Citations

ObjectiveThe objective was to determine the mortality rate as well as the causes and predictors of death in antiphospholipid antibody (aPL)–positive patients with and without antiphospholipid syndrome (APS) classification.MethodsThe inclusion criterion for the multicenter international Antiphospholipid Syndrome Alliance for Clinical Trials and International Networking (APS ACTION) registry is positive aPLs according to the Revised Sapporo Classification Criteria tested within one year before enrollment. Patients are observed every 12 ± 3 months with clinical data and blood collection. For this prospective analysis, we first analyzed the causes of death for patients reported as “deceased.” Secondly, we analyzed risk factors for death using the adjusted Cox proportional hazards model and calculated survival probability using the Kaplan‐Meier model based on different age groups.ResultsOf 967 patients, 43 (5%) were deceased after a median follow‐up of 5.3 years. Based on the univariate analysis, deceased patients, compared to living patients, were more likely to be older and have a history of arterial thrombosis, catastrophic APS, concomitant systemic autoimmune diseases (SAIDs), and baseline cardiovascular disease (CVD) risk factors. Based on the Cox proportional hazards model adjusted for age and for each of the strongest predictors of death, arterial thrombosis (hazard ratio [HR] 2.94, 95% confidence interval [CI] 1.50–5.76), concomitant SAIDs (HR 2.97, 95% 1.56–5.63), and baseline any CVD risk factor (HR 2.43, 95% CI 1.05–5.71) were significantly associated with mortality.ConclusionIn our cohort of persistently aPL‐positive patients, the mortality rate was 5% after a median follow‐up of five years and was highest for patients ≥60 years old at registry entry. History of arterial thrombosis, concomitant SAIDs, and baseline any CVD risk factor independently predicted future death.

AimsWe compiled two cohorts of colorectal adenosquamous carcinoma (ASC) to describe its histologic and molecular aspects using modern parameters to compare them with literature reports using meta‐analysis of cohorts and individual case series.Methods and ResultsWe identified 53 colorectal ASC from 19 North American academic medical centres, in addition to national database reports on 94 Dutch cases. We analysed available clinical, histologic, and immunohistochemical features and patient outcome. ASC comprised 0.02% of colorectal cancers in the Dutch database. The median cohort patient ages at resection were 65 and 69 years (North American and Dutch cohorts, respectively), with a roughly equal male:female ratio. The squamous component represented between 5% and 95% of each tumour, with a median of 50%. Tumour‐infiltrating lymphocytes (TILs) were generally low (66%), and tumour budding was often Bd1 (64%). Most cases were pT3 (55%) or pT4 (40%), with nodal metastases in more than half (58%). Twenty‐three cases (43%) metastasized distantly, most commonly to the liver. Mismatch repair (MMR) deficiency was identified in 34% of the cases. Follow‐up was available for 48 patients; 13 (27%) had recurrent disease and 29 (60%) died. A total of 31 patients progressed, with median time to progression of 18 months. Available data for the Dutch cohort revealed largely similar findings, as did review of cases in the literature.ConclusionColorectal ASC usually presents at an advanced stage. Despite high rates of MMR deficiency and low tumour budding, TILs were generally low, and there is a high recurrence rate and poor prognosis.

AbstractAutoimmune pancreatitis (AIP) is identified as a severe chronic immune‐related disorder in pancreas, including two subtypes. In this study, pancreatic lesions in patients diagnosed as either type 1 AIP or type 2 AIP are examined, and these patients’ peripheral blood at single‐cell level. Furthermore, flow cytometry, immunofluorescence, and functional assays are performed to verify the identified cell subtypes. In type 1 AIP, there is a notable increase in the amount of B cells and plasma cells, and IgG4+ plasma cells are key pathogenic cells of AIP. The differentiation path of naïve‐stage B cells into IgG4+ produced plasma cells is observed, and an increased amount of T helper cells and T follicular helper (Tfh) cells. This study also reveals that HIF‐1α, an activated transcriptional factor, can directly bind to promoter site of NAMPT, promoting higher levels of visfatin production in HIF1A+ classical monocytes. Pancreatic stellate cells can be activated by extracellular visfatin and promote the development of fibrotic response in pancreatic lesions across both AIP subtypes. The current findings shed light on the exploration of dynamic alterations in peripheral blood cells and cell subgroups in pancreatic lesions of AIP, while elucidating a pathogenic cell subset and potential fibrosis mechanism of AIP.

Migraine with aura(MwA) is associated with an increased risk of stroke and adverse vascular outcomes compared to those with migraine without aura (MwoA). AI-ECG prediction models developed at our institution can evaluate the probability of atrial fibrillation (AF) and estimate a patient’s age based on a normal sinus rhythm (NSR) ECG. Delta age, AI-ECG estimated age minus chronological age, indicates endothelial dysfunction and is associated with cardiovascular mortality. We aim to assess how AI-ECG prediction model outputs, specifically the AF probability and delta age, are associated with adverse vascular outcomes in patients with migraine. Adult patients diagnosed with MwA and MwoA from 2000-2020 with at least one digital, standard 12-lead ECG were identified. The first ECG that showed NSR is used as the index ECG. Patients with any adverse vascular outcomes before the index ECG were excluded. Adverse vascular outcomes used as endpoints include acute ischemic stroke, acute myocardial infarction, deep vein thrombosis/pulmonary embolism, AF, and carotid artery dissection. A total of 31301 patients (13783 MwA, 17518 MwoA) were included in our analysis. The mean age at the time of the index ECG was 44.3 (14.5), and the average follow-up time was 71.6 (69.8) months. Based on the index ECG, the mean AF probability was significantly higher in MwA compared to MwoA (2.39 vs 2.06, p< 0.001), while the delta age was lower in MwA compared to MwoA (3.7 vs 4.2, p <.001). The prevalences of all vascular outcomes are summarized in Table 1. Multivariate Cox regression models showed that a higher AF prediction model output (every 10% increase), as well as a higher delta age (every 10-year increase), are associated with an increased risk of composite vascular outcomes (HR1.20, 95%CI 1.17-1.23, p<.001, and HR1.19, 95%CI 1.14-1.23, p < .001) [Table 2]. The Kaplan-Meier curve of adverse vascular outcome-free survival by AF prediction model output, using 1% as the cutoff (HR 1.49, 95% CI 1.41, 1.57, p<.001), and by delta age, using 2-year as the cutoff (HR 1.14, 95% CI 1.08, 1.21, p <. 001) are presented in Figure 1. Having aura, older age, male, coronary artery disease, congestive heart failure, diabetes, hypertension, and tobacco use were also associated with a higher risk of adverse vascular outcomes. Our results demonstrated the potential of using AI-ECG AF prediction model output and delta age to identify migraine patients at risk for adverse vascular outcomes.

Abstract Background 16S ribosomal RNA (rRNA) gene PCR and sequencing may serve as an adjunctive diagnostic tool in complex infections, identifying bacteria in patients on antibiotics whose cultures may be negative. Data on the optimal clinical settings for utilizing this type of testing are limited. This study reviews a single center's 16S rRNA PCR/sequencing experience in children to identify clinical syndromes and optimize specimen choice for higher yield, leading to testing of appropriate patients. Methods A retrospective study was performed at Mayo Clinic, Rochester involving children aged 0 to 18 years whose normally sterile tissue or fluid samples underwent 16S rRNA gene PCR/sequencing. The assay involved an up-front real-time PCR assay, reported as negative or submitted to Sanger or next-generation sequencing depending on Ct values. Data was collected on patient characteristics and results of 16S rRNA gene PCR/sequencing and conventional tests. Impact on clinical decision-making was assessed as to whether the advanced molecular diagnostic changed antimicrobial therapy. Results A total of 162 tests were performed on 124 patients, including 47% females (58/124) with a median age of 9.6 (range, 2.2-15.0) years. Overall, 33/162 (20%) of tests were positive in 24/124 (19%) patients. 58% of positive tests (19/33) were from samples with negative bacterial cultures. Cerebrospinal fluid was the most common specimen tested (n=38; 31%). Positive results were more likely from fluid compared to tissue samples (OR [95% CI]: 3.1 [1.3, 7.1], p=.007; OR [95% CI]: 0.3 [0.1, 0.8], p=.007, respectively). Testing was positive in 5/10 (50%) pleural fluids tested, a higher positivity rate than any other specimen type (OR [95% CI]: 5 [1.3, 19.0], p=.011). No significant changes in antibiotics were made within 24 hours of reporting positive 16S rRNA gene PCR/sequencing results. Conclusion This study highlights the importance of selecting appropriate sample types for 16S rRNA gene PCR/sequencing in pediatric patients. The assay is most likely to yield positive results in children with pleural effusion and in other fluid samples such as subdural and synovial fluid. Further implementation science research is needed to achieve impact on clinical practice. Disclosures Robin Patel, MD, a patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, a: See above|MicuRx Pharmaceuticals and BIOFIRE: Grant/Research Support|PhAST, Day Zero Diagnostics, Abbott Laboratories, Sysmex, DEEPULL DIAGNOSTICS, S.L., Netflix, Oxford Nanopore Technologies and CARB-X: Advisor/Consultant|Up-to-Date and the Infectious Diseases Board Review Course.: Honoraria

Importance Normothermic machine perfusion (NMP) has been shown to reduce peritransplant complications. Despite increasing NMP use in liver transplant (LT), there is a scarcity of real-world clinical experience data. Objective To compare LT outcomes between donation after brain death (DBD) and donation after circulatory death (DCD) allografts preserved with NMP or static cold storage (SCS). Design, Setting, and Participants This single-center, retrospective observational cohort study included all consecutive adult LTs performed between January 2019 and December 2023 at the Mayo Clinic in Arizona. Data analysis was performed between February 2024 and June 2024. Outcomes of DBD-SCS, DBD-NMP, DCD-SCS, and DCD-NMP transplants were compared. Exposure DBD and DCD livers preserved on NMP or SCS. Main Outcomes and Measures The primary outcomes were early allograft dysfunction (EAD), intraoperative transfusion, and post-LT hospital resource use, including length of stay (LOS) and readmissions. Secondary outcomes included acute kidney injury (AKI) and 1-year graft and patient survival. Results A total of 1086 LTs were included in the following 4 groups: DBD-SCS (n = 480), DBD-NMP (n = 63), DCD-SCS (n = 264), and DCD-NMP (n = 279). Among LT recipients, median (IQR) age was 60.0 years (52.0-66.0); 399 LT recipients (36.7%) were female. DCD-NMP had the lowest EAD rate (17.5%), followed by DCD-SCS (50.0%), DBD-NMP (36.8%), and DBD-SCS (27.3%) ( P &amp;lt; .001). DCD-NMP had the lowest intraoperative transfusion requirement compared to all other groups. Hospital and intensive care unit (ICU) LOS were shortest in DCD-NMP (median [IQR] hospital LOS, 5.0 days [4.0-7.0]; P = .01; median [IQR] ICU LOS, 1.5 days [1.2-3.1]; P = .01). One-year cumulative readmission probability was 86% lower for DCD-NMP vs DCD-SCS (95% CI, 0.09-0.22; P &amp;lt; .001) and 53% lower for DBD-NMP vs DBD-SCS (95% CI, 0.26-0.87; P &amp;lt; .001). AKI events were lower in DCD-NMP (31.1%) vs DCD-SCS (47.4%) ( P = .001). Compared to SCS, the NMP group had a 78% overall reduction in graft failure (hazard ratio [HR], 0.22; 95% CI, 0.10-0.49; P &amp;lt; .001). For those receiving DCD allografts, the risk reduction was even more pronounced, with an 87% decrease in graft failure (HR, 0.13; 95% CI, 0.05-0.33; P &amp;lt; .001). NMP was significantly protective from patient mortality vs SCS (HR, 0.31; 95% CI, 0.12-0.80; P = .02). Conclusions and Relevance In this observational high-volume cohort study, NMP significantly improved LT clinical outcomes and reduced hospital resource use, especially in DCD allografts. NMP may enhance access to LT by addressing the challenges historically linked with DCD liver use.

ABSTRACT Symmetry refers to properties that remain invariant upon mathematical transformations. The principles of symmetry have guided numerous important discoveries in physics and chemistry but not in biology and medicine. Here, we aim to explore the presence of symmetry relationships at the gene expression level as a mean to distinguish between healthy and disease states. We deployed Learning-Based Invariant Feature Engineering - LIFE, a hybrid machine learning approach implemented with two symmetric invariant feature functions (IFFs) to identify Invariant Feature Genes (IFGs), which are gene pairs whose IFF single-value outputs remain invariant across individual samples in a given biological phenotype. Our multiclass classification results across the transcriptomes of 25 normal organs, 25 cancer types, and blood samples obtained from 4 different types of neurodegenerative diseases revealed the presence of unique phenotype-specific IFGs. We constructed networks using these IFGs (IF-Nets) and intriguingly, we demonstrated that the hubs could serve as information encoders, capable of reconstructing sample-wise expression values in relation to their counterpart genes. More importantly, we found that hubs of cancer IF-Nets were enriched with both approved and clinical trial drugs, highlighting “symmetry breaking” as a novel approach for treating diseases.

484 Background: The histopathological growth patterns (HGPs) of liver metastasis reflect the complicated and varied interactions between tumor cells and the host microenvironment. We studied HGPs of gastric cancer liver metastasis (GCLM) and sought to predict them using radiomic and clinical variables. Methods: Hepatectomy was performed in 62 patients with GCLM at our university hospital between 2011 and 2021. HGPs were evaluated according to international consensus guidelines, and were classified as either desmoplastic HGP (dHGP) or non-dHGP. CD4, CD8, VEGF and CD31 were analyzed by immunohistochemistry. Eight hundred and fifty-one radiomics features were extracted from CT portal venous phase images and the optimal radiomics signature was determined by univariate analysis and LASSO regression. Multivariable regression analyses and ROC curves were used to assess the predictive performance of HGPs with a radiomic and clinical combined model. Results: Among 62 patients, 14 were categorized as dHGP, and 48 as non-dHGP. Non-dHGP vs. d-HGP was associated with higher tumor N stage and CEA level, and with decreased CD8 + T cells, and lower VEGF and CD31 expression. HGP status was independently associated with patient cancer-specific survival (CSS) (P＜0.05) multivariately.Analysis of percent relative contribution revealed that HGP ranked first for CSS (35.9%), ahead of T (28.9%) and N (28.9%) stage. A model with combined radiomic and clinical features demonstrated robust performance with area under the curve (AUC) values of 0.993 and 0.933 in the training and validation sets, respectively. Conclusions: Non-invasive determination of radiomic and clinical features was shown to predict HGPs types. Compared to dHGP, GCLM with non-dHGP exhibited significantly lower immune cell infiltration and decreased angiogenesis. Among features examined in GCLM, HGP was the most robust for prognostication. Univariate and multivariate analysis of prognostic factors for cancer-specific survival. Characteristics Univariate analysis Multivariate rergression analysis HR (95%CI) P HR (95%CI) P Gender ( Women vs Men ) 1.13(0.61-2.09) 0.71 Age ( >60years vs ≤60years) 1.08(0.60-1.70) 0.98 HGP ( non-desmoplastic HGP vs desmoplastic HGP ) 3.63(1.78-7.41) 0.00 3.48(1.37-8.88) 0.01 T stage ( T3-T4 vs T1-T2 ) 2.03(1.08-3.80) 0.03 2.29(1.15-4.58) 0.02 N stage ( N1-N3 vs N0 ) 3.46(1.66-7.23) 0.00 2.54(1.17-5.56) 0.02 CEA ( >5ng/ml vs ≤5ng/ml ) 2.37(1.25-4.48) 0.01 1.56(0.70-3.48) 0.27