Citations

OBJECTIVE Ganglioneuromas (GNs) are rare benign tumors arising from sympathetic neural crest derivatives, with limited large-scale data guiding management. The objective of this study was to characterize the clinical presentation, imaging features, surgical management, and long-term outcomes of patients with GN treated at a single institution over a 30-year period. METHODS The authors conducted a retrospective review of all patients diagnosed with GN between 1995 and 2025 at a single institution. Clinical data, imaging characteristics, operative details, perioperative complications, and long-term outcomes were abstracted. RESULTS A total of 101 patients (62.3% female, mean age 26.9 ± 15.9 years) were identified. Tumors most commonly arose in the retroperitoneum (n = 46, 45.5%), thoracic paraspinal/mediastinal region (n = 33, 32.7%), presacral space (n = 18, 17.8%), and cervical region (n = 4, 4%). The mean tumor dimensions on MRI were 8.5 ± 3.8 × 6.6 ± 3.2 × 5.8 ± 3.7 cm. Most lesions (72%) were incidental findings. Seventy patients underwent 72 surgeries, of which 69.4% had preoperative biopsy confirmation. Gross-total resection (GTR) was achieved in 73.6% of cases (53/72) and subtotal resection (STR) was performed in 26.4% (19/72). Short-term postoperative complications occurred in 43.1% of cases, most commonly neurological deficits (22.2%). The mean hospital length of stay was 4.6 ± 3.7 days. At the final follow-up (mean duration 33.8 ± 42.6 months), 46.5% of patients were stable, 42.3% had improved, and 11.3% had worsened from baseline. Two patients experienced recurrence (2.9%, 2/70). No malignant transformations were observed. Thirty-one patients were managed with observation (mean age 32.3 ± 17.7 years; mean follow-up duration 90.9 ± 151 months). Observation was chosen primarily due to proximity to major vascular or neural structures (74.2%). No patient in the observation group developed new symptoms, and 2 tumors exhibited minimal interval growth (0.08–0.17 cm/year). CONCLUSIONS GNs demonstrate indolent behavior, low recurrence rates, and no observed malignant transformation in this large cohort. GTR is achievable in most cases, but STR provides excellent long-term control when required to avoid morbidity. Observation is safe for asymptomatic tumors, particularly when adjacent to critical structures, with no growth observed on long-term follow-up, except for minimal growth in few cases. These findings support an individualized, risk-based approach to management.

OBJECTIVE This study examines the recovery rates of patients who experience postoperative dysphagia within 1 month following cervical spine surgery. METHODS Data from a prospectively maintained multi-institutional quality registry were retrospectively analyzed. Eating Assessment Tool-10 (EAT-10) questionnaire scores were collected at baseline and 1, 3, and 12 months postoperatively, with total scores ≥ 3 indicating dysphagia. Patients were grouped by whether they reported baseline dysphagia to assess the impact of baseline dysphagia on recovery. Recovery was defined as resolution of postoperative dysphagia and not reporting the condition at any follow-up time point. Patients were excluded from the recovery model if they did not report dysphagia within 1 month of surgery. Recovery to baseline was defined as reporting a postoperative EAT-10 score equal to or less than the baseline score at subsequent time points. Patients were excluded from the recovery-to-baseline model if they did not report EAT-10 scores within 1 month of surgery that were worse than their baseline score. Survival curves were generated for both models. RESULTS Of the 2003 patients in the registry, 627 met inclusion criteria for the recovery curve and 714 for the recovery-to-baseline curve. Of the patients without baseline dysphagia, 498 developed new postoperative dysphagia within 1 month, with cumulative recovery probabilities of 39.5% by 3 months and 59.1% by 12 months after cervical spine surgery. Furthermore, of the patients without baseline dysphagia, 73.5% (175/238) who reported no dysphagia at 3 months and 32.5% (68/209) who reported no dysphagia at 12 months experienced long-term recovery. Eighty patients with baseline dysphagia reported worse EAT-10 scores within 1 month, with cumulative probabilities of improvement to baseline or below of 37.7% by 3 months and 54.1% by 12 months. Patients with baseline dysphagia were significantly less likely to recover than patients without baseline dysphagia (hazard ratio [HR] 0.37, 95% CI 0.26–0.53; p < 0.001) but significantly more likely to recover to baseline (HR 1.45, 95% CI 1.05–2.00; p = 0.025). CONCLUSIONS Patients who develop postoperative dysphagia within 1 month of cervical spine surgery generally see symptomatic improvement over time. This analysis may aid in clinical decision-making when informing patients about the risk of developing postoperative dysphagia and the recovery rate of this surgical complication.

Introduction/Objectives The rise in screening for social drivers of health (SDoH) in primary care settings has led to questions about effective intervention design. A large primary care practice at Mayo Clinic developed a model centered on a full-time Health Equity Coordinator (HEC) to facilitate clinic-community partnerships in 2022. The goal of this analysis was to assess the model on process outcomes, resolution of SDoH needs, and changes in healthcare utilization. Methods Using a cohort study design, we identified primary care patients with unmet SDoH needs at the intervention clinic and two comparator clinics from March 2022 to December 2023. We assessed process outcomes descriptively and resolution of SDoH needs and healthcare utilization using multivariable regression. Results The HEC contacted 348 patients and conducted 748 meetings with community-based organization staff. While there were decreases for SDoH needs and missed or late cancelled appointments in intervention group, there were no significant difference in resolution of SDoH and healthcare utilization relative to comparator groups. Conclusions The HEC model for multi-stakeholder coordination showed promise in referring patients to services and engaging key stakeholders in a primary care setting. Longer term follow up may be needed to identify changes in SDoH needs and healthcare utilization.

Abstract Introduction Distinct temperature patterns have long been recognized to correlate with fevers of differing etiologies. While the use of wearable sensors for high-frequency temperature monitoring (HFTM) on a near minute-by-minute basis has been shown to detect fevers earlier than standard-of-care nursing vital sign assessments in hospitalized patients, leveraging these high-resolution datasets to computationally identify unique digital signatures for real-time diagnosis of underlying fever etiology has not been widely explored. Diagnostic uncertainty is common in patients undergoing hematopoietic stem cell transplantation (HCT), with only 20–30% of febrile neutropenic episodes being microbiologically documented. We hypothesized that unique temperature patterns extracted from HFTM data collected during episodes of febrile neutropenia could be used to develop a supervised machine learning classifier capable of accurately predicting underlying fever etiology in HCT patients. Methods We analyzed 68 clinically independent fever episodes recorded in HCT patients (n=90) outfitted with an FDA-cleared wireless temperature sensor (TempTraq®, BlueSpark Technologies) that measured axillary temperature every 2 minutes throughout hospitalization. Time-series features were extracted from temperature traces spanning 1 hour before to 3 hours after fever onset and used to train a suite of machine-learning models to distinguish engraftment fevers from other fever etiologies. Model training and evaluation were performed using repeated stratified 5-fold patient-level cross-validation, yielding 100 train-test evaluations. Results Among all classification models, the logistic regression classifier provided the best overall performance and interpretability, achieving 94% specificity (95% CI, 0.84–1.0) for identifying engraftment fevers with a mean AUROC of 0.88 ± 0.10. Feature importance analysis demonstrated that both clinical variables and HFTM-derived temperature dynamics contributed to model performance, with a strong reliance on time-series features captured within the first 4 hours of fever onset. Conclusion Our study provides a demonstration that continuous temperature data collected from patients outfitted with wearable sensors can be leveraged not only for early fever detection but also for machine learning–based diagnosis of fever etiology. These findings suggest that dynamic temperature patterns contain clinically meaningful physiologic information that with further studies could support real-time diagnostic decision-making and guide safe de-escalation of empiric antibiotics during febrile neutropenia in patients undergoing intensive cancer therapy.

ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors. Many of these challenges must be addressed during the process of simulation. This report provides guidelines for pediatric radiotherapy simulation from the Children's Oncology Group. These guidelines cover all anatomic sites and include recommendations for photon and proton therapies, as well as specialized procedures such as stereotactic body radiation therapy, brachytherapy, and total body irradiation. These guidelines are presented as recommendations rather than prescriptive standards as the practice will vary depending on patient age, diagnosis, clinical judgment, and institutional resources.

Hospital medicine offers diverse career opportunities, yet formal guidance for residents pursuing hospitalist careers is often lacking. To address this gap, the Hospital Internal Medicine Interest Group (HIMIG) was launched at an academic institution in the Southeastern United States to provide structured mentorship and professional development. Residents expressing interest completed an entry survey to identify career goals and areas of focus, informing a longitudinal curriculum that included education, leadership, research, quality improvement, and networking. Seventeen residents (≈25% of the IM residency program) joined HIMIG, and 88% completed the initial survey. Education, leadership, and quality improvement were top interests, while mentorship and career guidance were primary motivators. A post-implementation survey revealed all participants met mentors and felt HIMIG supported their career goals. HIMIG demonstrates a flexible, personalized approach to hospitalist career development that may serve as a model for other programs.

Ultrafast oscillations (UFOs) are brief bursts of high-frequency (2–8 kHz) activity recorded using depth electrodes in epileptic brain tissue. While reliably detected at small scales using microelectrodes, UFOs have thus far likely not been observed at larger scales using macroelectrodes. Here we show that faint echoes of these bursting patterns can be detected in macroelectrode signals using a model of cross-scale propagation. To model this cross-scale effect, we extend the classical damped wave equation to include an explicit scale coordinate governed by the dilation operator. We then use Green's functions to obtain an expression for the spectral echo expected at the macroelectrode scale. This echo takes the form of a carrier envelope modulated by the temporal structure of the original microscale bursting event. We test the predicted signature echo pattern in human intracranial recordings from eleven epilepsy patients implanted with both micro- and macroelectrodes. Statistically significant echoes are confirmed in two out of eleven patients, appearing in 2% of all tested micro-macro pairs.

Background: Noninvasive tests are well validated in metabolic dysfunction–associated steatotic liver disease, but evidence in metabolic dysfunction and alcohol-associated liver disease (MetALD) and alcohol-associated liver disease (ALD) is limited. We evaluated noninvasive test–based clinical care pathways for fibrosis risk stratification in MetALD and ALD. Methods: This is a multinational, multicenter, cross-sectional study across 35 centers in 16 countries (2013–2025), including adults with MetALD or ALD. Fibrosis was assessed by liver biopsy and/or vibration-controlled transient elastography (VCTE). In biopsy-proven participants, we analyzed the sequential pathway (Fibrosis-4 [FIB-4] first, followed by VCTE for indeterminate FIB-4) to identify advanced fibrosis (≥F3). Diagnostic accuracy was assessed using the AUC. Results: Among 893 participants (41.3% MetALD and 58.7% ALD), the median age was 52 [43.0–61.0] years, and 79.4% were male. The estimated prevalence of advanced fibrosis was 45% (32.2% in MetALD and 54.0% in ALD). Participants with MetALD had a more dysmetabolic profile but lower fibrosis stages than ALD. Among biopsy-proven participants, FIB-4 AUC was 0.720, and VCTE AUC was 0.833. FIB-4 performed better in MetALD than ALD (AUC 0.773 vs. 0.540), while VCTE accuracy was similar across groups. In the sequential pathways, the false-negative rate for advanced fibrosis (misclassified as low risk) was 6.8% (4.9% MetALD and 11.3% ALD). Conclusions: In biopsy-proven patients, FIB-4 performance was acceptable in MetALD but substantially weaker in ALD. The standard 2-step pathway performed adequately in MetALD but missed a clinically meaningful proportion of advanced fibrosis in ALD.