Citations

Background: Cognitive change is an important factor in understanding dementia. Estimating effects of exposures on cognitive change requires choosing an analytical timescale, typically time on study or current age. There is limited consensus regarding timescale choice in epidemiologic cognitive aging research. Methods: Using a coordinated analytic approach in 10 cohorts of older adults, we evaluated whether estimated effects of two exposures on memory change differed depending on timescale (time on study or current age). We modeled effects of apolipoprotein-E (APOE) ε4 genotype (a time-invariant exposure) and diabetes (a potentially time-varying/acquired exposure evaluated at baseline) using mixed-effects models with linear and nonlinear time specifications for both timescales. Results: Among APOE ε4 carriers, model-estimated memory scores at baseline (time on study timescale) or at each cohort’s median baseline age (current age timescale) were lower, and the average rate of decline was faster than among APOE ε4 noncarriers. Model-estimated memory scores at baseline or at median baseline age were generally similar across baseline diabetes status, with variability across cohorts in the diabetes-memory change association. In some cohorts, trends in diabetes-memory change associations differed in direction across timescales. Conclusions: Timescale was largely inconsequential for estimated effects of APOE genotype, but yielded differences in estimated diabetes effects, raising questions about the appropriate scale. The current age scale may be problematic because diabetes was measured heterogeneously in age across individuals, a common issue in aging cohorts. Our work demonstrates approaches to evaluate alternative timescales, including in multicohort analyses, and highlights potential implications for estimated exposure effects on cognitive change.

AbstractPeripheral spondyloarthritis (pSpA) encompasses multiple entities affecting the musculoskeletal system with classic findings of synovitis, enthesitis, and tenosynovitis. It remains poorly defined when compared with the axial spondyloarthritides due to nonspecific symptoms, ill-defined imaging findings, and lack of specific testable biomarkers. Previous research has tried to distinguish between the two disease entities using clinical presentations, scoring systems, and radiographic findings; however, overlap remains. We summarize the current classification of pSpA, imaging findings, and the distinction between these entities and axial spondyloarthritis.

Abstract Background Impact of BRAF V600E mutations (BRAFV600E), a poor prognostic factor in metastatic colorectal cancer, is lacking in non-CRC gastrointestinal (GI) cancers including pancreatic (PDAC), gastric/gastroesophageal (GEA), hepatocellular carcinoma (HCC), and cholangiocarcinoma (CCA). Due to tumor-agnostic approvals for patients with BRAFV600E, understanding the frequency and impact of BRAF alterations across non-CRC GI cancers is essential for clinical decision-making. Methods Patients with PDAC, GEA, HCC, or CCA who had cell-free DNA detected on Guardant360 (Guardant Health) from 2020 to 2023 were queried. Prevalence of characterized BRAF genomic alterations (GA) was calculated; GAs were grouped by class (Class I/II/III). The Chi-squared test assessed differences between cancer types. A subset of patients had outcomes analysis using GuardantINFORM, a real-world clinicogenomic database, to derive real-world overall survival (rwOS). Results Of 32 480 included patients, BRAF GAs were identified in 4.4%; 19% were BRAFV600E (0.81% prevalence overall). CCA had the highest rate of BRAF GAs and BRAFV600E (P < .01); HCC and GEA had the highest rates of BRAF class II/III alterations. There were no significant differences in rwOS by alteration class or cancer type; numeric differences were observed by alteration class. Few patients were treated with BRAF inhibitors (2.2%). Prevalence of co-occurring alterations was unique by cancer type. Conclusions Frequency of BRAF GAs, including BRAFV600E, in non-CRC GI cancers detected by liquid biopsy is similar to tissue-based rates and can be reliably used to assess BRAF status. BRAF GAs have mixed prognostic implications on survival for patients with non-CRC GI malignancies that warrant further exploration.

Abstract Background and Aims Positron emission tomography (PET)/computed tomography (CT) myocardial perfusion imaging (MPI) is a vital diagnostic tool, especially in patients with cardiometabolic syndrome. Low-dose CT scans are routinely performed with PET for attenuation correction and potentially contain valuable data about body tissue composition. Deep learning and image processing were combined to automatically quantify skeletal muscle (SM), bone and adipose tissue from these scans and then evaluate their associations with death or myocardial infarction (MI). Methods In PET MPI from three sites, deep learning quantified SM, bone, epicardial adipose tissue (EAT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and intermuscular adipose tissue (IMAT). Sex-specific thresholds for abnormal values were established. Associations with death or MI were evaluated using unadjusted and multivariable models adjusted for clinical and imaging factors. Results This study included 10 085 patients, with median age 68 (interquartile range 59–76) and 5767 (57%) male. Body tissue segmentations were completed in 102 ± 4 s. Higher VAT density was associated with an increased risk of death or MI in both unadjusted [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.37–1.43] and adjusted (HR 1.24, 95% CI 1.19–1.28) analyses, with similar findings for IMAT, SAT, and EAT. Patients with elevated VAT density and reduced myocardial flow reserve had a significantly increased risk of death or MI (adjusted HR 2.49, 95% CI 2.23–2.77). Conclusions Volumetric body tissue composition can be obtained rapidly and automatically from standard cardiac PET/CT. This new information provides a detailed, quantitative assessment of sarcopenia and cardiometabolic health for physicians.

Background Overhead athletes are susceptible to shoulder injuries, among which rotator cuff injuries are common and often directly associated with muscle weakness. Therefore, valid and reliable measures of rotator cuff strength at sport specific positions may be a vital part of sports physical therapy practice. Purpose: The current study aimed to determine the inter- and intra-tester reliability of measuring shoulder internal rotation (IR) and external rotation (ER) strength at a novel testing position, 130° of abduction and compared to the 90°/90° position. A secondary aim was to assess concurrent validity between measurements taken with the Humac® Norm™ Isokinetic Dynamometer (IKD) and Microfet® 2 hand-held dynamometer (HHD). Study Design Inter-Rater and Intra-Rater Reliability and Criterion Validity Methods Twenty-five (n=25) healthy participants were recruited for this study. Exclusion criteria included prior shoulder surgery, shoulder injury within the last three months, and contraindications to exercise according to ACSM guidelines. Participants performed maximal isometric shoulder external and internal rotation strength testing at both 90° and 130° of shoulder abduction. On the first day, participants were tested on the IKD at both positions, followed by each tester using the HHD. Participants returned 7-14 days later for repeat testing using the HHD only. ICC values were calculated for each rater, instrument, and testing position. Bland-Altman plots were created to establish limits of agreement. Minimal detectable change values were calculated. Results Inter- and intra-rater reliability for testing isometric strength using a hand-held dynamometer was good to excellent for both shoulder positions with ICC values consistently above 0.8. Concurrent validity between the HHD and IKD was poor to moderate with ICC values ranging from 0.1-0.4. However, Bland-Altman plots demonstrated that the difference in strength measures was within the limits of agreement. Conclusion Shoulder IR and ER strength testing at 130° of abduction shows strong inter-rater and intra-rater reliability for measurement in sport specific positions. Level of Evidence Level 3

Abstract Introduction: Periacetabular osteotomy (PAO) is a complex procedure historically requiring inpatient stay. There is increased emphasis for these to be performed on an outpatient basis by insurance companies. The purpose of this study was to investigate the proportion of various surgical listing classifications (outpatient, outpatient-overnight, inpatient), the incidence of subsequent denial/request for additional documentation for approval of inpatient stay, and to characterize the average length of stay (LOS) following PAO. Methods: A retrospective chart review was performed to identify all PAOs, performed by four participating surgeons, at a single academic institution over a two-year period. The initial listing status as an outpatient-overnight or inpatient procedure was identified. Whether a preoperative peer review was required for approval of inpatient listings as well as if additional documentation was necessary to convert outpatient-overnight listings to inpatient stays were also recorded. Results: A total of 140 PAOs amongst 117 patients were performed with 25 (17.9%) initially listed as an inpatient stay and 115 (82.1%) listed as outpatient-overnight. Of the 25 PAOs listed as inpatient, 2 (8.0%) required a preoperative peer review process to justify or clarify listing status. The average LOS was 1.9 ± 1.4 days with 55.7% (78/140) of PAOs staying two or more nights in the hospital. Only 6 PAOs (4.3%) went home the same day as surgery. Of the 115 PAOs listed as an outpatient-overnight, 53 (46.1%) converted to an inpatient stay. Conclusion: Over half of PAOs performed required inpatient stay beyond outpatient-overnight status. Preoperative peer-to-peer review for inpatient stay approval was modestly frequent (8% of inpatient listings), and all conversions to inpatient required additional service documentation to support status conversion. Understanding trends in postoperative hospitalizations and LOS might allow for better informed partnerships between surgeons and insurance companies creating more efficient pre-authorizations, billing practices, and expected patterns of patient care and discharge.

Abstract Background Most oncology therapeutics have limited distribution into the brain, and developing strategies to overcome this limitation would be clinically impactful. While therapeutic radiation is often cited as a strategy to accomplish this, there are no published studies demonstrating the effect of radiation on drug distribution into the brain or brain tumors. Methods Mice were treated with brain radiation (6 Gy × 5, 4 Gy × 10; 40 Gy × 1) and dosed with drugs (levetiracetam, cefazolin, nedisertib, brigimadlin, apitolisib, or GNE-317) at times ranging from just prior to months after radiation. Plasma and tissue drug concentrations were measured by LC-MS/MS. Results Radiation did not significantly enhance drug delivery into brain tissue for levetiracetam, cefazolin, GNE-317, apitolisib, or nedisertib at any time post-radiation. Even a single, supra-therapeutic dose of radiation (40 Gy) did not significantly affect brain distribution of GNE-317 or apitolisib (P ≥ .07) from 16 to 160 hours post-radiation. For brigimadlin, radiation (6 Gy × 5) was associated with a modest but significant increase in drug accumulation only at 72 hours post-radiation (brain-to-plasma ratio 0.014 ± 0.006 vs. 0.025 ± 0.010, respectively; P = .04), but not at any other timepoint (24 hours, 15, 28, 94, 133, 183 days; P > .05). Similarly, radiation (6 Gy × 5) of orthotopic tumors did not increase levels of brigimadlin in GBM10 or GBM108 or nedisertib in GBM108 (P > .05). Conclusions Radiation had no meaningful impact on drug delivery into brain or brain tumors for the drugs tested.

Abstract Aims Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field. Methods and results An AI checklist specific to EP was developed with expert input from the writing group and voted on using a modified Delphi process, leading to the development of a 29-item checklist. The checklist was subsequently applied to assess reporting practices to identify areas where improvements could be made and provide an overview of the state of the art in AI-related EP research in three domains from May 2021 until May 2024: atrial fibrillation (AF) management, sudden cardiac death (SCD), and EP lab applications. The EHRA AI checklist was applied to 31 studies in AF management, 18 studies in SCD, and 6 studies in EP lab applications. Results differed between the different domains, but in no domain reporting of a specific item exceeded 55% of included papers. Key areas such as trial registration, participant details, data handling, and training performance were underreported (<20%). The checklist application highlighted areas where reporting practices could be improved to promote clearer, more comprehensive AI research in EP. Conclusion The EHRA AI checklist provides a structured framework for reporting AI research in EP. Its use can improve understanding but also enhance the reproducibility and transparency of AI studies, fostering more robust and reliable integration of AI into clinical EP practice.