Citations

Abstract We present a comprehensive global analysis of genetic variants associated with autosomal-dominant Alzheimer’s disease (ADAD). A total of 550 variants in the APP, PSEN1 and PSEN2 genes were identified, of which 279 were classified as pathogenic or likely pathogenic based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria, utilizing data from the Dominantly Inherited Alzheimer Network (DIAN), literature and public databases. Symptomatic age at onset (AAO) data were estimated for 227 of these variants, allowing detailed characterization of their frequency, pathogenicity and AAO. Importantly, 226 variants met eligibility criteria for inclusion in disease-modifying clinical trials. Furthermore, we demonstrated the predictive value of mean variant AAO and parental AAO in predicting symptomatic AAO, validated against converters who became symptomatic during follow-up in the DIAN Observational Study. This dataset provides critical insights into the global landscape of ADAD and reveals the genetic and AAO heterogeneity of ADAD variants while refining variant trial eligibility criteria.

Achondroplasia accounts for approximately 70% of all forms of dwarfism. Cesarean delivery is often required in parturients with achondroplasia due to cephalopelvic disproportion. There is no consensus on the optimal management for cesarean delivery considering the difficulties in both general and regional anesthesia in patients with achondroplasia. The aim of this study was to explore the literature for prior case reports and series to determine the optimum anesthetic management for cesarean delivery in achondroplastic patients. We conducted a review of the literature using Embase, Medline, Scopus, and Web of Science database searches for case series and case reports on achondroplasia and pregnancy through January 2024. Conference abstracts >3 years old were excluded, as well as data on forms of dwarfism other than achondroplasia, patients taller than 147 cm, and non-English language papers. Extracted data included demographic information, anesthetic management, and reported complications. The literature review resulted in 57 manuscripts with a total of 80 anesthetics. Anesthetic management consisted of planned general anesthesia (n = 16), single injection spinal (n = 28), epidural (n = 17), combined spinal-epidural (n = 12), and intrathecal catheter (n = 1). Six patients required conversion from neuraxial anesthesia to general anesthesia due to failed neuraxial placement (n = 3), inadequate blockade (n = 2), and high neuraxial block (n = 1). Reduced dose of intrathecal bupivacaine was common in this population. Complications such as hypotension (4 in 64), inadvertent dural puncture (1 in 64), and transient paresthesia (3 in 64) during neuraxial technique were reported but were infrequent. Neuraxial anesthesia is more common and a viable option in carefully selected parturients with achondroplasia. We recommend reduction of intrathecal local anesthetic as part of a titratable neuraxial technique (ie, combined spinal-epidural) that minimizes the risk of hypotension, high spinal, and emergent intubation.

Background Our study was designed to determine the safety, efficacy, and immunological effects of perioperative pembrolizumab in early-stage NSCLC. Methods This is a single-arm phase II study of perioperative pembrolizumab in patients with untreated, clinical stage IB to IIIA NSCLC. Patients received two doses of 200 mg pembrolizumab, surgery, standard adjuvant chemotherapy, followed by four doses adjuvant pembrolizumab. The primary objective of this study was to determine surgical feasibility rate, and secondary objectives are pathological response rate, treatment adverse events, efficacy data, and exploratory analysis of biomarkers. Results 30 patients initiated perioperative pembrolizumab, and 25 completed tumor resection. At median follow-up of 59 months after surgical resection, seven patients had disease progression, while six had died representing. A 5-year progression-free survival (PFS) from time of surgery was 72.0% (56.4%–91.9%) and overall survival (OS) from time of surgery was 75.8% (60.7%–94.7%). Major pathological response (MPR) was found in seven tumors (28%) including two complete responses (4%). Across all treated patients, four receiving neoadjuvant and four receiving adjuvant pembrolizumab experienced treatment-related adverse events of grade 3 or higher with no grade 5 events. Plasma proprotein convertase subtilisin/kexin type 9 (PCSK9) levels increased across our patient cohort over time from baseline until postsurgery and remained elevated at the end of treatment. There was a significant difference between mean plasma PCSK9 levels for patients with MPR versus all other patients on study when checked postoperatively. Conclusions Perioperative pembrolizumab was safe and effective with promising MPR rate, PFS, and OS.

Abstract Background: Prostate artery embolization (PAE) requires a careful understanding of pelvic arterial anatomy and identifying prostatic artery variants. Pre-procedure CTA and intra-procedural cone beam CT are traditional means of planning and performing PAE, with the latter providing guidance for embolization. Photon counting detector (PCD) CT is a novel technology enabling ultra-high spatial resolution (UHR) whole-body imaging, with reconstructed slices as thin as 200 um. For PAE, we obtain a single UHR PCD CT acquisition, which provides both detailed pre-procedure pelvic arterial anatomy information and a registration reference for intra-procedural embolization guidance. Case Presentation: In five patients who underwent technically successful PAE via a left transradial approach, the pre-procedure diagnostic UHR PCD prostate CTA delineated bilateral prostatic artery origins and course in all cases, as confirmed with conventional angiograms. Further, registration of the UHR PCD CT for embolization guidance was successful in all cases, augmenting vessel selection. No complication occurred. Conclusion: UHR PCD CT is a novel acquisition option that is well suited to PAE due to its ability to delineate small vessels. Further, our experience has shown that a single pre-procedure scan can also be utilized for intra-procedural embolization guidance, obviating the need for a traditional cone beam CT angiogram. Further research is needed to assess reductions in radiation dose, contrast use, and intra-procedural time with these techniques.

Background: This study aimed to analyze the geographic distribution of diabetes and sedentary behavior across Florida counites, identifying high-risk areas to inform targeted public health interventions. We seek to inform targeted public health interventions and address health disparities, particularly in rural areas. Methods: Data from the 2017-2019 Florida Behavioral Risk Factor Surveillance System (BRFSS) were analyzed, among adults aged 18 years and older. Diabetes status was determined by self-reported diagnosis, and sedentary behavior was assessed based on physical activity participation. Respondents who declined to answer or were unsure were excluded. Results: The statewide prevalence of diabetes diagnosis in Florida was 11.7% (95% CI: 10.8-12.6), with substantial geographic variation across counties. Sedentary prevalence varied significantly across the state, compared to the statewide rate of 26.5% (95% CI: 25-28). Counties with high diabetes prevalence often had elevated rates of sedentary behavior. Rural northern panhandle counties had higher concentrations of both diabetes and sedentary behavior. BRFSS design variables and weights ensured representative estimates for Florida. Conclusion: This study highlights the elevated prevalence of diabetes and sedentary lifestyles in the northern counties of Florida. The geographic patterns underscore the need for targeted, county-level interventions. Despite troubling rise in diabetes and sedentary behavior, there is a significant opportunity to mobilized community and outreach services, ensuring they are effectively deployed to these high-risk areas.

Background: Electronic Health Records (EHRs) encompass valuable data essential for disease prediction. The application of artificial intelligence (AI), particularly deep learning, significantly enhances disease prediction by analyzing extensive EHR datasets to identify hidden patterns, facilitating early detection. Recently, numerous foundation models pretrained on extensive data have demonstrated efficacy in disease prediction using EHRs. However, there remains some unanswered questions on how to best utilize such models, especially with very small fine-tuning cohorts. Methods: We utilized Med-BERT, an EHR-specific foundation model, and reformulated the disease binary prediction task into a token prediction task and a next visit mask token prediction task to align with Med-BERT’s pretraining task format in order to improve the accuracy of pancreatic cancer (PaCa) prediction in both few-shot and fully supervised settings. Results: The reformulation of the task into a token prediction task, referred to as Med-BERT-Sum, demonstrated slightly superior performance in both few-shot scenarios and larger data samples. Furthermore, reformulating the prediction task as a Next Visit Mask Token Prediction task (Med-BERT-Mask) significantly outperformed the conventional Binary Classification (BC) prediction task (Med-BERT-BC) by 3% to 7% in few-shot scenarios with data sizes ranging from 10 to 500 samples. These findings highlight that aligning the downstream task with Med-BERT’s pretraining objectives substantially enhances the model’s predictive capabilities, thereby improving its effectiveness in predicting both rare and common diseases. Conclusions: Reformatting disease prediction tasks to align with the pretraining of foundation models enhances prediction accuracy, leading to earlier detection and timely intervention. This approach improves treatment effectiveness, survival rates, and overall patient outcomes for PaCa and potentially other cancers.

Objective: To develop and validate 2 predictive models, the Diabetes Remission Index (DRI) and the Weight loss–adjusted DRI (W-DRI), for assessing type 2 diabetes (T2D) remission following metabolic and bariatric surgery (MBS). Background: MBS, including Roux-en-Y gastric bypass and sleeve gastrectomy, is highly effective in achieving T2D remission, but outcomes vary across populations. Predicting remission remains critical for individualized patient care and optimizing surgical outcomes. Existing tools focus on general outcomes, and a specific model incorporating weight loss data has been lacking. Methods: This multicenter, retrospective cohort study included patients with T2D and overweight/obesity (body mass index: ≥27 kg/m 2 ) who underwent Roux-en-Y gastric bypass or sleeve gastrectomy between 2008 and 2018. Institution 1 (I-1) data (n = 503) were used to develop and internally validate the models, whereas Institution 2 (I-2) data (n = 409) were used for external validation. The DRI model incorporated preoperative variables, and the W-DRI model, in addition, included postsurgical weight loss. Predictive accuracy was assessed using area under the Receiver Operating Characteristic curve [area under the curve (AUC)], calibration plots, and stratified analyses. Results: In I-1, 44.7% of patients achieved T2D remission, with a DRI model AUC of 0.80. In I-2, 52.6% achieved remission, with a model AUC of 0.78. Incorporating weight loss improved W-DRI predictive accuracy (AUC: 0.82 in I-1, 0.79 in I-2). Calibration plots demonstrated strong agreement between predicted and observed remission rates. An online DRI and W-DRI calculator is available through the Mayo Clinic webpage (https://newsnetwork.mayoclinic.org/dri-calculator/). Conclusions: The DRI and W-DRI models accurately predict T2D remission post-MBS, enabling personalized patient care and informed decision-making. Further validation across diverse populations is warranted.

Abstract Objective To assess the real‐world performance of a live (LCBA) versus a fixed (FCBA) cell‐based assay for the detection of serum antibodies directed against myelin oligodendrocyte glycoprotein (MOG‐IgG) and aquaporin‐4 (AQP4‐IgG). Methods This was a retrospective study of patients evaluated at a single tertiary academic referral center, with serum testing performed clinically for AQP4‐IgG and/or MOG‐IgG by FCBA and LCBA on the same day. Additionally, frozen banked sera from the same day for patients tested only by one assay were retrieved and tested by the other assay. FCBA was performed by the Johns Hopkins Immunology Laboratory using Euroimmun kits with detection by indirect immunofluorescence (FCBA‐IF), whereas LCBA was performed by the Mayo Clinic Neuroimmunology Laboratory with detection by flow cytometry (LCBA‐FACS). Results Of 594 specimens with paired MOG‐IgG testing, 500 were negative by both assays, 33 were positive by both assays, 56 were positive exclusively by LCBA‐FACS, and 5 were only positive by FCBA‐IF. Overall, MOG‐IgG LCBA‐FACS exhibited 95.1% sensitivity and 97.7% specificity, whereas MOG‐IgG FCBA‐IF had 45.7% sensitivity and 99.8% specificity. Of 577 specimens with paired AQP4‐IgG testing, 503 were negative by both assays, 51 were positive by both assays, 21 were positive exclusively by LCBA‐FACS, and 2 were only positive by FCBA‐IF. Overall, AQP4‐IgG LCBA‐FACS exhibited 97.3% sensitivity and 100% specificity, whereas AQP4‐IgG FCBA‐IF had 71.6% sensitivity and 100% specificity. Interpretation LCBA‐FACS for both MOG‐IgG and AQP4‐IgG had markedly better sensitivity than FCBA‐IF, with similar specificity. The use of FCBA‐IF may result in underrecognition of both MOG antibody‐associated disease (MOGAD) and AQP4‐IgG seropositive neuromyelitis optica spectrum disorder (NMOSD).