Citations

Abstract Background Coronary computed tomography angiography (CCTA) and myocardial perfusion imaging (MPI) are guideline-recommended to assist in clinical decision-making in patients with prior coronary artery bypass grafting (CABG). However, the value of combining CCTA and MPI for guiding revascularization decision-making in post-CABG patients with recurrent ischemic symptoms remains unexplored. In this study, we compared Heart Team strategies for revascularization based on CCTA and MPI as standalone and hybrid CCTA/MPI imaging, to strategies guided by invasive coronary angiography (ICA). Methods We included symptomatic patients with prior CABG who underwent CCTA and MPI (single-photon emission computed tomography, positron emission tomography or stress perfusion cardiac magnetic resonance imaging) preceding ICA. Simulated Heart Teams, blinded to other Heart teams and outcomes, performed revascularization decision-making based on conventional CCTA, MPI and a hybrid CCTA/MPI strategy (non-invasive Heart Team) or based on ICA (invasive Heart Team). The primary outcome was the Cohen’s kappa agreement (κ) between non-invasive and invasive Heart Teams. Results A total of 115 patients (mean age 73±7 years; 99 [86%] male) were included. Revascularization was recommended in 96 patients (83.5%) by CCTA, 92 patients (80.0%) by MPI, 80 patients (69.6%) by hybrid CCTA/MPI and 76 patients (66.1%) by ICA. The agreements were significant but low for CCTA (κ: 0.25 [95% confidence interval (CI): 0.07-0.42], P=0.003) and MPI (κ: 0.27 [95% CI: 0.09-0.48], P=0.002) compared to ICA, with only a modest increase when using the hybrid non-invasive imaging strategy (κ: 0.32 [95% CI: 0.14-0.51], P<0.001). Conclusions In patients with recurrent ischemic symptoms after CABG, Heart Team assessment of conventional CCTA and MPI yielded similarly poor agreements with revascularization strategies based on ICA, with only a modest improvement observed when using a hybrid CCTA/MPI approach. Overall, non-invasive imaging alone appears insufficient to accurately guide treatment strategies in patients with prior CABG, and their use as gatekeeping for ICA in these patients should be questioned.

Background: Plasma cell dyscrasia (PCD) is a rare but important cause of end stage kidney disease (ESKD). Kidney transplant is the treatment of choice in patients with ESKD. However, the complexity of PCD care and risk of disease recurrence poses challenges to kidney transplant candidacy and outcomes. We examined the current clinical practice patterns of clinicians who care for patients with PCD and identified barriers to kidney transplantation for patients with PCD. Methods: A web-based survey was developed and distributed from January to July 2024 to kidney transplant clinicians (American Society of Transplant (AST) members), hematologists (PCD experts), and onco-nephrologists. Results: Seventy clinicians (50 transplant nephrologists, 18 hematologists, and two surgeons) from 42 transplant centers in the US participated in the survey. Clinical practice patterns pre and post kidney transplant for patients with PCD are highly variable among institutions, and only 36% reported having a protocol for pre- and post-transplant management for patients with PCD. Particularly, the requirement for pre-transplant hematologic remission criteria, induction and maintenance immunosuppression regimens and protocols for prophylaxis and screening for opportunistic infection are areas of future study. Clinicians listed lack of data and practice guidance as well as communication challenges among multiple specialties especially hematology and kidney transplant clinicians as notable barriers. Conclusions: Our study identified the highly variable current practice patterns when evaluating and managing patients with PCD for kidney transplant. Our findings emphasize the need for collecting and sharing clinical data to support standardized practices and serve as a basis for the upcoming multi-societal management recommendation for kidney transplant for patients with PCD.

Background and Aims: Cholangiocarcinoma (CCA) is a rare but aggressive malignancy with poorly understood genetic susceptibility. To date, genome-wide association studies (GWAS) investigating germline variants associated with CCA risk remain limited. We aimed to identify genetic risk loci for CCA and its clinical subtypes through comprehensive GWAS and post-GWAS analyses. Approach and Results: We conducted a GWAS of 2366 CCA cases and 11,750 controls of European ancestry. Genome-wide significant loci ( p <5×10 −8 ) were identified and further examined through fine-mapping, functional annotation, and HLA imputation. Subgroup analyses were conducted by CCA subtypes and primary sclerosing cholangitis (PSC) status. Cross-trait linkage disequilibrium score regression and Mendelian randomization were employed to investigate the shared genetic architecture and potential causal relationships with a diverse range of traits. We identified 1 new genome-wide significant variant, rs535777 (OR=1.44), near HLA-DRB1/DQA1 associated with CCA, and 2 variants associated with extrahepatic CCA: rs116224263 (OR=0.17) in LINC02506 at 4p15.1 and rs6914950 (OR=1.63) near HLA-DRB1/DQB1 . Stratified analyses revealed rs2395184 (OR=3.51) near HLA-DRA/DRB5 associated with PSC-related CCA, and rs142674434 (OR=2.98) in THSD7A at 7p21.3 associated with non-PSC-related CCA. HLA imputation uncovered new amino acid residues associated with disease risk. Cross-trait analyses identified shared genetic signals between CCA and anthropometric, lipidemic, lifestyle, and medical traits. Mendelian randomization supported putative causal associations for 12 traits with CCA or its subtypes. Conclusions: Our large-scale GWAS highlights new genetic variants and HLA-linked mechanisms underlying CCA susceptibility. Integrating multi-step post-GWAS approaches enhances understanding of CCA pathogenesis and may facilitate the development of risk biomarkers for early detection and precision prevention strategies.

INTRODUCTION Recent work has identified unique cognitive profiles for early‐onset Alzheimer's disease (EOAD) relative to late‐onset Alzheimer's disease (LOAD), however, examination has been limited in determining whether the association between age and cognitive severity at presentation also differs across conditions. METHODS A series of linear spline regression models was conducted across baseline cognitive data from 325 EOAD and 314 LOAD participants, after accounting for education, sex, and apolipoprotein ε4 status. RESULTS Significant differences existed in the relationship between baseline age and cognitive performance between EOAD and LOAD samples for Processing Speed/Attention, Executive Functioning, and Episodic Immediate Memory. Younger participants from both EOAD and LOAD groups performed disproportionately worse on non‐amnestic cognitive domains, with this occurring to a greater extent in EOAD than LOAD. DISCUSSION In the age of disease‐modifying treatments, results highlight the importance of assessing for cognitive declines in individuals starting much earlier than age 65. Highlights Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) participants each displayed cognitive impairments relative to same‐aged peers across most domains. Both groups displayed positive relationships between impairment among non‐amnestic cognitive domains and baseline age. This relationship displayed a significantly greater effect in EOAD than LOAD, with domains of Processing Speed/Attention and Executive Functioning skills being the most pronounced. Of those participants developing AD, age displayed a disproportionate impact on their symptom onset.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Background: Cardiac CT acquired during the acute stroke imaging protocol is an emerging diagnostic modality to detect cardiac thrombi. We aimed to determine its diagnostic yield in a large, international, multicenter study. Methods: We performed an individual patient data meta-analysis by pooling prospective and retrospective observational data of patients with acute ischemic stroke (AIS) who underwent cardiac CT (ECG-gated or non-ECG-gated) as part of the acute imaging protocol between May 2018 and June 2024. We excluded patients with a TIA or stroke mimic. The primary outcome was the proportion of patients with a cardiac thrombus detected on cardiac CT. Secondary outcomes were additional scan time and radiation dose, comparison of yield with echocardiography, and 90-day mortality and recurrent ischemic stroke rates. Results: We included 3940 patients from 4 hospitals (median age 74 [IQR 63-82], 58.0% male, median NIHSS 6 [IQR 3-12], median time onset to hospital arrival 100 minutes [IQR 62-185]). Atrial fibrillation at baseline was present in 23.1% patients, and 29.6% had a large vessel occlusion. Cardiac CT was non-diagnostic in 17 (0.4%) patients. In total, cardiac CT detected 254 cardiac thrombi in 243/3923 (6.2%) patients. Thrombi were located in the left atrial appendage (n=193), left atrium (n=19), and left ventricle (n=42). Of 95/243 (39.1%) patients with a cardiac thrombus that underwent echocardiography (median interval cardiac CT-echocardiography: 2 days), transthoracic echocardiography detected a thrombus in 18/92 (19.6%) patients and transesophageal echocardiography in 2/5 (40.0%) patients. The diagnostic yield in patients that underwent both modalities was higher for cardiac CT (OR 7.5 [CI 4.0-15.3], p<0.001). Median additional scan time was 6 minutes (IQR 5-7) for ECG-gated and 17 seconds (IQR 15-63) for non-ECG-gated cardiac CT. Median additional radiation dose was 5.4mSv (IQR 3.0-7.6). Patients with a cardiac thrombus on cardiac CT had higher 90-day mortality than those without a thrombus (33.3% vs 14.6%, p<0.001). We found no difference in 90-day recurrent stroke rate (5.4% vs 4.4%, p=0.50). Conclusion: Routine cardiac CT performed during the acute stroke imaging protocol detects a cardiac thrombus in 1 out of 16 patients with AIS, with a 7-times higher yield than routine echocardiography. Mortality rate was doubled in patients with a cardiac thrombus, but 90-day stroke recurrence risk did not differ.

Introduction: Spinal cord infarction (SCI) is a rare but serious neurological condition that accounts for 1-2% of all ischemic strokes and can lead to significant disability. Despite its clinical importance, existing studies are limited by small sample sizes that lack national generalizability, and little is known about post-discharge events such as hospital readmissions. We aimed to evaluate factors associated with all-cause hospital readmissions among hospitalizations with primary diagnosis of SCI, utilizing the Nationwide Readmissions Database (NRD). Methods: NRD data were abstracted from 2016 to 2022 including all hospitalizations of adult patients (≥18 years) with a primary diagnosis of SCI. Multiple-predictor logistic regression models were estimated to assess the association of demographic and clinical variables with all-cause 90-day readmissions. We included specific comorbidities often used in comorbidity scoring systems and added conditions or complications that are known to be associated with SCI. Statistically significant covariates from the unadjusted model were retained in the multiple-predictor model. Odds ratios (OR) with associated 95% Confidence intervals (CI) and p-values were reported. Results: From 2016 to 2022, there were an estimated 3321 hospitalizations with a primary diagnosis of SCI, out of which 27% (95% CI: 24-30%) were readmitted within 90 days. Demographic factors that were associated with lower odds of readmission included private insurance (vs. Medicare) and high-income quartile (Fig. 1). [AH1] [AAs2] Clinical factors that were associated with increased odds of readmission included autonomic dysfunction (OR = 5.44, 95% CI: 1.86 to 15.94), renal disease (OR = 3.57, 95% CI: 1.83 to 6.96), liver disease (OR = 2.40, 95% CI: 1.34 to 4.32), full clinical associations shown in Figure 2. Conclusion: We identified several clinical and demographic factors that were significantly associated with increased all-cause readmissions after SCI hospitalizations. Autonomic dysfunction and renal disease were among the top predictors of readmissions. We uncovered socioeconomic disparities in readmissions rates following SCI. This data may assist vascular neurologists, physicians and healthcare administrators in reducing readmissions after SCI and addressing these disparities. Additionally, our results can guide future studies focusing on the management of this rare entity.

Background: The rate of intracardiac thrombus detection in the hyperacute phase of stroke varies from 5% to 12% between studies. Our aim was to compare the thrombus detection rate between ECG-gated and non-ECG-gated cardiac CT protocols in acute stroke patients, using data from a large, international, multicentre registry. Methods: We conducted an individual patient data meta-analysis by pooling prospective and retrospective observational data from stroke patients assessed at four comprehensive stroke centres who underwent either ECG-gated or non-ECG-gated cardiac CT (extended CT angiography or two-phase non-ECG-gated cardiac CT) as part of the acute stroke imaging protocol between May 2018 and June 2024. The primary outcome was the proportion of patients with a cardiac thrombus in gated vs non gated techniques. Results: Of 3,940 patients, 1,474 (37.4%) underwent ECG-gated and 2,466 (62.6%) non-ECG-gated cardiac CT. Patients in the ECG-gated group were younger (median age 72 [IQR 62–81] vs. 74 [IQR 64–82] years, p = 0.000) and had a lower NIHSS at baseline (median 5 [IQR 2–12] vs. 6 [IQR 3–13], p < 0.00). There was a higher rate of thrombus detection with ECG-gated CT compared to non-gated CT (7.5% vs. 5.5%, p = 0.011. The association remained significant after adjusting for age, sex, baseline NIHSS score, and baseline atrial fibrillation (adjusted OR 1.87, 95% CI 1.42–2.47, p = 0.000). ECG-gated CT was associated with lower radiation dose (3.6 vs. 6.3 mSv, p = 0.000) but longer acquisition time (5.8 vs. 0.28 min, p = 0.000). Conclusion: ECG-gated cardiac CT has a higher detection rate for intracardiac thrombus detection compared to non-ECG-gated CT in patients with acute ischemic stroke.