Marshall University

Herpes zoster (HZ) is a cutaneous viral disease that typically presents with a dermatomal vesicular eruption. Immunosuppressed patients are more likely to have atypical HZ involving chronic ulceration and disseminated distribution, making diagnosis a challenge. The current report describes a unique case of HZ in a woman with systemic lupus on immunosuppressive therapy manifesting as persistent lower extremity ulceration with diffuse dermal and endothelial infection and secondary panniculitis without epidermal involvement. Other potential etiologies were thoroughly excluded. The ulceration successfully responded to several weeks of valacyclovir. Recognizing atypical clinicopathologic manifestations of HZ in the setting of immune compromise is critical to accurate diagnosis and prompt therapy.

The advent of large expansive datasets has generated substantial interest as a means of developing and implementing unique algorithms that facilitate more precise and personalized interventions. This methodology has permeated the realm of sleep medicine and in the care of patients with sleep disorders. One of the large repositories of information consists of adherence and physiological datasets across long periods of time as derived from patients undergoing positive airway pressure (PAP) treatment for sleep‐disordered breathing. Here, we evaluate the extant and yet scarce findings derived from big data in both adults and children receiving PAP for obstructive sleep apnea and suggest future directions towards more expansive utilization of such valuable approaches to improve therapeutic decisions and outcomes.

Medical education is the bedrock of modern medicine. How we teach learners (medical students, residents, and fellow physicians) is critically important. If we want an empathetic, sympathetic, knowledgeable, and competent physician workforce, we must teach these values. How will artificial intelligence improve the way we interact with our learners? This chapter will discuss some theories of adult learning. We will then apply these therapies to the future to see how artificial intelligence if applied correctly could really enhance the learning experience.

Lung cancer, a leading cause of cancer mortality, often involves epidermal growth factor receptor (EGFR) mutations, common in 17% of Caucasian and 40% of Asian non-small-cell lung cancer (NSCLC) patients. While the exon 19 deletion and L858R mutation are prevalent, rare variants like L833V/H835L are less understood. This case reports a 75-year-old female with NSCLC harboring L833V/H835L mutations. Initial imaging showed a right upper lobe mass and nodularity in the left upper lobe. Biopsy confirmed adenocarcinoma, and genomic analysis identified EGFR L833V/H835L mutations. Based on these findings, the patient was treated with osimertinib 160 mg daily, reduced to 80 mg due to side effects. After 3 months, positron emission tomography (PET) scans revealed significant tumor reduction, and brain metastasis remained stable. This case demonstrates the efficacy of osimertinib for rare EGFR mutations, aligning with literature suggesting its potential for managing such variants. Although large-scale trials are impractical due to the rarity of these mutations, this report adds valuable evidence supporting osimertinib’s use, highlighting the need for comprehensive genomic profiling in NSCLC.

Resilience‐related knowledge and skills are part of all counselors‐in‐training foundational curriculum. We used interpretative phenomenological analysis to explore nine novice counselors’ perceived training experiences in the Predictive 6 Factor (PR6) model of resilience. We identified the following group experiential themes: value of the neuroscience information and PR6 model, counselors’ personal resonance and buy‐in, and considerations for practice. We also identified nine subthemes representing more nuanced elements of the larger themes.

Inferential decision-making algorithms typically assume that an underlying probabilistic model of decision alternatives and outcomes may be learned a priori or online. Furthermore, when applied to robots in real-world settings they often perform unsatisfactorily or fail to accomplish the necessary tasks because this assumption is violated and/or because they experience unanticipated external pressures and constraints. Cognitive studies presented in this and other papers show that humans cope with complex and unknown settings by modulating between near-optimal and satisficing solutions, including heuristics, by leveraging information value of available environmental cues that are possibly redundant. Using the benchmark inferential decision problem known as “treasure hunt”, this paper develops a general approach for investigating and modeling active perception solutions under pressure. By simulating treasure hunt problems in virtual worlds, our approach learns generalizable strategies from high performers that, when applied to robots, allow them to modulate between optimal and heuristic solutions on the basis of external pressures and probabilistic models, if and when available. The result is a suite of active perception algorithms for camera-equipped robots that outperform treasure-hunt solutions obtained via cell decomposition, information roadmap, and information potential algorithms, in both high-fidelity numerical simulations and physical experiments. The effectiveness of the new active perception strategies is demonstrated under a broad range of unanticipated conditions that cause existing algorithms to fail to complete the search for treasures, such as unmodelled time constraints, resource constraints, and adverse weather (fog).

Objective: Examine the sociodemographic and clinical profiles of Middle Eastern patients with atrial fibrillation (AF) who have a history of prior ischemic stroke or systemic embolism (SSE) and compare the risk of adverse events between AF patients from the Middle East with and without a history of SSE. Methods: The study population was drawn from the JoFib study, a multicenter, nationwide, prospective registry of AF patients from the Middle East. Patients with a history of prior hemorrhagic stroke were excluded from this analysis. The remaining patients were divided into two groups based on their history of prior SSE to compare baseline sociodemographic and clinical characteristics and the one-year risk of all-cause death, cardiovascular death, non-cardiovascular death, SSE, and major bleeding between AF patients with and without prior SSE. Multivariable Cox proportional hazards models and Fine-Gray sub-distribution hazards models were used to adjust for confounding factors. Additionally, multivariable logistic regression models were applied to compare the secondary outcome of clinically relevant non-major bleeding (CRNMB) between the two groups. Results: The study included 2,003 AF patients, divided into two groups: 318 patients (15.9%) with a history of prior SSE and 1,685 patients (84.1%) without. Patients with prior SSE were older than those without (45.3% vs. 30.4%, p<0.001). Compared to the no prior SSE group, those with prior SSE were less symptomatic (61.3% vs. 72.8%, p<0.001), had higher rates of diabetes (49.1% vs. 42.4%, p=0.03) and dyslipidemia (51.9% vs. 43.6%, p=0.007), and were less often obese (34.0% vs. 42.2%, p=0.009). Rhythm-control strategies were used less frequently in the prior SSE group (16.0% vs. 22.0%, p=0.02), while antithrombotic medications were more commonly used, including anticoagulants (89.0% vs. 80.7%, p<0.001) and antiplatelets (48.4% vs. 37.6%, p<0.001). The prior SSE group had a higher risk of all-cause death (aHR 1.64, 95% CI 1.21-2.22), cardiovascular death (adjusted subhazard ratio [aSHR] 1.50, 95% CI 1.04-2.16), non-cardiovascular death (1.76, 95% CI 1.00-3.08), and SSE (3.05, 95% CI 1.83-5.07). However, a history of prior SSE did not significantly affect the rates of major bleeding (0.67, 95% CI 0.27-1.65) or clinically relevant non-major bleeding (CRNMB) (AOR 0.79, 95% CI 0.47-1.33). Conclusion: AF patients with a history of prior SSE face a higher risk of adverse events compared to those without prior SSE.

Introduction: Studies have reported on the prevalence, and associations between acute myocardial infarction (AMI) and systemic lupus erythematosus (SLE), but there is limited data on the predictors of mortality and whether these differ among patients with a diagnosis of SLE. We examined the factors associated with mortality among hospitalized patients with a diagnosis of AMI with or without SLE. Hypothesis: Patient and hospital associated factors can predict mortality among hospitalized patients with AMI and these predictors differ by SLE diagnosis Methods: The National Inpatient Sample (NIS) data collected from 2016 – 2020 was utilized to conduct retrospective cohort analyses. Multivariate logistic regression models were used to examine the factors associated with mortality among hospitalized patients with AMI by SLE diagnosis. Results: Among SLE patients with a diagnosis of AMI, being female (AOR: 1.53; 95% CI: 1.02-1.86) and 65 years and above (AOR: 1.65; 95% CI: 1.20-2.74) was associated with higher odds of mortality compared to being male and younger than 65 years. Elective admission (AOR: 0.59; 95% CI: 0.39-0.85) was associated with lower risk of mortality relative to non-elective admission. Of note, non-Hispanic blacks (AOR: 0.68; 95% CI: 0.39-0.98) had lower odds of mortality than non-Hispanic whites. Patients with length of stay greater than 5 days (AOR: 1.75; 95% CI: 1.18-2.59) were more likely to die than those with hospital stay 5 days or less. Higher comorbidity scores were also associated with higher odds of mortality. Among patients without SLE, non-Hispanic blacks (AOR: 1.68; 95% CI: 1.07–2.48) reported higher mortality compared to their non-Hispanic white counterparts. Additionally, being on private insurance (AOR: 0.75; 95% CI: 0.32–0.99) was associated with lower odds of mortality relative to Medicare insurance. Conclusion: Our study highlights patients and hospital related factors that can predict mortality among patients hospitalized with AMI by SLE. Further studies are needed to explore these factors as it will help physicians identify patients that need closer monitoring.

Obstructive sleep apnea (OSA) in children is a prevalent and serious respiratory condition linked to cardiovascular morbidity. Polysomnography, the standard diagnostic approach, faces challenges in accessibility and complexity, leading to underdiagnosis. To simplify OSA diagnosis, deep learning (DL) algorithms have been developed using cardiac signals, but they often lack interpretability. Our study introduces a novel interpretable DL approach (SleepECG-Net) for directly estimating OSA severity in at-risk children. A combination of convolutional and recurrent neural networks (CNN-RNN) was trained on overnight electrocardiogram (ECG) signals. Gradient-weighted Class Activation Mapping (Grad-CAM), an eXplainable Artificial Intelligence (XAI) algorithm, was applied to explain model decisions and extract ECG patterns relevant to pediatric OSA. Accordingly, ECG signals from the semi-public Childhood Adenotonsillectomy Trial (CHAT, n = 1610) and Cleveland Family Study (CFS, n = 64), and the private University of Chicago (UofC, n = 981) databases were used. OSA diagnostic performance reached 4-class Cohen's Kappa of 0.410, 0.335, and 0.249 in CHAT, UofC, and CFS, respectively. The proposal demonstrated improved performance with increased severity along with heightened cardiovascular risk. XAI findings highlighted the detection of established ECG features linked to OSA, such as bradycardia-tachycardia events and delayed ECG patterns during apnea/hypopnea occurrences, focusing on clusters of events. Furthermore, Grad-CAM heatmaps identified potential ECG patterns indicating cardiovascular risk, such as P, T, and U waves, QT intervals, and QRS complex variations. Hence, SleepECG-Net approach may improve pediatric OSA diagnosis by also offering cardiac risk factor information, thereby increasing clinician confidence in automated systems, and promoting their effective adoption in clinical practice.

Background Branched-chain amino acid (BCAA) has been reported to be associated with obesity, the association of BCAA with visceral fat area (VFA) and subcutaneous fat area (SFA) remained unclear in patients with type 2 diabetes. Methods This cross-sectional study was conducted in 284 patients with type 2 diabetes mellitus. Enzyme-linked immunospecific assay was used to measure levels of serum BCAA and branched-chain keto acid (BCKA). VFA and SFA were measured with bio-impedance analysis method. The association between BCAA and VFA was calculated using Pearson correlation and multivariable linear regression analysis. Results There were significant differences in the means of body mass index, waist circumstance, SFA and VFA among the three groups divided by total BCAA tertiles (all p < 0.05). Compared to patients with lower levels of serum BCAA (the lower tertile group), the means of VFA and SFA were significantly larger in the middle and upper tertile groups (all p < 0.05). However, the differences in above obesity parameters were nonsignificant according to various BCKA tertiles. Pearson correlation analysis also demonstrated that BCAA levels were positive associated with each obesity parameter (p < 0.05). Nevertheless, multivariable linear regression analysis showed that levels of serum BCAA were correlated with VFA, BMI and WC (all p < 0.05) rather than SFA after adjusted for other confounders. Conclusions levels of serum BCAA were more closely correlated with VFA than SFA, prospective studies should be warranted to further explore the mechanism mediating BCAA and visceral fat accumulation in Human beings. Clinical trial number Not applicable.

Purpose The American Society of Pain and Neuroscience (ASPN) identified a significant gap in resources and guidelines that aim to educate healthcare providers for best practices when engaging on social media. As part of the broader initiatives on Spine and Nerve practice, the executive board of ASPN has decided it would be beneficial to include comprehensive guidance for healthcare providers when engaging on social media. Methods A panel of experts was chosen based on expertise, publications, diversity, and their social media presence. Along with expert guidance, the committee conducted an extensive analysis of peer-reviewed literature in communication and medical journals to determine best practices for healthcare practitioners on social media. Results Social media messages significantly impact patients’ and colleagues’ perceptions and actions regarding medical issues. As such, providers and their teams must be aware of legal and ethical considerations in healthcare while maintaining a consistent, educational, and digestible persona online. Conclusion The advancement of communication and medical technologies and systems necessitates continued education and resources to adapt to our rapidly changing media and medical landscape.

Background Anaplastic large-cell lymphoma primarily involving the omentum is an extremely rare entity with variable clinical presentation. Owing to its rarity and nonspecific clinical manifestation, omental T-cell lymphoma is often diagnosed at a later stage, riddled with complications. While imaging modalities such as computed tomography scan can help a physician reach a diagnosis, cases that present with complications may require a multidisciplinary approach that combines surgical exploration along with consultation from Oncology. Case presentation We hereby report a rare case of a 66-year-old African American male patient who presented to the emergency department with complaints of acute gastrointestinal obstruction. A computed tomography scan of the abdomen and pelvis revealed evidence of an internal hernia and surgical exploration revealed a hemorrhagic and infarcted omentum. Biopsies along with immunophenotypic studies confirmed the diagnosis of anaplastic T-cell lymphoma of the omentum complicated by Massilia timonae infection. Conclusion The case highlights the significance of considering lymphoma, although rare, as a differential in a patient who presents with small bowel obstruction and the importance of investigating for malignancy for early diagnosis and treatment of primary omental lymphomas, before complications develop.

Background The demands of professional tennis, including physical and psychological aspects, contribute to the frequency of retirements at elite levels of the sport. Purpose The aim of this study was to explore the frequency of injuries and the factors that influence the retirements of professional tennis players competing in the Davis Cup over the last two decades. Study Design Retrospective cohort study. Methods The data set includes data from 6,060 men’s singles matches that included 1,814,141 games from Davis Cup ties played between 2000 to 2019. Factors that might influence the retirements were studied by means of generalized linear models using Poisson distribution. Incidence rates by 1000 games and incidence rate ratios of retirements are provided as association measures. Results The retirement incidence was 1.05 per 1000 games [95% CI: 0.90, 1.21]. The main risk factors associated with retirements were matches played on hard courts (IRR: 2.52 [95% CI: 1.32, 4.83]) and matches played in the final two matches of the tie and in a best-of-5-set format (IRR: 2.63 [95% CI: 1.69, 4.09] and IRR: 5.52 [95% CI: 3.50, 8.69], respectively). The most common injuries that led to retirements were those affecting the lower extremities, specifically involving muscular or tendinous tissues. Conclusion This study provides valuable insights for coaches, players, support teams, and epidemiologists regarding retirements and their associated risk factors in Davis Cup tournaments. These findings may guide future research and inform strategies aimed at managing player health and performance in professional tennis. Level of evidence Level 2b.

Apnea of prematurity (AOP) occurs in 85% of neonates ≤34 weeks of gestational age. AOP is frequently associated with intermittent hypoxia (IH). This narrative review reports on the putative relationship of AOP with IH and the resulting oxidative stress (OS). Preterm infants are susceptible to OS due to an imbalance between oxidant and antioxidant systems with the excessive free radical load leading to serious morbidities that may include retinopathy of prematurity, bronchopulmonary dysplasia, and neurodevelopmental delay. Current therapeutic approaches to minimize the adverse effects of AOP and optimize oxygen delivery include noninvasive ventilation and xanthine inhibitor therapy, but these approaches have only been partially successful in decreasing the incidence of AOP and associated morbidities.

Background To determine the optimal fluid resuscitation volume in septic patients with acutely decompensated heart failure (ADHF). Methods Septic patients with ADHF were identified from a tertiary urban medical center. The generalized additive models were used to explore the association between fluid resuscitation volume and endpoints, and the initial 3 h fluid resuscitation volume was divided into four groups according to this model: < 10 mL/kg group, ≥ 10 to ≤ 15 mL/kg group, > 15 to ≤ 20 mL/kg group, and > 20 mL/kg group. Logistic and Cox regression models were employed to explore the association between resuscitation volume and primary endpoint, in-hospital mortality, as well as secondary endpoints including 30-day mortality, 1-year mortality, invasive ventilation, and ICU admission. Results A total of 598 septic patients with a well-documented history of HF were enrolled in the study; 405 patients (68.8%) had sepsis-induced hypoperfusion. Patients with NYHA functional class III and IV were 494 (83.9%) and 22 (3.74%), respectively. Resuscitation volumes above 20 mL/kg (OR 3.19, 95% CI 1.31–8.15) or below 10 mL/kg (OR 2.33, 95% CI 1.14–5.20) significantly increased the risk of in-hospital mortality in septic patients, while resuscitation volumes between 15 and 20 mL/kg were not associated with the risk of in-hospital death in septic patients (OR 1.79, 95% CI 0.68–4.81). In the multivariable Cox models, the effect of resuscitation volume on 30-day and 1-year mortality in septic patients was similar to the effect on in-hospital mortality. Resuscitation volume exceeds 15 mL/kg significantly increased the risk of tracheal intubation, while fluid resuscitation volume was not associated with ICU admission in the septic patients. In septic patients with hypoperfusion, these fluid resuscitation volumes have similar effects on patient outcomes. This association was consistent across the three subgroups with worsened cardiac function, as well as in sensitivity analyses. Conclusions Our study observed that an initial fluid resuscitation volume of 10–15 mL/kg in the first 3 h was optimal for early resuscitation in septic patients with ADHF, particularly those with worsened cardiac function. These results need to be confirmed in randomized controlled trials with larger sample sizes.

Objectives: To evaluate the prognostic utility of CT-imaging-derived biomarkers in distinguishing acute pulmonary embolism (PE) resolution and its progression to chronic PE, as well as their association with clot burden. Materials and Methods: We utilized a cohort of 45 patients (19 male (42.2%)) and 96 corresponding CT scans with exertional dyspnea following an acute PE. These patients were referred for invasive cardiopulmonary exercise testing (CPET) at the University of Pittsburgh Medical Center from 2018 to 2022, for whom we have ground truth classification of chronic PE, as well as CT-derived features related to body composition, cardiopulmonary vasculature, and PE clot burden using artificial intelligence (AI) algorithms. We applied Lasso regularization to select parameters, followed by (1) Ordinary Least Squares (OLS) regressions to analyze the relationship between clot burden and the selected parameters and (2) logistic regressions to differentiate between chronic and resolved patients. Results: Several body composition and cardiopulmonary factors showed statistically significant association with clot burden. A multivariate model based on cardiopulmonary features demonstrated superior performance in predicting PE resolution (AUC: 0.83, 95% CI: 0.71–0.95), indicating significant associations between airway ratio (negative correlation), aorta diameter, and heart volume (positive correlation) with PE resolution. Other multivariate models integrating demographic features showed comparable performance, while models solely based on body composition and baseline clot burden demonstrated inferior performance. Conclusions: Our analysis suggests that cardiopulmonary and demographic features hold prognostic value for predicting PE resolution, whereas body composition and baseline clot burden do not. Clinical Relevance: Our identified prognostic factors may facilitate the follow-up procedures for patients diagnosed with acute PE.