Citations

Abstract In epilepsy patients lacking magnetic resonance imaging‐visible lesions such as focal cortical dysplasia (FCD), surgical resections target regions with abnormal electroencephalographic (EEG) activity. However, histopathological identification of subtle cortical architectural abnormalities in these specimens remains challenging. We investigated whether artificial intelligence (AI)‐based morphometric and spatial analysis of NeuN‐stained cortical sections could detect neuronal architectural disorganization in epilepsy resections, including regions without definitive histologic dysplasia. Whole slide images were generated from 83 FCD regions and 19 neurologically normal autopsy controls. Regions of interest were annotated in QuPath as FCD, FCD‐adjacent, FCD‐distant, apparently normal (abnormal EEG without histologic dysplasia), and true normal (autopsy controls). NeuN‐positive neurons were detected using QuPath (90% sensitivity, 12% false positive rate). Spatial and morphometric features—including neuronal clustering, distribution inhomogeneity, and nuclear morphology—were extracted and used to train a multinomial, Least Absolute Shrinkage and Selection Operator‐regularized regression classifier. The classifier achieved 70.6% accuracy in subregion classification and 88.2% accuracy in overall specimen diagnosis. Notably, regions with abnormal EEG but lacking histologic dysplasia exhibited quantifiable architectural disorganization similar to those seen in areas adjacent to FCD and distinct from control tissue. AI‐driven analysis of neuronal morphology and spatial distribution reveals subtle cortical disorganization in epilepsy resections, including in histologically ambiguous regions. Further investigation is warranted to determine if this methodology can enhance the diagnostic yield of neuropathological evaluation and support more precise surgical targeting in epilepsy.

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The accurate prediction of motor progression in Parkinson’s disease (PD) remains a major clinical challenge that limits personalized treatment planning and efficient clinical trial design. In this study, we developed and validated a machine-learning framework integrating a targeted panel of plasma proteins measured by Olink proximity extension assays with clinical variables to stratify patients according to their progression risk. We analyzed baseline plasma samples from 211 early-stage PD patients enrolled in the Parkinson’s Progression Markers Initiative (PPMI) cohort using four targeted Olink panels, from which 28 circulating proteins were retained after quality-control filtering. Patients were classified as rapid or slow progressors based on their annualized change in MDS-UPDRS Part III scores. Among the algorithms tested, Random Forest achieved the highest discriminative performance with an area under the receiver operating characteristic curve (AUC) of 0.751 (95% CI: 0.684–0.811), which exceeded that of clinical predictors alone (AUC 0.666). The integration of targeted proteomic and clinical features further improved model performance (AUC 0.773; p = 0.009). Nested cross-validation confirmed minimal optimistic bias (AUC 0.743). To enhance clinical interpretability, we applied SHapley Additive exPlanations (SHAP) analysis, which identified interleukin-6 (IL-6), brain-derived neurotrophic factor (BDNF), and vascular endothelial growth factor A (VEGF-A) as the most influential predictors. SHAP feature rankings were highly stable across cross-validation folds (mean Spearman ρ = 0.91). The robustness of these findings was confirmed through sensitivity analyses using extreme quartile comparisons (AUC 0.823), treatment-naïve subgroup analysis (AUC 0.738), and a clinically anchored outcome definition based on the minimal clinically important difference (AUC 0.739). A decision curve analysis demonstrated a net clinical benefit across threshold probabilities of 0.25–0.70. Our results establish targeted plasma protein profiling combined with interpretable machine learning as a promising tool for PD motor progression risk stratification, with potential applications in individualized patient counseling regarding motor prognosis and the selection of candidates for disease-modifying trials.

Background: To our knowledge, there are no studies assessing associations between patients on preoperative estrogen replacement therapy (ERT) undergoing distal radius open reduction and internal fixation (DRORIF) and postoperative outcomes. Thus, the purpose of this study was to compare surgical and medical complications in patients on ERT undergoing DR-ORIF with a matched control cohort. Materials and Methods: The PearlDiver Mariner database was searched for female patients who took ERT within 3 months of the index procedure. Patients were matched 1:4 with non-ERT controls using propensity score matching. Complications were assessed at 90 days, 2 years, and 5 years. Statistical analyses were conducted using odds ratios (OR) with 95% confidence intervals (CI). Statistical significance was determined at a P value of <.05. Results: The ERT cohort consisted of 1,815 ERT users, and the control cohort consisted of 7,247 patients. At 2 years, the ERT cohort was associated with a slightly greater incidence of malunion/nonunion (OR, 1.57; 95% CI, 1.13–2.18) but with no increased risk of revision surgery (OR, 1.10; 95% CI, 0.50–2.10). Similarly, at 5 years, the ERT cohort was associated with a slightly higher likelihood of a malunion/nonunion diagnosis (OR, 1.69; 95% CI, 1.24–2.30). Conclusion: The current study suggests that patients on preoperative ERT had a slightly increased risk of malunion/nonunion at 2 years and 5 years after DR-ORIF. We did not find associations between increases in the risk of any other major or minor complications and the cohort of patients on preoperative ERT within 5 years postoperatively.

BACKGROUND AND OBJECTIVES: The Congress of Neurological Surgeons (CNS) Leadership Institute developed the first structured leadership program designed specifically for neurosurgeons. Led by the experts in neurosurgery, health care administration, and business, the program provides formal leadership training and mentorship aimed at advancing neurosurgeons' professional development at local, regional, national, and international levels. METHODS: The CNS Leadership Institute offers 2 curricula tailored for junior and senior faculty. Training begins with assigned readings, webinars, and online lectures that establish essential leadership principles. Core learning occurs during 2 in-person courses featuring interactive lectures, feedback sessions, and a longitudinal leadership project guided by national mentors. Program outcomes were assessed through a 40-question survey of alumni evaluating training effectiveness, skill application, and career advancement. RESULTS: Since 2016, 195 neurosurgeons have completed the CNS Leadership Institute. Among the 77 survey respondents, 70.1% reported significant professional advancement (new leadership role or job transition), and 64.8% directly attributed their advancement in skills and insights acquired through the program. Overall program effectiveness was rated 4.4 of 5, and the mean likelihood-to-recommend was 8.95 (95% CI: 8.70-9.20), yielding a Net Promoter Score of +63 (95% CI: +49 to +77). Alumni have assumed prominent roles including 16 Residency Program Directors, 3 Department Chairs, 1 Vice Dean, 4 Service Line Leaders, 13 CNS Executive Committee members, and over 100 committee or editorial board appointments critical to the specialty. CONCLUSION: The CNS Leadership Institute equips neurosurgeons with structured leadership training, mentorship, and practical tools to enhance their effectiveness as leaders. Survey results confirm that the program has a measurable impact on participants' career trajectories and professional growth. This initiative provides a reproducible model for cultivating the next generation of neurosurgical leaders and advancing the specialty's capacity for strategic, transformational leadership.

Abstract Context Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are widely prescribed for type 2 diabetes and obesity and can lead to substantial weight loss. In patients taking levothyroxine, weight loss can reduce thyroid hormone requirements and potentially associated adverse effects. Thyroid-stimulating hormone (TSH) monitoring is essential but unclear whether thyroid function is routinely reassessed after GLP-1 RAs initiation. Objective Examine the changes in the timing of TSH testing after GLP-1 RAs. Design Retrospective cohort study emulating a target trial using Medicare from January 1, 2011, to December 31, 2020. The primary analysis followed an intention-to-treat approach. Patients were matched 1:1 using propensity scores. Logistic regression models and informed by least absolute shrinkage operator variable selection were used. Setting The 15% sample of U.S. Medicare fee-for-service claims data. Patients or Other Participants Adults aged ≥65 years with type 2 diabetes on a stable levothyroxine dose at baseline. Intervention(s) Initiation of GLP-1 RAs vs initiation/ongoing use of sodium-glucose cotransporter-2 inhibitors (SGLT-2is). Main Outcome Measure(s) TSH testing during follow-up. Results Among 5370 matched patients, the mean age was 73.2 years. 71.6% were women, and 87.1% were White. Approximately 83.0% of patients in both treatment groups receive a TSH testing within a 1-year follow-up. The mean time to TSH testing was approximately 130.5 days for both groups. Conclusion TSH testing patterns did not differ between GLP-1 RAs and SGLT-2is, despite the greater likelihood of requiring levothyroxine dose adjustment associated with weight loss seen with GLP-1 RA therapy. Given levothyroxine's widespread use, this gap suggests missed opportunities for timely and weight-responsive thyroid monitoring.

Abstract Aims Obesity is linked with worse outcomes in hypertrophic cardiomyopathy (HCM). While both bariatric surgery (BS) and GLP-1 receptor agonists (GLP-1RA) promote weight loss and may improve cardiometabolic risk, their comparative outcomes in HCM remain unclear. Methods and results Adults with HCM and body mass index (BMI) ≥ 30 kg/m were divided into two cohorts: (i) GLP-1 RA users who never had BS, and (ii) BS patients who never received GLP-1 RA. Propensity score matching (1:1) was performed to balance demographics, comorbidities, and medications. Outcomes over 24 months include all-cause mortality, acute heart failure (HF) hospitalization, arrhythmias, change in BMI, and cardiovascular symptoms. Hazard ratios with 95% confidence intervals were estimated using Cox models. Of 5002 patients, 955 were included in each matched cohort after matching (mean age 54 ± 13 years, 70% female, BMI 40.0 kg/m). GLP-1 RA was associated with a significantly lower observed rate of all-cause mortality compared with BS (2.0% vs. 4.4%; HR 0.46; 95% CI 0.27–0.80; P = 0.004) and HF hospitalization (8.7% vs. 14.0%; HR 0.60; 95% CI 0.46–0.79; P &lt; 0.001). Similarly, GLP-1 RA use was associated with a lower incidence of composite cardiovascular outcomes (10.7% vs. 17.2%; HR 0.60; 95% CI 0.47–0.77; P &lt; 0.001). Rates of arrhythmia and cardiovascular symptoms were comparable between the two groups. BMI reduction was greater after bariatric surgery (−4.0 vs. −2.6 kg/m; P &lt; 0.001). Conclusion In obese patients with HCM, GLP-1 RA therapy was associated with lower all-cause mortality and fewer HF events compared with BS. Future studies are warranted to confirm our findings.

Abstract Aims Left bundle branch block (LBBB) is associated with mechanical dyssynchrony, heterogeneous perfusion, and adverse left ventricular (LV) remodelling. However, not all patients with LBBB develop cardiomyopathy, and dyssynchrony can occur without conduction defects. The role of microvascular dysfunction remains uncertain. We aimed to assess how mechanical dyssynchrony and perfusion heterogeneity relate to LV remodelling and function in patients with and without LBBB. Methods and results We analysed 233 patients with LBBB and 932 matched controls who underwent PET myocardial perfusion imaging, assessing mechanical dyssynchrony (phase entropy), LV volumes, and ejection fraction (EF); coronary vascular resistance (CVR), myocardial blood flow (MBF), myocardial flow reserve (MFR) as markers of microvascular function; and septal-to-lateral MBF ratio (SLR) as a measure of regional perfusion heterogeneity. Compared with controls, LBBB patients had greater dyssynchrony (56% vs. 40%), larger LV volumes, and lower EF (54% vs. 67%) (all P &lt; 0.001), as well as higher stress CVR (37 vs. 34 mmHg/mL·min−1·g−1), and lower MBF (2.4 vs. 2.6 mL/min/g), MFR (2.4 vs. 2.6), and SLR (0.95 vs. 1.00) (all P &lt; 0.05). Among patients with dyssynchrony, SLR &lt;1.0 identified greater remodelling. In multivariable regression, phase entropy and SLR independently predicted LV volumes and EF, with adverse effects of SLR reduction amplified in LBBB (interaction P &lt; 0.01). In Cox analysis, phase entropy (HR:1.02, P = 0.01), MFR (HR:0.62, P &lt; 0.001), and LVEF (HR:0.97, P &lt; 0.001) were independently associated with death or heart failure hospitalization, whereas LBBB was not. Conclusion Mechanical dyssynchrony and perfusion heterogeneity independently predict adverse LV remodelling, irrespective of LBBB. Integrated imaging improves cardiomyopathy stratification.

Abstract Objectives Minimally invasive cardiac surgery (MICS) offers significant advantages over conventional sternotomy, including reduced trauma and faster recovery. Preoperative planning is crucial, with computed tomography (CT) emerging as an essential imaging tool. This systematic review aims to evaluate CT’s role in MICS planning, focusing on imaging protocols, surgical guidance, and patient outcomes. Methods This study included studies published between January 2003 and January 2025 that examined the role of CT imaging in planning minimally invasive valvular heart surgery. A comprehensive search was conducted in Medical Literature Analysis and Retrieval System Online (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Excerpta Medica Database (EMBASE) using predefined keywords and medical subject headings (MeSH) terms related to CT imaging, angiography, minimally invasive surgery, robotic surgery, aortic valve surgery, and mitral valve surgery. Results Initial search found 378 studies, and 17 studies were included in the review. The studies highlight CT’s value in assessing surgical feasibility, vascular access, and risk stratification. CT aids in selecting arterial cannulation sites, guiding aortic occlusion strategies, and optimizing port placement. It also identifies contraindications, such as extensive atherosclerosis and anatomical abnormalities, that may necessitate sternotomy. Conclusions Current evidence underscores CT’s critical role in optimizing MICS planning and enhancing patient safety.