Search Results (1,173)

Background/Objectives: Chronic kidney disease (CKD) is a recognised risk factor for severe COVID-19, but comparative outcomes between conservatively managed CKD patients and those on maintenance haemodialysis (HD) remain incompletely characterised, particularly in Central Asia. This study evaluated the impact of CKD severity on clinical outcomes, inflammatory profiles, and mortality in hospitalised COVID-19 patients. Methods: This retrospective cohort study reviewed 891 patients hospitalised with COVID-19 at a tertiary infectious disease centre in Almaty, Kazakhstan, between 2020 and 2021. Patients were stratified into three groups: No CKD (n = 598), CKD without HD (n = 116), and CKD on maintenance HD (n = 177). Demographic, laboratory, treatment, and outcome data were extracted from electronic medical records. Multivariate logistic regression was used to identify independent predictors of in-hospital mortality, acute kidney injury (AKI), and intensive care unit (ICU) admission. Model 1 served as the primary prognostic model, while Model 2 explored in-hospital complications. Results: Patients with CKD exhibited significantly higher inflammatory markers, with peak C-reactive protein reaching 168.3 mg/L in the HD group compared to 44.4 mg/L in the No CKD group. In-hospital mortality was highest in the CKD without HD group (34.8%), followed by CKD on HD (21.7%) and No CKD (13.6%). AKI occurred in 35.7% of conservatively managed CKD patients. In multivariate analysis, CKD without HD independently predicted mortality (OR 3.23; 95% CI 1.38–7.63) and AKI (OR 4.12; 95% CI 1.73–10.03). Conversely, established HD status was not a significant independent predictor of mortality after adjusting for age and comorbidities. Conclusions: CKD severity strongly influences COVID-19 prognosis. Paradoxically, conservatively managed CKD patients carry a higher mortality and AKI risk than patients already on maintenance HD, which may be associated with the absence of scheduled volume and metabolic control, although causal inferences cannot be drawn from this observational data. These findings support the need for aggressive monitoring and early nephrological intervention in non-dialysis CKD patients hospitalised with severe viral respiratory infections. Full article

Cancer-associated thrombosis (CAT) is a major cause of morbidity and mortality in patients with malignancy. Biomarkers of hypercoagulability and thromboinflammation may improve risk stratification and support personalised thromboprophylaxis, but evidence remains heterogeneous, particularly in cervical cancer. A systematic review was conducted according to PRISMA 2020. PubMed/MEDLINE, Scopus, Embase, and Web of Science were searched for studies published between January 2009 and March 2025 evaluating biological, molecular, genetic, and imaging biomarkers associated with hypercoagulability and thromboinflammation in women withcervical cancer. Evidence from breast cancer and broader CAT studies was incorporated to provide translational context. Owing to substantial methodological heterogeneity, findings were synthesised qualitatively. Twenty-five cervical cancer studies met eligibility criteria. D-dimer was the most extensively investigated biomarker and was consistently associated with VTE risk, although specificity was limited. Biomarkers of thrombin generation and fibrinolytic activation, including thrombin–antithrombin complexes, prothrombin fragment 1+2, and plasmin–α2-antiplasmin complex, demonstrated greater mechanistic specificity. Multimarker panels integrating coagulation, fibrinolysis, endothelial injury, platelet activation, and inflammation showed superior predictive performance compared with single biomarkers. Emerging biomarkers, including circulating tumour DNA, extracellular vesicles, and microRNAs, further supported tumour-driven thromboinflammation. SERPINE1 and F2 gene variants were associated with thrombotic risk and adverse prognosis. Current evidence supports further evaluation of integrated multimodal biomarker strategies for CAT risk assessment, but prospective, standardised, tumour-specific studies are required before biomarker-guided approaches can be implemented in clinical practice. Full article

Background: Pediatric head trauma is a common reason for emergency department presentation. Although most children have minor injuries, a small proportion harbor clinically important traumatic brain injuries requiring urgent intervention. Artificial intelligence (AI) may offer structured support in computed tomography (CT) decision making, but evidence regarding the performance of general-purpose large language models in pediatric head trauma remains limited. Objective: To evaluate the association between AI-based cranial CT recommendations and clinically meaningful outcomes in pediatric patients with blunt head trauma and to assess the diagnostic performance and clinical utility of the model. Methods: This retrospective single-center observational study included pediatric patients younger than 18 years with blunt head trauma who underwent cranial CT imaging and had complete outcome data. A general-purpose large language model generated binary CT recommendations (“CT recommended” or “CT not recommended”) using structured clinical information available at the time of emergency department presentation. The primary outcome was a composite adverse clinical outcome defined as the occurrence of at least one of the following: emergency surgical intervention, intensive care unit admission, intubation, neurological sequelae or mortality. Diagnostic performance metrics, calibration analysis and decision curve analysis were performed. Results: A total of 819 pediatric patients were included, and the AI model recommended CT in 530 patients (64.7%). The primary outcome occurred in 143 patients (17.5%) and was significantly more frequent in the CT-recommended group than in the CT-not recommended group (24.5% vs. 4.5%; OR 6.90, 95% CI 3.82–12.45; p < 0.001). Abnormal CT findings, emergency surgery, intubation and neurological sequelae were also significantly more common in patients for whom CT was recommended by the AI system. For the primary outcome, the AI recommendation demonstrated a sensitivity of 90.9%, specificity of 40.8%, positive predictive value of 24.5% and negative predictive value of 95.5%. Calibration analysis showed acceptable agreement between predicted probabilities and observed event rates. Decision curve analysis demonstrated greater net benefit than both the “treat-all” and “treat-none” strategies across a range of threshold probabilities. Conclusions: In this clinically selected cohort of pediatric patients with blunt head trauma who underwent cranial CT imaging, AI-based CT recommendations were strongly associated with adverse clinical outcomes and demonstrated high sensitivity and negative predictive value for identifying children at risk of clinically important events. These findings suggest that, within a clinically selected cohort of children who underwent cranial CT imaging, AI-generated CT recommendations were associated with clinically meaningful outcomes. However, these results should not be interpreted as validation of CT decision making in the broader pediatric head trauma population and require prospective validation in unselected cohorts. Full article

Postoperative cardiovascular complications remain a leading cause of morbidity and mortality after noncardiac surgery, yet current risk models do not incorporate psychosocial stress. With over 300 million noncardiac surgeries performed annually worldwide and a substantial burden of perioperative cardiovascular complications, preoperative chronic stress is increasingly recognized as a potentially modifiable risk factor. Chronic stress produces HPA axis dysregulation, glucocorticoid resistance, sympathetic activation, inflammation, endothelial dysfunction, and hypercoagulability. These pathways overlap with the mechanisms underlying perioperative myocardial injury, arrhythmogenesis, and venous thromboembolism. Prospective data demonstrated that preoperative psychological distress independently predicted 30-day cardiovascular complications and 1-year mortality after noncardiac surgery. Allostatic load studies in noncardiac surgery patients showed that high preoperative physiological burden was associated with up to twofold increases in postoperative mortality and elevated rates of myocardial infarction and venous thromboembolism. Epidemiological evidence further supports that anxiety and depression independently increase cardiovascular risk. Converging evidence suggests that preoperative psychological distress is a relevant perioperative cardiovascular risk factor. However, no randomized controlled trial has evaluated whether targeted preoperative stress reduction can decrease postoperative cardiovascular events, representing a critical gap warranting prospective investigation. Full article

Background/Objectives: Blunt thoracic aortic injury (BTAI) is a rare, highly lethal trauma typically occurring at the aortic isthmus. Advanced BTAI is primarily treated with thoracic endovascular aortic repair (TEVAR). Because emergent surgical debranching is rarely feasible, management depends heavily on patient anatomy, especially regarding the left subclavian artery (LSA). Patient-specific computational fluid dynamics (CFD) models offer critical insights into periprocedural planning and outcome prediction. Methods: This study investigates hemodynamic changes in a patient-specific BTAI case following intentional LSA coverage by a stent graft. Three-dimensional patient-specific models were coupled with RCR-Windkessel boundary conditions for both pre- and post-procedural imaging data to simulate blood flow in each scenario. Results: Post-intervention, flow distribution improved significantly; relative perfusion to the brachiocephalic trunk and left common carotid artery increased by 3.51% and 4.02%, respectively, alongside an elevated overall pressure throughout the entire computational domain. However, regions with high oscillatory, low magnitude shear (HOLMES), specifically wall areas with values < 0.3 Pa, expanded post-stenting. This warrants careful monitoring during follow-ups, given the associated risk of thrombus formation. Furthermore, time-averaged swirling strength (TASS) variation along the aorta decreased (standard deviation dropped from 1.8610 to 1.3835), indicating stabilized flow within the stented region, while normalized swirling strength increased distally. Conclusions: This study establishes an effective, non-invasive framework for assessing pre- and post-TEVAR hemodynamics. It demonstrates that LSA coverage induces uniformly elevated pressure and alters wall shear stress and helicity indices, highlighting the need for future research into pharmacological management to optimize long-term outcomes. Full article

Background/Objectives: Cardiac comorbidities are increasingly common among liver transplant candidates, particularly those with metabolic dysfunction-associated steatohepatitis (MASH)-related cirrhosis. Although the Liver Transplant Comorbidity Index identifies coronary artery disease (CAD) as a predictor of post-transplant mortality, the impact of overall cardiac comorbidity burden on early outcomes after liver transplantation remains unclear. We evaluated the association between pre-transplant cardiac comorbidities and early post-transplant outcomes, with emphasis on MASH-related cirrhosis. Methods: We performed a retrospective cohort study using the TriNetX US Collaborative Research Network. Adults undergoing first-time isolated liver transplantation through May 2026 were included. Pre-transplant CAD, heart failure (HF), and atrial fibrillation (AF) documented within 12 months before transplantation were identified using ICD-10-CM codes. Patients were categorized by cardiac comorbidity burden (0–3 conditions). Recipients with any cardiac comorbidity underwent 1:1 propensity score matching to those without cardiac disease using 16 baseline demographic, clinical, and laboratory variables, including MELD-Na. The estimand was the average treatment effect in the treated patients. Primary outcomes comprised 30- and 90-day all-cause mortality. Secondary outcomes included a prespecified restricted major adverse cardiac event (MACE) composite, limited to hard endpoints (death, myocardial infarction, cardiac arrest, ischemic stroke), and a broader composite, i.e., acute kidney injury, prolonged mechanical ventilation, vasopressor requirement, renal replacement therapy, ICU and hospital length of stay, and 90-day readmission. Results: Among 5124 recipients, 986 (19.2%) exhibited at least one cardiac comorbidity. After matching, 974 patients remained in each group. Pre-transplant cardiac comorbidity was associated with higher 30- and 90-day mortality and increased risks of all secondary outcomes. The association with MACE persisted but was attenuated when restricted to hard endpoints (90-day RR 1.55; 95% CI 1.19–2.03) when compared with the broad composite (RR 1.75; 95% CI 1.40–2.18). MASH recipients with cardiac comorbidities experienced numerically higher event rates than did non-MASH recipients, but interaction estimates were imprecise and non-significant. In separate matched analyses, AF was most strongly associated with MACE, whereas CAD showed the strongest association with mortality. Conclusions: Pre-transplant cardiac comorbidity burden is associated with worse early post-transplant outcomes. Although MASH-cirrhosis recipients experienced numerically higher event rates, exploratory subgroup analyses did not demonstrate statistically significant differences from the non-MASH recipients. These findings may help refine cardiac risk prediction and perioperative planning, but they do not establish that intensified cardiac risk stratification or perioperative optimization improve outcomes. Prospective studies incorporating detailed cardiac, donor, operative, frailty, and medication data are needed to validate these associations and determine whether targeted risk-stratification and perioperative strategies can improve post-transplant outcomes. Full article

Musculoskeletal injury remains a major welfare and performance concern in Thoroughbred racing, and biomarkers for early risk stratification are of scientific interest. This multicentre observational cohort study characterised serum concentrations of two bone turnover markers, osteocalcin/BGLAP (OC) and C-terminal telopeptide of type I collagen (CTX-I), in 1359 fit-to-race Thoroughbred racehorses sampled across New South Wales, Victoria, and Western Australia. Biomarker distributions, population-wide percentile ranges, demographic and training-related associations, and short-term soundness outcomes were evaluated using nonparametric methods. Both markers were positively skewed, with population-wide percentile ranges (2.5–97.5 percentile) of 0.13–9.44 ng/mL for CTX-I and 0.02–7.25 ng/mL for OC; CTX-I varied substantially by jurisdiction, so this pooled range should not be interpreted as a clinical reference interval for individual horses. CTX-I varied significantly by age, jurisdiction, venue, and training surface, with markedly higher concentrations in New South Wales horses and lower concentrations associated with polytrack training, but did not predict lameness outcomes. OC concentrations were significantly higher in horses classified as lame at sampling and showed modest discriminatory ability for subsequent lameness in univariate analysis, with the strongest performance for persistent lameness at both 7 and 28 days; this association attenuated after adjustment for age, sex, state, and training surface. At an unadjusted operational threshold of approximately 1.24 ng/mL, OC achieved high negative predictive value for persistent lameness. These findings suggest OC may have scientific value as a potential rule-out screening marker for short-term soundness, warranting further investigation, while CTX-I appears more informative for characterising population-level skeletal turnover variation. Full article

Background: Systemic inflammation plays a critical role in secondary brain injury after spontaneous intracerebral hemorrhage (ICH). The pan-immune-inflammation value (PIV) has recently emerged as a novel composite inflammatory biomarker; however, its prognostic significance in critically ill ICH patients remains unclear. Methods: This retrospective cohort study included 111 consecutive adult patients admitted to the intensive care unit (ICU) with spontaneous ICH between January 2020 and December 2024. PIV, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and conventional clinical predictors were evaluated at ICU admission. The primary outcome was 28-day mortality, while the mechanical ventilation (MV) requirement was assessed as a secondary outcome. Receiver operating characteristic (ROC) analysis and logistic regression models were used to evaluate prognostic performance. Results: MV was required in 78 patients (70.3%), and 41 patients (36.9%) died within 28 days. Patients requiring MV had significantly higher PIVs than non-ventilated patients (p = 0.013), whereas PIVs did not differ significantly between survivors and non-survivors (p = 0.539). For predicting MV requirement, GCS score demonstrated the highest discriminative performance (AUC = 0.922), followed by ICH score (AUC = 0.874), procalcitonin (AUC = 0.861), and NLR (AUC = 0.832), whereas PIV showed modest discrimination (AUC = 0.650). For 28-day mortality, procalcitonin achieved the highest AUC (0.800), while PIV showed poor predictive performance (AUC = 0.535). In multivariable analysis, NLR and procalcitonin remained independently associated with both MV requirement and 28-day mortality. PIV was not included in the final multivariable models because of its overlap with NLR; moreover, it did not provide meaningful incremental prognostic value when added to the reference models. Conclusions: In this single-center cohort of ICU-admitted patients with spontaneous ICH, PIV did not add meaningful prognostic value beyond established clinical and inflammatory predictors. These findings do not support the routine use of PIV for early risk stratification in this specific population; simpler markers, particularly NLR and procalcitonin, may be preferred when interpreted alongside established clinical severity measures. Full article

Basilar trunk aneurysms (BTAs) are rare intracranial aneurysms. These aneurysms pose substantial clinical risk because they are located close to vital cranial structures and perfusion-sensitive perforating arteries. In addition, outcomes from BTA repair are dependent upon several factors, which include proximity to the brainstem, preservation of perforators, corridor access to the aneurysm, successful clipping of the aneurysm through reconstruction, the need for intraoperative rescue manoeuvres and the ability of the patient to recover from complications. Many previous studies have documented the outcomes associated with BTA repair; however, few studies have examined how the anatomy of the BTA directly relates to surgical decisions made by surgeons. Therefore, we developed an explainable AI framework for documenting surgeon reasoning regarding the open microsurgical treatment of BTAs. The primary objective was to develop and internally evaluate an explainable microsurgical intelligence framework for structuring surgeon reasoning during open microsurgical treatment of BTAs. The secondary objectives were to explore the relationships between the proposed constructs and postoperative pontine infarction, angiographic occlusion, functional outcome, hidden disability, operative difficulty, and composite technical-safety failure. Methods: We retrospectively analysed the cases of 31 adult patients who underwent open microsurgical treatment of a basilar trunk aneurysm at our hospital between October 1999 and March 2025. The cohort included 18 women (58.1%) and 13 men (41.9%), with a median age of 55 years (interquartile range, 44–63 years); 14 patients (45.2%) presented with ruptured aneurysms. A database containing more than 300 variables collected information about each patient’s imaging studies, operative strategies employed during surgery, intraoperative events encountered during surgery, intraoperative angiographic verification, occurrence of new injuries or complications resulting from surgery, and degree of recovery in each patient. Temporally separated scores were generated to quantify perforator-aware hazard, compression burden imposed by proximity to the brainstem, constraints imposed by corridors available for clipping of the BTA, burden imposed by clip reconstruction, degree of surgical precision adjusted based on the need for rescue manoeuvres, degree of dataset/model readiness, and degree of case-level learning density. The framework was evaluated internally using methods that included leave-one-out cross-validation, Firth regression modelling, Bayesian modelling, bootstrap optimism correction, calibration assessments using Brier score, decision-curve analysis, evaluations of explainability, conformal uncertainty estimation, and retrieval of similar cases. Results: Complete occlusion of the aneurysm was successfully achieved in 27 patients (87.1%), whereas residual neck or sac remained in four patients (12.9%). New pontine infarction occurred in six patients (19.4%), including four perforator-related infarctions (12.9%). A favourable last-follow-up modified Rankin Scale (mRS) score of 0–2 was achieved in 25 patients (80.6%); however, hidden disability was noted in 11 of these 25 patients (44.0%). Mortality was 6.5% and was limited to two patients with high-grade rupture. PAH-S-pre predicted pontine infarction (OR, 1.19 for every five-point increase; leave-one-out cross-validated AUC, 0.92). The composite technical-safety failure model had an ROC AUC of 0.91, optimism-corrected AUC of 0.88, calibration slope of 0.96, Brier score of 0.10, and permutation p < 0.001. Explainability indicated that PAH-S-pre, BPCI, and CCR represented the most important features. Conformal prediction resulted in abstention from prediction in four patients (12.9%). Conclusions: Expert microsurgical thought processes involved in repairing BTAs can be systematised and recorded into time-relevant and clinically meaningful measures that preserve anatomical interpretability. Clinical use will require external validation before implementation; however, this framework may provide a clinically interpretable foundation for risk-adapted planning, verification, surveillance, education, and future decision-support research for complex neurovascular surgery. Full article

Background/Objectives: Foreign body ingestion is a frequent gastrointestinal emergency in children. Although most ingested objects pass spontaneously, button batteries, multiple high-powered magnets, sharp objects, and superabsorbent polymers may cause rapid and severe complications. Recent reviews have often focused on individual categories of high-risk objects, whereas practical integration of time-critical diagnosis, comparative guideline recommendations, radiolucent objects, vulnerable pediatric populations, and prognostic risk factors remains limited. This narrative review aims to critically synthesized current evidence and to propose a clinically oriented, risk-stratified framework that distinguishes emergent, urgent, and observational management pathways according to object characteristics, anatomical location, symptoms, elapsed time, imaging findings, and patient-related factors. Methods: A structured narrative review was performed using PubMed/MEDLINE, Scopus and Web of Science. The final searches were performed in July 2026 and covered publications indexed from January 2000 to June 2026. The review included international guidelines, position papers, systematic reviews, meta-analyses and clinically relevant observational studies in patients up to 18 years of age with gastrointestinal foreign body ingestion. Exclusion criteria were studies only involving adults, foreign body aspiration, nasal or auricular insertion, ingestion of caustic substances, duplicate publications, isolated case reports with no broader clinical relevance and articles not available in full text. Evidence was synthesized according to object type, anatomical location, urgency of intervention, imaging strategy, prognostic factors, and patient-related risk. Results: Most ingested foreign bodies pass spontaneously; however, button batteries, multiple magnets, sharp objects, and superabsorbent polymers are associated with distinct mechanisms of injury and a disproportionate risk of severe complications. Time to intervention, object type and size, anatomical location, symptom severity, delayed presentation, and imaging evidence of complications consistently emerge as the principal determinants of outcome. Current international recommendations show broad agreement for immediate removal of esophageal button batteries and sharp objects causing obstruction, but important differences remain regarding gastric batteries, distal magnets, radiolucent objects, and selected asymptomatic patients. Evidence for predictive models is still limited, and most proposed risk factors have not undergone external validation. Vulnerable children (e.g., with neurodevelopmental disorders, pica or recurrent intentional ingestion) require individualized multidisciplinary assessment and follow-up. Conclusions: Pediatric foreign body ingestion should be approached in a time-critical and risk-stratified manner, combining object characteristics, anatomical location, presenting symptoms, time from ingestion, imaging findings, and patient-specific vulnerability. Differentiated triage for emergent intervention, urgent removal and structured observation may improve clinical triage and reduce delays for high-risk cases. Current guidelines offer a robust management framework, but there are significant evidence gaps relating to radiolucent objects, water beads, distal magnets and externally validated predictive models. More multicenter studies are required to support standardized prognostic tools and more consistent decision-making across pediatric emergency settings. Full article

Background/Objectives: Early risk stratification remains challenging in patients with non-ST-segment elevation myocardial infarction (NSTEMI). The present study evaluated the prognostic value of 24 h high-sensitivity cardiac troponin I (hs-Troponin I) and assessed whether combining biomarkers and echocardiographic parameters improves short-term risk prediction. Methods: This prospective observational cohort study included 170 consecutive adult patients with confirmed NSTEMI who were admitted to a Medical Intensive Care Unit and prospectively enrolled between February 2022 and January 2023. Clinical, routine biochemical, inflammatory, hematological, lipid, and echocardiographic data were collected during index hospitalization. High-sensitivity cardiac troponin I was measured at admission and again 24 h after hospitalization, with the 24 h value used as the principal marker of myocardial injury in the prediction analyses. The primary endpoint was major adverse cardiovascular events (MACEs), defined as cardiovascular death, recurrent myocardial infarction, ischemic stroke, urgent coronary revascularization, or hospitalization for worsening heart failure, within 3 months. Multivariable logistic regression, Cox regression, sequential prediction modeling, and internal bootstrap validation were performed. Results: MACEs occurred in 88 patients (51.8%). Twenty-four-hour hs-Troponin I, but not admission hs-Troponin I, was independently associated with MACEs (OR 1.57, 95% CI 1.09–2.26; p = 0.015) and a shorter time to the first MACE event (HR 1.38, 95% CI 1.07–1.78; p = 0.012). Lower left ventricular ejection fraction (LVEF) was also independently associated with adverse outcomes. The addition of 24 h hs-Troponin I, LVEF, and C-reactive protein improved discrimination from an AUC of 0.665 to 0.759 (optimism-corrected AUC, 0.717), with corresponding improvements in reclassification. A simplified multimarker score was independently associated with event-free survival (HR 2.36, 95% CI 1.53–3.64; p < 0.001). Conclusions: In patients admitted to a medical intensive care unit with NSTEMI, the integration of 24 h hs-Troponin I, LVEF, and C-reactive protein improved short-term risk prediction beyond that of clinical variables alone. A practical multimarker model based on routinely available parameters identified patients at increased risk of adverse cardiovascular outcomes during early follow-up. Full article

This paper presents a retrospective proof-of-concept development and preliminary evaluation of an interpretable decision-support system for daily fatigue-risk management in one elite women’s football club. The system integrates morning wellness, GPS-derived external load, and a daily wellness-duration internal-load proxy at the player-day level. It combines a player-day integration layer, an interpretable predictive layer, and a recommendation layer that returns one of three staff-facing actions: Reduce, Maintain, or Progress. The predictive model outputs a calibrated probability of elevated next-morning self-reported soreness. The target is a subjective questionnaire outcome, not an injury, medical diagnosis, or objective marker of recovery. The decision-support layer maps this probability to a three-state recommendation, informed by a review threshold, operational guardrails, and staff oversight. Using retrospective monitoring data from two competitive seasons (2024/25 and 2025/26) in a single professional team, we evaluated the proposed approach using rolling-origin temporal validation, leave-one-player-out cross-validation, and between-season validation. To separate genuine predictive signal from the day-to-day persistence of soreness, we report a baseline ladder ranging from a trivial persistence rule to the full model, with bootstrap confidence intervals for performance differences. Under rolling-origin validation across 16 monthly folds, the final logistic regression model achieved a mean ROC-AUC of $0.759$ ($SD=0.089$). Critically, a model excluding current soreness still outperformed the persistence baseline (ROC-AUC $0.738$ vs. $0.721$), and the isolated contribution of current soreness was modest but reliable ($\Delta$ROC-AUC $=+0.044$, 95% CI $[+0.027,+0.059]$). Between-season validation (train: 2024/25; test: 2025/26) yielded an ROC-AUC of 0.801. The three-state recommendation layer separated outcomes monotonically, with observed next-morning soreness rates of $0.054$ for Progress, $0.217$ for Maintain, and $0.326$ for Reduce ($p<0.001$ for the Progress-versus-Maintain contrast). These preliminary findings support the feasibility of the proposed approach within the club studied. However, because the model requires complete wellness, GPS, and proxy data, it operates only on the fully monitored on-pitch stratum (3386 of 17,703 player-days); the reported performance therefore applies to this stratum rather than to a typical player-day, and prospective evaluation and external validation by independent teams are required before broader implementation can be considered. Full article

Extracorporeal cardiopulmonary resuscitation (ECPR) has emerged as a promising strategy for selected patients with refractory cardiac arrest, improving survival and the likelihood of favorable neurological outcomes. However, neurological prognostication in this setting remains highly challenging and insufficiently standardized. The pathophysiological complexity of ECPR, including global ischemia–reperfusion injury, altered cerebral perfusion, systemic inflammation, anticoagulation and prolonged sedation, limits the reliability of conventional post-cardiac arrest prognostic tools. This narrative review provides a focused and clinically oriented synthesis of current evidence on brain injury and neuroprognostication in patients undergoing veno-arterial extracorporeal membrane oxygenation (V-A ECMO) for cardiac arrest. Key determinants of neurological outcome across pre-ECMO and peri-resuscitation phases are examined, alongside the role and limitations of multimodal monitoring strategies, including neurological examination, electroencephalography, neuroimaging, cerebral oximetry and circulating biomarkers. Particular attention is given to the timing of prognostication and the risk of premature or inaccurate predictions leading to self-fulfilling prophecies. Emerging data suggest that neurological recovery in ECPR patients may be delayed, supporting a more cautious and time-adapted approach. A pragmatic, multimodal framework for neurological assessment in this population is outlined. By addressing current gaps and proposing a structured approach, this review aims to inform clinical decision making and contribute to improved neurologically meaningful survival in ECPR-treated cardiac arrest. Full article

Cardiac myosin-binding protein C (cMyBP-C) is a cardiac-restricted sarcomeric protein; after cardiomyocyte injury, circulating intact cMyBP-C and/or cMyBP-C fragments, collectively referred to here as the cMyC biomarker signal, appear rapidly in blood. In suspected acute coronary syndrome (ACS), its most important potential role is not as another marker of injury but as a decision-enhancing biomarker beyond symptoms, electrocardiography, cardiac troponin T and I concentrations measured with high-sensitivity assays (hs-cTnT and hs-cTnI), time from pain onset, and pre-test probability. This narrative review separates three clinical tasks frequently conflated in the biomarker literature: diagnosis of acute myocardial infarction, emergency-department triage, and prediction of short-term or post-infarction risk. We integrate cMyBP-C sarcomeric architecture, N-terminal regulatory biology, phosphorylation, proteolysis, circulating fragments, assay epitopes, analytical stability, diagnostic algorithms, point-of-care testing, ST-segment elevation myocardial infarction reperfusion biology, and major confounders including renal dysfunction, heart failure, age, sex, and chronic ventricular remodeling. Current evidence supports further evaluation of cMyC as an adjunct in early presenters and accelerated diagnostic pathways. However, diagnostic safety and efficacy have not been consistently reproduced across platforms and populations, and external validation—particularly of rule-out performance—remains insufficient for routine clinical use. Recurrent injury assessment and post-infarction risk phenotyping remain promising but incompletely validated applications. Before guideline adoption, cMyC needs phenotype-specific, multicenter implementation trials demonstrating incremental net benefit, cost-effectiveness, and patient-level safety compared with contemporary hs-cTnT- and hs-cTnI-based clinical decision algorithms. Full article

This article presents a geospatial model for identifying and assessing the risk of hazardous locations in the road network, developed to predict traffic safety hazards in areas with complex infrastructure where traditional methods, such as the Highway Safety Manual, are insufficient. The objective of the study was to develop a model that classifies road segments into five risk categories based on environmental and infrastructural characteristics, without using accident or traffic volume data. The model accounts for speed limits, road geometry, and the proximity of facilities that generate pedestrian traffic (schools, preschools, stores) and infrastructure elements (crosswalks, intersections). A hybrid approach was used, combining proprietary methods for determining distances from objects: vector-based (geodetic distance), route-based (road graph), and geometric (classification of a road segment’s shape), using QGIS, OpenStreetMap, and custom Python scripts. The results enabled assigning a risk category to each road segment, and validation was performed by comparing them with the locations of actual accidents resulting in serious injuries or fatalities. The developed model for identifying hazardous locations is a scalable tool that supports sensor-network-based area-based speed control systems, infrastructure planning, and safety management in regions with diverse road networks. Full article