of the SII, especially in women.Conclusions:The SII is a simple, easily accessible biomarker that independently predicts mortality in ACS patients, with notable gender-specific differences in the prognostic value of the SII. Nonetheless, incorporating SII into routine risk assessment could enhance risk stratification and improve personalized treatment strategies, particularly in settings with limited resources.

Background: Large language models (LLMs) are increasingly proposed as clinical decision support tools. However, their reliability in the emergency department (ED) triage remains insufficiently validated. This study aimed to evaluate the performance and limitations of multiple LLMs in triage using a large retrospective dataset. Methods: We conducted a retrospective analysis of 39,375 anonymized patient cases from the ED of AHEPA University General Hospital, Thessaloniki, Greece (June 2024–July 2025), extracted from the hospital’s electronic medical record system. All cases were triaged in real time according to the Emergency Severity Index (ESI) by 25 emergency physicians. In cases of uncertainty, a senior emergency physician was consulted. Seven LLMs (ChatGPT-5 Thinking, ChatGPT-5 Instant, Gemini 2.5, Qwen 3, Grok 4.0, Deep Seek v3.1, and Claude Sonnet 4) were evaluated against the physician-assigned ESI level (reference standard). Outcomes included triage score agreement (quadratic weighted kappa, κw), clinic referral accuracy and admission prediction. Subgroup analyses were performed by referral clinic and admission outcome. The study was conducted in accordance with TRIPOD-AI reporting guidelines. Results: Model performance varied substantially. DeepSeek and Claude Sonnet 4 achieved the highest agreement with physician-assigned ESI (κw ≈ 0.467; raw accuracy: 61.7%). In contrast, GPT-5 Instant performed poorly across all evaluation metrics (κw = 0.176; 95% CI: 0.167–0.186). Claude Sonnet 4 demonstrated the best performance in clinic referral (67.1%; κ = 0.619) and admission prediction (κw ≈ 0.46). Subgroup analyses indicated higher performance in pediatric cases and organ-specific complaints, such as ophthalmology (up to 81% accuracy). LLMs also showed tendencies toward over- or under-triage. Conclusions: Current LLMs demonstrate promising but inconsistent capability in triage. While selected models achieved moderate alignment with physician ESI decisions, none achieved strong agreement (κ > 0.80). LLMs are most suitable as supervised decision support tools, particularly in anatomically well-defined clinical scenarios, rather than as autonomous systems.

Background: Rapid Sequence Induction (RSI) is a widely used method for emergency airway management in critically ill and clinically unstable patients. Beyond the risks inherent to the procedure itself, RSI is almost exclusively performed in emergency settings where patients present with severe physiological derangement and a high risk of aspiration. In postmortem examinations, forensic toxicology results may be influenced by the patient’s clinical condition, the sampling site, the postmortem interval (PMI), and postmortem drug redistribution (PMR). This review aims to evaluate the existing literature regarding PMR of drugs commonly used during RSI. Methods: PubMed/MEDLINE, Embase and the Cochrane Library were searched for studies on PMR of drugs used in intravenous (IV) RSI (up to November 2025). Human and animal studies, patient populations comparable to critically ill individuals requiring RSI, and forensic case reports of exclusively IV drug administration were included. Studies on recreational use, overdose and non-IV administration were excluded. Results: Data on the PMR of IV-administered RSI drugs remain limited. Most available studies involve Intensive Care Unit (ICU) patients or individuals who underwent RSI in emergency settings. Fentanyl and midazolam appear to demonstrate notable PMR. Several factors influencing postmortem drug concentrations were identified. Although these findings are consistent with the existing literature, the small number of studies and the heterogeneity of data preclude definitive conclusions. Conclusions: Critical patient condition, including frailty due to advanced age, hemodynamic instability (particularly in ICU patients), hypoalbuminemia, body mass index (BMI), and injury and/or trauma, as well as the interval between IV drug administration and death, appear to affect postmortem concentrations of drugs used during RSI. The potential for PMR of certain agents, such as fentanyl and midazolam, adds further complexity. Given the scarcity of consolidated evidence and until further research provides more robust data, postmortem drug levels should not be interpreted as directly reflective of antemortem concentrations.

Background: In-hospital cardiac arrest (IHCA) constitutes a high-impact clinical event, associated with substantial mortality, frequent neurological and functional impairment. There is a pressing need for primary IHCA studies that evaluate risk predictors, given the inherent challenges of IHCA data collection, previously unharmonized reporting frameworks, and the predominant focus of prior investigations on other domains. Among potential contributors, the “off-hours effect” has consistently been linked to poorer IHCA outcomes. Accordingly, we sought to examine whether in-hospital mortality after IHCA varies according to the time and day of occurrence within a tertiary academic center in Northern Greece. Methods: We conducted a single-center observational cohort study using a prospectively maintained in-hospital resuscitation registry at AHEPA University General Hospital, Thessaloniki. All adults with an index IHCA between 2017 and 2019 were included, and definitions followed Utstein-style recommendations. Results: Multivariable logistic regression adjusted for organizational, patient, and process-of-care factors demonstrated that afternoon/night arrests, weekend arrests, heart failure comorbidity, and need for mechanical ventilation were independent predictors of higher in-hospital mortality. Conversely, arrhythmia as the cause of IHCA and arrests occurring in the intensive care unit or operating room were associated with improved survival. Subgroup analyses confirmed consistent off-hours differences, with weekend events showing reduced 30-day and 6-month survival and worse functional status at discharge. Afternoon/night arrests were more frequent, characterized by longer response intervals and lower survival at both time points. Conclusions: Organizational factors during nights and weekends, rather than patient case mix, drive poorer IHCA outcomes, underscoring the need for targeted system-level improvements.

Atrial fibrillation (AF) is the most common sustained arrhythmia and a growing global health burden, yet conventional monitoring with Holter devices, event recorders and implantable loop recorders often fails to adequately capture recurrence. Rapid advances in digital health, wearable biosensors and artificial intelligence (AI) have transformed consumer smartwatches and wearables into potential clinical tools capable of continuous, real-world rhythm surveillance. This narrative review synthesizes contemporary evidence on smartwatch-based AF monitoring, spanning core technologies—photoplethysmography, single-lead electrocardiography and AI fusion algorithms—and validation studies across post-ablation follow-up. Compared with traditional modalities, smartwatch-based AF monitoring demonstrates improved detection of AF recurrence, enhanced characterization of AF burden, symptom–rhythm correlation, and greater patient engagement. At the same time, key limitations are critically examined, including motion artifacts, false-positive alerts, short recording windows, adherence dependence, digital literacy and access gaps, as well as unresolved issues around regulation, interoperability and data privacy. By integrating engineering advances with guideline-directed care pathways, smartwatch-based AF monitoring holds promise to complement, rather than immediately replace, established diagnostic tools and to enable more proactive, individualized AF management. Future work must focus on robust clinical validation, equitable implementation and clear regulatory frameworks to safely scale these technologies.

Background/Objectives: Stress-induced hyperglycemia (SIH) is frequently observed in critically ill patients and has been associated with adverse outcomes in individuals both with and without known diabetes mellitus (DM). However, evidence regarding its prognostic utility for in-hospital mortality in high-acuity emergency department (ED) populations remains limited. Methods: We conducted a retrospective observational cohort study of consecutive adult ED patients classified as Emergency Severity Index (ESI) triage level 1. SIH was defined a priori as an admission serum glucose > 140 mg/dL, a pragmatic cutoff widely applied in clinical practice despite ongoing debate regarding optimal pathophysiological thresholds. Associations with in-hospital mortality were assessed using logistic regression in the overall cohort and stratified by DM status. Additional analyses assessed the prognostic performance of admission glucose as a continuous variable. Results: Of 470 included patients, 435 had complete mortality data; 247 (56.8%) died during hospitalization. SIH was present in 258/435 (59.3%)and known DM in 114/435 (26.2%). SIH was associated with higher in-hospital mortality in univariate analysis (OR 2.90, 95% CI 1.91–4.43; p < 0.001) and remained independently associated after adjustment (adjusted OR 2.22, 95% CI 1.41–3.51; p < 0.001). The association between SIH and mortality persisted in both non-DM and DM subgroups, with no significant interaction by DM status. SIH alone showed modest discrimination for mortality (AUC 0.625, 95% CI 0.572–0.669), whereas continuous admission glucose performed better. Discrimination improved in the multivariable model (AUC 0.728, 95% CI 0.677–0.779). Restricted cubic spline analysis demonstrated a strong overall association between admission glucose and mortality without evidence of nonlinearity, indicating an approximately linear risk increase across the observed glucose range. Conclusions: Regarding severely ill ED patients, classified as ESI triage 1, SIH is an independent predictor of in-hospital mortality irrespective of DM status. Admission glucose may improve early risk stratification when incorporated into clinical models.