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Importance Treatment for cognitive dysfunction due to postacute sequelae of long COVID (ie, symptoms of fatigue, malaise, weakness, confusion that persist beyond 12 weeks after an initial COVID infection) remains a significant unmet need. Objective To test evidence-based rehabilitation strategies for improving cognitive symptoms in persons with long COVID. Design, Setting, and Participants This was a 5-arm, multicenter, randomized clinical trial of 3 remotely delivered interventions conducted between August 17, 2023, and June 10, 2024. The study took place at 22 trial sites and included the screening of individuals with cognitive long COVID. Interventions Participants were randomized to 1 of 5 arms: adaptive computerized cognitive training (BrainHQ [Posit Science]), cognitive-behavioral rehabilitation involving both group and individual counseling sessions (PASC-Cognitive Recovery [PASC-CoRE]) paired with BrainHQ, and transcranial direct current stimulation (tDCS) paired with BrainHQ. Two comparator arms were included as follows: unstructured computer puzzles and games (active comparator) and sham tDCS paired with BrainHQ. The interventions occurred 5 times per week over 10 weeks. Main Outcomes and Measures Cognitive and behavioral in-person assessments were performed at baseline, midintervention, at the end of intervention, and 3 months after the end of the intervention. The primary outcome measure was the modified Everyday Cognition Scale 2 (ECog2) completed at the end of the intervention compared to the baseline visit based on participant self-report looking back over the prior 7 days. Results A total of 378 individuals were screened, from which there were 328 participants (median [IQR] age, 48.0 [37.0-58.0] years; 241 female [73.5%]; race: 15 Asian [4.6%], 47 Black [14.3%], and 235 White [71.6%]; ethnicity: 52 Hispanic [15.9%]). None of the 3 active interventions demonstrated benefits on the modified ECog2 in the intention-to-treat population by the end of the intervention period. The adjusted differences in mean change were 0.0 (95% CI, −0.2 to 0.2) for BrainHQ vs active comparator, 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs active comparator, 0.0 (95% CI, −0.2 to 0.2) for tDCS-active + BrainHQ vs tDCS-sham + BrainHQ, and 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs BrainHQ alone. Secondary participant-reported outcomes and neuropsychological tests showed no differential benefits for any treatment arm. All 5 arms demonstrated some improvements over time on the modified ECog2 and on secondary outcomes. There were no serious adverse events attributable to the interventions. Conclusions and Relevance This phase 2 randomized clinical trial failed to demonstrate differential benefits for online cognitive training, a structured cognitive rehabilitation program, and tDCS for cognitive long COVID. Trial Registration ClinicalTrials.gov Identifier: NCT05965739 .

The NCCN Guidelines for Prostate Cancer provide a framework on which to base decisions for patients with prostate cancer across the disease spectrum. The Guidelines sections included in this article focus on metastatic castration-sensitive prostate cancer (mCSPC), nonmetastatic castration-resistant prostate cancer (CRPC), and metastatic CRPC (mCRPC). For patients with mCSPC, disease characteristics, such as whether metastases arose synchronously or metachronously and the degree of metastatic burden, impact therapy decisions, including how much treatment intensification is appropriate and when prostate-directed and/or metastasis-directed therapy should be considered. In the mCRPC setting, androgen deprivation therapy is continued with the sequential or concurrent addition of certain androgen receptor pathway inhibitors, chemotherapies, immunotherapies, radiopharmaceuticals, and/or targeted therapies. The NCCN Prostate Cancer Panel emphasizes a shared decision-making approach in all disease settings based on patient preferences, prior treatment exposures, biomarkers, the extent and location of metastases, symptoms, and potential side effects.

Abstract Repetitive head impacts are common in contact and collision sports and are linked to structural brain changes and an elevated risk of neurodegenerative diseases such as Chronic Traumatic Encephalopathy. Identifying early in vivo structural markers remains challenging. Although diagnosis currently requires post-mortem confirmation, clinical symptoms, including cognitive impairment and behavioural changes, are reflected in the diagnosis of Traumatic Encephalopathy Syndrome. These symptoms align with dysfunction in key brain regions—amygdala, hippocampus and thalamus—which support memory, emotion and behaviour and commonly show tau pathology in Chronic Traumatic Encephalopathy. This study uses shape analysis to examine structural differences in these regions between former American football players and unexposed asymptomatic controls and evaluates the influence of age, head impact exposure and clinical diagnosis on brain structure. We analyzed brain morphology in former American football players (n = 163) and unexposed, asymptomatic controls (n = 53). Structural segmentation was performed with FreeSurfer 7.1, and the shape analysis pipeline was used to generate subregional reconstructions. Vertex-level morphometry, based on the logarithm of the Jacobian determinant and radial distance, quantified local surface area dilation and thickness. Group differences were examined with covariate-adjusted linear regression models contrasting football players and controls, as well as participants with and without a Traumatic Encephalopathy Syndrome diagnosis. Partial correlations examined the influence of age, age of first football exposure and cumulative head impact index metrics, including frequency, linear acceleration and rotational force. Models were adjusted accordingly for age, body mass index, education, race, imaging site, apolipoprotein ϵ4 status and total intracranial volume. Former football players exhibited bilateral surface area contractions in the hippocampus and amygdala, along with reduced amygdala thickness, compared to controls. Older age was associated with widespread surface contractions and thinning across all regions, except for preserved thickness in the left hippocampus. An earlier age of first exposure to football correlated with surface contractions in the thalamus and left hippocampus. Greater cumulative linear acceleration was linked to bilateral hippocampal surface contractions and reduced thickness in the left thalamus, while greater rotational force exposure was associated with hippocampal thinning. No significant structural differences were found between players with and without a diagnosis of Traumatic Encephalopathy Syndrome. These findings extend volume-based research by revealing localized alterations in surface area dilation and thickness and emphasize the roles of age and repetitive head impact exposure in long-term brain changes.

Background The Woven EndoBridge (WEB) device represents an innovative solution for cerebral aneurysm occlusion, particularly for challenging wide-neck bifurcation aneurysms. However, factors affecting sustained occlusion remain poorly understood. We utilized machine learning to attempt to identify predictors of favorable long-term outcomes following WEB treatment. Methods In this multicenter retrospective study, we collected patient demographics, aneurysm characteristics, procedural details, and clinical outcomes. The primary endpoint was improvement in occlusion status, defined as maintained Raymond-Roy Occlusion Classification (RROC) grade 1, or improvement from grade 2 to 1, or from grade 3 to either 2 or 1 on final angiographic follow up. The dataset was split into training (75%) and validation (25%) sets. The CatBoost algorithm was selected based on performance metrics, with Shapley Additive exPlanations (SHAP) values calculated to determine feature importance. Furthermore, a multivariable binomial logistic regression model was performed to validate machine learning findings. Results Among 720 aneurysms from 36 hospitals, 84% showed improvement in occlusion at follow up. Both machine learning and multivariable logistic regression identified aneurysm height as the most consistent correlate of nonimprovement (odds ratio (OR) 0.90 per mm, p = 0.022). In the CatBoost model, the highest-ranking features by SHAP included aneurysm height, patient age, treatment acuity, ACom location, WEB-SLS device, bifurcation anatomy, aneurysm multiplicity, baseline modified Rankin Scale, access route, and partial thrombosis. Conclusions Machine-learning and regression analyses identified consistent predictors of occlusion improvement after WEB treatment, with aneurysm height most strongly linked to nonimprovement. These insights may guide patient selection and follow up. Findings require cautious interpretation and external validation in larger cohorts.

Abstract Disclosure: D.S. Ali: None. Z. Chung: None. L. Kamel: None. S. Björnsdottir: Shire. B.L. Clarke: Shire, Takeda, Ascendis, Calcilytix. S. Hahner: None. L.C. Hofbauer: Amgen Inc, Ascendis, UCB, Ascendis, Amolyte. P. Houillier: None. S.W. Ing: Amgen Inc, Radius Health, Inc, Takeda, AscendAlexion, Amolyt, Ascendis, Calcilytix, Kyowa Kirin. M.A. Levine: Takeda, Amolyt, Calcilytix. M. Mannstadt: Takeda, Amolyt, Calcilytix. L. Rejnmark: Takeda, Amolyt, Ascendis, Calcilytix. D.M. Shoback: Amolyt, Ascendis, member of the advisory board (PARADIGHM). M. Brandi: Takeda, Eli Lilly & Company, Calcilytix, Kyowa Kirin, UCB, Abiogen, Alexion, Amolyt, Amorphical, Bruno Farmaceutici, CoGeDi, Echolight. A.A. Khan: Takeda, Amgen Inc, Alexion, Ascendis, Amolyt, Calcilytix. Background: Hypoparathyroidism (HypoPT) is a rare endocrine disorder that requires close evaluation and follow up during pregnancy to minimize maternal and fetal complications. The primary objectives of this study are to evaluate the use of rhPTH (1-84) during pregnancy by analyzing data from the PARADIGHM disease registry, and to compare maternal and neonatal outcomes among patients who continued PTH therapy during pregnancy versus those on conventional therapy (CT). Methods: We performed a retrospective analysis of data in the PARADIGHM registry. Maternal and neonatal outcomes in women treated with rhPTH (1-84) were compared to women who received CT. Results: We analyzed 39 pregnancies of 32 women. Of those, 4 women (6 pregnancies) used rhPTH (1-84) either before or during pregnancy and 28 women (33 pregnancies) continued CT during pregnancy. The mean (SD) maternal age at enrollment was 31.7 (5.6) years. Postsurgical HypoPT was the most common etiology (68.8%). The mean gestational age at delivery was 36 (2.4) weeks (PTH-treated) vs 38.3 (3.3) weeks (CT) (p=0.162). Preterm delivery rates were higher in the PTH-treated group (50% vs. 27%, p=0.591), but this was not statistically significant. Two women had pre-eclampsia, one in each group (PTH-treated and CT). In the PTH-treated group, one pregnancy resulted in a stillbirth, and one infant was born with congenital anomalies (16.7% each). Conclusions: The safety of rhPTH (1-84) use in pregnancy cannot be determined at this time. The PTH-treated group exhibited trends towards higher rates of preterm delivery, but the rates of stillbirth, and congenital anomalies were low and comparable in both groups of women. Larger studies are necessary to determine the optimal approach to manage women with HypoPT during pregnancy. Presentation: Sunday, July 13, 2025

Stereotactic radiosurgery was associated with a higher obliteration rate compared with embolization in patients with eloquent brain arteriovenous malformations, whereas there was no evidence of a difference in functional outcomes or complications after adjustment.

Abstract Aims Endogenous endophthalmitis (EE) is a rarely reported complication of infective endocarditis (IE). In an international series, we sought to determine the clinical and microbiological profile, treatment, and outcome of patients presenting with IE-related EE. Methods and results Cases recorded from 2014 to 2023 in nine centres in Europe and the United States were collected. Results were compared to a matched control group. Conclusion Sixty-six patients with EE were reported, mean age of 65.2 ± 14.9 years, 71% (n = 47) male. Blood cultures were positive in 97% (64 cases) of patients, with a predominance of streptococci (46%, n = 30). As compared with the control group (n = 264), the EE group presented with more frequent diabetes (35% vs. 21%, P = 0.02), history of cirrhosis (9% vs. 3%, P = 0.04), glomerulonephritis (15% vs. 0.4%, P < 0.001), embolism before admission (92% vs. 55%, P < 0.001), and Janeway lesions (9% vs. 1%, P = 0.002). Streptococcal infection (46% vs. 26%, P = 0.001) was more frequent and Enterococcal infection (0% vs. 18%, P < 0.001) less frequent in the EE group. The main ocular symptoms were a decrease in visual acuity (96%), red eye (55%), and ocular pain (55%). Treatment of EE consisted of intravitreal antibiotic injection in 55 (83%) patients and vitrectomy in 17 (26%). Improvement of visual acuity was observed in 36 (55%) patients. Conclusion EE is a serious complication of IE with severe residual vision impairment. Patients with IE should be evaluated for ocular complications, since early detection of EE is crucial to prevent delays in management and to preserve visual function.

Background: Mild cognitive impairment (MCI) is a precursor to dementia, with a prevalence of over 15% among community dwellers, with significant economic and social implications. Despite preserved autonomy in daily living, individuals with MCI face challenges in handling everyday technology and memory-related tasks, necessitating digital interventions, such as digital planning-based technologies to support cognitive functioning. Objective: The aim of this study is to identify and summarize available research literature on available digital planning-based technologies to support memory-related functioning in older adults with MCI. Specifically, this study seeks to (1) document the types and functions of these technologies, (2) report their effectiveness, and (3) identify gaps in the current evidence. Methods: A comprehensive literature search of four databases (Medline, Embase, APA PsycINFO, and CINAHL) was conducted in accordance with Arksey and O’Malley’s scoping review methodological framework from inception to February 6, 2024, without restrictions. Inclusion criteria focused on peer-reviewed studies involving adults aged 50 or older with diagnosed cognitive impairment, specifically using digital planning-based technologies for memory support. Results: From 1854 sources, 8 studies were included. Five categories of digital planning-based technologies were identified: (1) reminders and alarms, (2) electronic calendars, (3) digital memory notebooks, (4) digital visual mapping, and (5) smart-home integration. Several studies reported improved task performance, memory recall, and executive function, with digital memory notebooks and visual mapping software showing greatest impact on functional independence. While interventions were generally well-received, usability challenges and low adherence were common, often linked to technological familiarity and motivation. Conclusions: Digital planning-based technologies show promise in supporting memory-related functioning in older adults with MCI. While studies report positive outcomes, more research is needed to refine these tools, evaluate long-term effects, and ensure integration into daily life. Expanding the evidence base will be key to improving accessibility and effectiveness for this population.

Abstract Medical imaging is undergoing a transformation driven by the advent of new, highly effective, machine learning techniques paired with increases in computational capabilities (Cheng et al. 2021; Gilson et al. 2023; Almeida et al. 2024; Krishna et al. 2024). These advanced algorithms have the potential to improve disease detection, diagnosis, prognosis, and treatment outcomes. However, the complexity of machine learning models, the large amounts of curated and annotated data required by some methods, and the potential for bias and error make it challenging for individuals to safely and effectively leverage these methods (Lin et al. 2024; Guo et al. 2024; Xu et al. 2024; Linguraru et al. 2024; Wood et al. 2019). To address these challenges, the American Association of Physicists in Medicine (AAPM), American College of Radiology (ACR), Radiological Society of North America (RSNA), and Society for Imaging Informatics in Medicine (SIIM) have worked together to develop a syllabus detailing a recommended set of competencies for medical imaging professionals interacting with these systems. This guide is aimed at four different personas: users of AI systems, purchasers of AI systems, individuals who provide clinical expertise during the development of AI systems (“clinical collaborators”), and developers of AI systems.1 This is a syllabus, not a curriculum, and is intentional in this scope. Recognizing that individuals may benefit from different presentations of the same material, this work enumerates a series of relevant competencies but does not prescribe, nor offer, a method of instruction (Schuur, Rezazade Mehrizi, and Ranschaert 2021; Garin et al. 2023). By addressing the task‐specific demands of each role, this guide will enable medical imaging professionals to utilize machine learning systems more safely and effectively, ultimately improving patient care and outcomes.