Alen Juginović

Objective: This study was undertaken to characterize sleep architecture assessed by polysomnography (PSG) in children with epilepsy versus matched nonepilepsy clinical comparators and disentangle disease from antiseizure medication (ASM) effects. Methods: In this cross‐sectional analysis of the Nationwide Children's Hospital Sleep DataBank (3647 PSG studies from 3392 patients aged ≤18 years), a clinical cohort referred for PSG, we compared 560 PSG studies in children with epilepsy to 3087 studies in nonepilepsy clinical comparators. Propensity score matching (1:1) on age, sex, and body mass index percentile yielded 560 pairs. Fifteen PSG outcomes were compared using Wilcoxon signed‐rank tests with Hedges g and false discovery rate (FDR) correction. A secondary analysis compared 208 matched pairs of on‐ versus off‐ASM epilepsy patients. Seven sensitivity analyses addressed age subgroups, medication exclusions, and comorbidity matching. Results: Children with epilepsy had reduced rapid eye movement (REM) sleep (median 18.2% vs. 20.9%, g = −.32 [95% confidence interval = −.41 to −.24], FDR p < .001), lower sleep efficiency ( g = −.14, p = .007), shorter total sleep time ( g = −.12, p = .015), prolonged REM latency (g = .14, p = .029), and lower arousal index ( g = −.12, p = .013). ASM use amplified the REM deficit (15.8% vs. 19.8%, g = −.48, p < .001). The effect followed a developmental gradient: strongest at age < 6 years ( g = −.38, p < .001), intermediate at 6–12 years ( g = −.31, p = .002), and not detected at >12 years ( g = −.07, p = .953). Excluding benzodiazepine users attenuated the signal ( g = −.24), whereas excluding melatonin users preserved it ( g = −.29). Significance: In the largest pediatric epilepsy PSG study to date, epilepsy is associated with an REM‐predominant sleep disruption concentrated in children younger than 6 years and amplified by ASMs, although the independent contribution of epilepsy itself remains uncertain. These cross‐sectional findings identify early childhood as a period of heightened vulnerability that warrants prospective study.

Sleep banking, i.e., preemptively obtaining extra sleep prior to anticipated sleep loss, has been proposed as a strategy to reduce the cognitive and physiological consequences of sleep deprivation. However, our understanding remains incomplete regarding the effectiveness of preemptive sleep extension in enhancing resilience to sleep loss. A comprehensive literature search was conducted using PubMed, MEDLINE, and Embase for studies published between 2004 and 2025. Following a comprehensive literature search, we identified 12 studies meeting the inclusion criteria—seven primary experimental trials comprising approximately 140 participants, predominantly healthy young adults aged 18–39 years. We evaluated the effects of sleep banking on cognitive performance, mood, physiological parameters, and real-world outcomes. Included studies encompassed experimental laboratory trials, observational research, and field studies in occupational and athletic settings. Although the number of studies on sleep banking remains limited, experimental evidence demonstrates that preemptive sleep extension improves objective alertness and vigilance during subsequent sleep restriction or total sleep deprivation. Individuals who obtained additional sleep exhibited fewer attentional lapses, faster reaction times, and improved mood, although subjective sleepiness often remained high. Preliminary field evidence suggests that preemptive sleep extension enhances workplace safety, reduces errors, and improves sustained attention in shift workers. In athletic contexts, sleep banking has been associated with improved physical endurance and reaction speed. Importantly, this review primarily addresses the homeostatic dimension of sleep regulation (Process S); circadian factors (Process C), including chronotype, social jetlag, and circadian timing of sleep extension and testing, were not systematically addressed in the included studies and represent important limitations of the current evidence base. Overall, sleep banking appears to be a viable strategy for enhancing resilience to acute sleep loss. It confers measurable benefits in performance, cognitive function, and physiological markers, supporting its application in high-demand occupations and competitive environments. Although it does not fully eliminate subjective fatigue, sleep banking may serve as a valuable complement to other fatigue mitigation strategies for anticipated short-term sleep loss.

Background: Sepsis is a complex life-threatening condition. Early initiation of treatment is crucial in reducing mortality. Current scoring systems have a lack of reliability in the emergency department (ED) or during early hospitalization (EH). Thus, a quick, reliable, and objective scoring system for assessing mortality risk during EH or ED could significantly reduce sepsis mortality. Methods: Using the MIMIC-IV database, we identified 7546 patients hospitalized due to septicemia. We included 13 comorbidity groups and the first chronologically available values of 75 laboratory parameters from the ED or EH. To create and validate our scoring system for early prediction of in-hospital mortality (e-SEPSS), patients were assigned to model development (MD) (N = 1004) or model validation (MV) group (N = 6542), with the latter serving as internal validation of e-SEPSS. Each risk factor that contributed significantly to mortality was assigned one point. Groups with different numbers of points were compared according to mortality and hospitalization duration. Results: Decreased chlorides, increased mean corpuscular hemoglobin, increased red blood cell distribution width, increased phosphates, decreased pH, increased partial thromboplastin time, and increased lactate dehydrogenase were included in e-SEPSS due to the highest reliability in predicting mortality. Patients received 1 point for each parameter, creating 8 mortality risk groups. A significant linear increase in mortality with each additional point was shown, ranging from 4.1% (0 points) to 100% (7 points) in the MD group. Similar trends were observed in the MV group. High power in discriminating patients with different mortality risks was shown (MD (ROC AUC = 0.718, CI 0.682–0.754), MV (ROC AUC = 0.798, CI 0.783–0.813)). Decreased survival time and shorter time-to-death with each additional point strengthened the validity of e-SEPSS (Mantel-Cox χ²(7) = 994.2, p-value < 0.001). Conclusion: e-SEPSS provides a simple, objective, reliable, and accessible way of predicting mortality in septic patients in the ED or during EH.. After external and clinical validation of e-SEPSS, it could become a useful additional tool in reducing sepsis mortality.

This review aims to provide a comprehensive framework for implementing precision sports medicine, integrating genetics, pharmacogenomics, digital health solutions, and multi-omics data. Literature review was conducted using MEDLINE, EMBASE, Web of Science, and Cochrane Library databases (January 2018–April 2024), focusing on precision medicine applications in sports medicine, utilizing key terms including “precision medicine”, “sports medicine”, “genetics”, and “multi-omics”, with forward and backward citation tracking. The review identified key gene variants affecting athletic performance: endurance (AMPD1, PPARGC1A), power (ACTN3, NOS3), strength (PPARG), and injury susceptibility (COL5A1, MMP3), while also examining inherited conditions like cardiomyopathies (MYH7, MYBPC3). Pharmacogenomic guidelines were established for optimizing common sports medications, including NSAIDs (CYP2C9), opioids (CYP2D6), and cardiovascular drugs (SLCO1B1, CYP2C19). Digital health technologies, including wearables and predictive analytics, showed potential for enhanced athlete monitoring and injury prevention, while multi-omics approaches integrated various molecular data to understand exercise capacity and injury predisposition, enabling personalized assessments, training regimens, and therapeutic interventions based on individual biomolecular profiles. This review provides sports medicine professionals with a framework to deliver personalized care tailored to each athlete’s unique profile, promising optimized performance, reduced injury risks, and improved recovery outcomes.