Ochsner Medical Center

Avelumab, pembrolizumab, and enfortumab vedotin (EV) demonstrated efficacy in mUC following platinum-based chemotherapy. However, real-world data in patients with urothelial carcinoma with squamous differentiation (UCSD) are limited. The aim of this study is to assess the real-world clinical outcomes of avelumab, pembrolizumab, or EV in mUCSD patients. The ARON-2EV study is a retrospective, international, multicenter analysis in patients with mUC treated with avelumab, pembrolizumab, or EV across 79 centers in 21 countries. Patients were divided into three cohorts: 1 (avelumab), 2 (pembrolizumab), and 3 (EV). Primary endpoints were overall survival (OS) and time on treatment (ToT). Secondary objectives included evaluating clinical factors associated with outcomes and exploring the impact of UCSD histology on response to therapy. Statistical methods included Kaplan-Meier estimates, log-rank tests, Fisher's exact and chi-square tests, and Pearson's correlation coefficients. A total of 1918 patients, 1696 with advanced pure UC (pUC) and 222 with mUCSD (36 in cohort 1, 111 in cohort 2, and 75 in cohort 3), were included. Median OS was shorter in patients with UCSD compared to patients with pUC histology in the three cohorts (1: 13.0 vs 26.8months, HR 2.66,p = 0.003; 2: 10.2 vs 18.5months, HR 1.52,p = 0.008; and 3: 7.6 vs 13.1months, HR 1.68,p = 0.011). Median ToT was shorter in patients with UCSD compared to patients with pUC histology in cohort 1 (3.5 vs 5.6months, HR 1.57,p = 0.044) and 3 (7.6 vs 13.6months, HR 1.83,p = 0.005) but not in cohort 2 (3.7 vs 4.7months, HR 1.19,p = 0.177). Response to therapy was negatively correlated with UCSD histology in cohorts 2 (correlation coefficient 0.094,p = 0.008) and 3 (correlation coefficient 0.107,p = 0.021), while response to avelumab was not correlated with UCSD (correlation coefficient 0.072,p = 0.263). UCSD is a histology with a poor prognosis and response to treatments compared to pUC. Treatments activity and effectiveness in divergent differentiations should be addressed in dedicated prospective studies. NCT05290038.

The rapid adoption of telemedicine has transformed healthcare delivery in the U.S., enhancing access and communication for surgical patients across wide geographic areas. However, a critical challenge persists: the need to define and standardize quality metrics specifically for telemedicine in surgery. Existing studies suggest that telemedicine can yield equivalent or improved outcomes compared to in-person visits. Nevertheless, literature remains limited in evaluating patient satisfaction, cost-effectiveness, and diagnostic accuracy. Through expert consensus within the American College of Surgeons Board of Governors Telehealth Pillar, we propose a structured framework for defining and implementing quality metrics for surgical telemedicine. This is based on the Donabedian model, addressing structure, process, and outcome, while also considering the distinct phases of surgical care: pre-operative, intra-operative, and post-operative. This framework identifies unique domains of telemedicine in surgical care, emphasizing hospital and organizational structure, patient and provider readiness, and policy alignment. Comparative analysis against existing AHRQ and WHO frameworks highlights gaps in surgical applicability. Finally, we propose an implementation roadmap prioritizing immediate, feasible metrics while identifying areas for future validation. Collaboration among researchers, clinicians, and policymakers will be essential to establish these metrics and ensure that telemedicine delivers on its potential to improve surgical care delivery while addressing disparities in access and outcomes.

IntroductionBrain glucose hypometabolism precedes cognitive decline in Alzheimer's disease, however its role in determining long-term cognitive trajectories remains under studied in current literature in a clear manner. We investigated whether baseline brain glucose metabolism predicts cognitive decline rates and disease conversion risk in a large longitudinal cohort.MethodsWe analyzed 4,732 participants (1,685 with longitudinal cognitive data) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with fluorodeoxyglucose positron emission tomography (FDG-PET), Mini-Mental State Examination (MMSE), and Alzheimer's Disease Assessment Scale (ADAS) measurements over ten years. Mixed-effects models investigated time × brain glucose metabolism interactions on cognitive decline. Cross-validation assessed predictive accuracy for mild cognitive impairment and Alzheimer's disease conversion.ResultsBrain glucose metabolism was found to modulate the cognitive decline rates (time × FDG interaction: MMSE β = 0.746, P-value <0.001; ADAS β = −1.595, P-value <0.001). High versus low glucose metabolism demonstrated 1.49 MMSE points/year and 3.19 ADAS points/year protection. Among cognitively normal participants, low glucose metabolism increased Alzheimer's disease conversion risk four-fold (incidence rate ratio = 3.79, 95%CI: 2.94–4.88). Predictive models achieved high accuracy for Alzheimer's disease conversion (AUC = 0.826) with good calibration (Brier score = 0.092). High-metabolism individuals showed essentially stable cognition over ten years follow-up duration as evident in the ADNI dataset.ConclusionsWe found that brain glucose metabolism is a notable determinant of cognitive decline progression, especially for Alzheimer’s disease risk, providing quantifiable metabolic protection against decline. Our results demonstrate brain glucose hypometabolic findings from baseline FDG-PET as a precision biomarker for therapeutic stratification and support further interventions for cognitive preservation for further research, validation and development purposes that should be further evaluated and investigated in further clinical trials that may lead to better preventive and therapeutic benefits for cognitive functions preservation and prevention of cognitive decline process in high-risk individuals.

What use has the past? This paper explores its specific utility to the field of medical education. It particularly focuses on the value of history for educators (as opposed to students) by highlighting its potential to contribute in three areas. First, it examines the professional rupture in medical history as an example to avoid - and provides specific suggestions to retain unity. Second, in comparing how the humanities foundation of history privileges different modes of inquiry than the social sciences, it highlights how such methodology - in particular oral histories and material culture - might enrich educational scholarship. Finally, it suggests different ways of incorporating history into the classroom, such as interleaving eponyms, as a way to improve student retention and facilitate their ability to think more broadly, more ethically, and more empathetically.

Continuous glucose monitoring (CGM) use among patients with type 1 diabetes mellitus (T1DM) has been associated with improved glycemic control, though improvement in non-glycemic outcomes is less consistent. We hypothesize that CGM use in patients with T1DM in a real-world clinical setting is associated with both improved glycemic and clinical outcomes.This was a retrospective cohort study of patients with T1DM receiving care at a large health system from 2016 to 2023. Primary outcomes included (1) glycemic control and (2) a composite comprising severe maternal morbidity, preeclampsia with severe features, delivery prior to 34 weeks, and admission for diabetic ketoacidosis. Primary glycemic outcome was hemoglobin A1c (HbA1c) <6% in the second trimester. We compared patients using CGM, our exposure group, to patients using traditional blood glucose monitoring (TBGM). During initial data abstraction, we noted variation in CGM target blood glucose settings. A subgroup analysis was performed in which patients using CGM were evaluated by device setting, with those set to targets consistent with American Diabetes Association (ADA) recommendations compared with those with more permissive goals. Adjusted odds ratios were calculated using multivariable logistic regression to adjust for potential confounding variables.Among 288 patients with T1DM, there were 145 deliveries in the CGM group and 143 in the traditional capillary blood glucose monitoring group. Midtrimester on-target glycemic control was improved in the CGM group compared with traditional monitoring (40.7 vs. 17.5%, adjusted odds ratio [aOR] = 2.32; 95% confidence interval [CI]: 1.21-4.12). There was no difference in the rate of the composite outcome (CGM: 42.8% vs. TBGM: 49.0%, aOR = 0.70; 95% CI: 0.40-1.22), nor was there a difference in secondary outcomes. In patients using CGM, those with stricter targets had improved glycemic control as well as reduced rates of preterm delivery prior to 37 weeks (18.8 vs. 56.9%, aOR = 0.16, 95% CI: 0.05-0.48) and neonatal intensive care unit admission (37.5 vs. 60.0%, aOR = 0.37, 95% CI: 0.14-0.96).CGM use in T1DM is associated with improved glycemic control throughout pregnancy; however, this does not uniformly translate to improved clinical outcomes. Lack of adherence to ADA blood glucose targets may contribute to these findings. · Glycemic control in pregnancy is improved with CGM use in patients with T1DM.. · CGM use does not translate to consistent improvement in clinical outcomes.. · Stricter CGM targets are associated with improvement in glycemic control and some clinical outcomes.. · Simply prescribing an intervention does not automatically lead to benefit..