Citations

Abstract Objective Textual radiology reports contain a wealth of information that may help understand associations among diseases and imaging observations. This study evaluated the ability to detect causal associations among diseases and imaging findings from their co-occurrence in radiology reports. Materials and Methods This IRB-approved and HIPAA-compliant study analyzed 1 702 462 consecutive reports of 1 396 293 patients; patient consent was waived. Reports were analyzed for positive mention of 16 839 entities (disorders and imaging findings) of the Radiology Gamuts Ontology (RGO). Entities that occurred in fewer than 25 patients were excluded. A Bayesian network structure-learning algorithm was applied at P < 0.05 threshold: edges were evaluated as possible causal relationships. RGO and/or physician consensus served as ground truth. Results 2742 of 16 839 RGO entities were included, 53 849 patients (3.9%) had at least one included entity. The algorithm identified 725 pairs of entities as causally related; 634 were confirmed by reference to RGO or physician review (87% precision). As shown by its positive likelihood ratio, the algorithm increased detection of causally associated entities 6876-fold. Discussion Causal relationships among diseases and imaging findings can be detected with high precision from textual radiology reports. Conclusion This approach finds causal relationships among diseases and imaging findings with high precision from textual radiology reports, despite the fact that causally related entities represent only 0.039% of all pairs of entities. Applying this approach to larger report text corpora may help detect unspecified or heretofore unrecognized associations.

OBJECTIVES: To describe the factors affecting critical care capacity and how critical care organizations (CCOs) within academic centers in the U.S. flow-size critical care resources under normal operations, strain, and surge conditions. DATA SOURCES: PubMed, federal agency and American Hospital Association reports, and previous CCO survey results were reviewed. STUDY SELECTION: Studies and reports of critical care bed capacity and utilization within CCOs and in the United States were selected. DATA EXTRACTION: The Academic Leaders in the Critical Care Medicine Task Force established regular conference calls to reach a consensus on the approach of CCOs to “flow-sizing” critical care services. DATA SYNTHESIS: The approach of CCOs to “flow-sizing” critical care is outlined. The vertical (relation to institutional resources, e.g., space allocation, equipment, personnel redistribution) and horizontal (interdepartmental, e.g., emergency department, operating room, inpatient floors) integration of critical care delivery (ICUs, rapid response) for healthcare organizations and the methods by which CCOs flow-size critical care during normal operations, strain, and surge conditions are described. The advantages, barriers, and recommendations for the rapid and efficient scaling of critical care operations via a CCO structure are explained. Comprehensive guidance and resources for the development of “flow-sizing” capability by a CCO within a healthcare organization are provided. CONCLUSIONS: We identified and summarized the fundamental principles affecting critical care capacity. The taskforce highlighted the advantages of the CCO governance model to achieve rapid and cost-effective “flow-sizing” of critical care services and provide recommendations and resources to facilitate this capability. The relevance of a comprehensive approach to “flow-sizing” has become particularly relevant in the wake of the latest COVID-19 pandemic. In light of the growing risks of another extreme epidemic, planning for adequate capacity to confront the next critical care crisis is urgent.

Esophageal adenocarcinoma (EAC) is rising in incidence and has a poor 5-year survival. Decades of targeted screening for Barrett’s esophagus (BE), the precursor to EAC, have not appreciably reduced EAC incidence. Here, we review the drawbacks of the current screening paradigm, including overreliance on GERD symptoms and sedated upper endoscopy. We debate the merits of a universal BE screening program. We propose an ideal BE screening strategy combining novel risk stratification models and non-invasive screening techniques to expand selective screening to patients without GERD, but at elevated risk for BE.

Abstract Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������

Objectives:We sought to evaluate the safety and effectiveness of fecal microbiota transplantation (FMT) for recurrent Clostridioides difficile infection (CDI) in pediatric immunocompromised (IC) patients.Methods:This is a multicenter retrospective cohort study of pediatric participants who underwent FMT between March 2013 and April 2020 with 12‐week follow‐up. Pediatric patients were included if they met the definition of IC and were treated with FMT for an indication of recurrent CDI. We excluded patients over 18 years of age, those with incomplete records, insufficient follow‐up, or not meeting study definition of IC. We also excluded those treated for Clostridioides difficile recurrence without meeting the study definition and those with inflammatory bowel disease without another immunocompromising condition.Results:Of 59 pediatric patients identified at 9 centers, there were 42 who met inclusion and no exclusion criteria. Included patients had a median age of 6.7 years. Etiology of IC included: solid organ transplantation (18, 43%), malignancy (12, 28%), primary immunodeficiency (10, 24%), or other chronic conditions (2, 5%). Success rate was 79% after first FMT and 86% after 1 or more FMT. There were no statistically significant differences in patient characteristics or procedural components when patients with a failed FMT were compared to those with a successful FMT. There were 15 total serious adverse events (SAEs) in 13 out of 42 (31%) patients that occurred during the follow‐up period; 4 (9.5%) of which were likely treatment‐related. There were no deaths or infections with multidrug resistant organisms during follow‐up and all patients with a SAE fully recovered.Conclusions:The success rate of FMT for recurrent CDI in this pediatric IC cohort is high and mirrors data for IC adults and immunocompetent children. FMT‐related SAEs do occur (9.5%) and highlight the need for careful consideration of risk and benefit.

Abstract Richter syndrome (RS), an aggressive lymphoma that develops in patients with chronic lymphocytic leukemia (CLL), is a striking example of histologic transformation. While recent therapeutic advances have transformed the treatment landscape of CLL and lymphoma, RS remains associated with dismal overall survival. Despite an advanced genomic and molecular characterization of CLL over the past decade, the current understanding of the genetic factors driving evolution of CLL to RS is limited. To decipher the genetics underlying this transformation, we have performed an integrative analysis of exome, genome and transcriptome data generated from matched RS and CLL samples from a discovery cohort of 53 patients with newly diagnosed RS of DLBCL histology. Through computational deconvolution of CLL and RS clones, we constructed phylogenetic relationships and traced evolution of CLL to RS, confirming both clonal related (87%) and unrelated cases (13%). In addition to identifying recognized RS-risk genetic lesions, we discovered novel RS-specific alterations, including 5 putative somatic driver genes (IRF2BP2, SRSF1, B2M, DNMT3A and EZH2), frequent copy number alterations beyond del(9p21)(CDKN2A/B), (including amp(7q21.2) (CDK6), amp(9p24) (PDL1/L2), and amp(1q23)(MCL1)), and recurrent whole genome duplication and chromothripsis. Integration of exome and genome sequencing data led to the identification of distinct molecular subtypes of RS with prognostic importance. To confirm these molecular subtypes, a validation cohort of 47 RS cases has been assembled with paired exome and transcriptome data. To further investigate the stepwise clonal evolution of CLL to RS, we performed single-cell RNA-sequencing on biopsy samples obtained at diagnosis from 5 individuals with clonally related transformation. Using a novel tool, CNVSingle, we inferred allele specific single-cell copy number alterations that enabled identification of the single-cell clusters representing distinct CLL and RS genetic subclones as well as intermediate, or transitional, evolutionary states. RS cells displayed gene expression enriched in pathways of MYC targets and cell cycle, in line with similar analysis on bulk transcriptomes. Finally, by ultra-low pass (ULP)-WGS sequencing of plasma samples from RS patients, we demonstrate detection of RS tumor DNA in plasma months prior to initial clinical diagnosis (n=3 of 6) or post-allogeneic stem cell transplant relapse (n=2 of 2). cfDNA is thus a promising tool for early detection of emerging RS and RS relapse as well as for non-invasive detection surrounding diagnosis. Altogether, our study defines RS-specific alterations and provides a molecular definition of RS, identifies distinct genetic subtypes of RS with prognostic significance, traces the evolutionary path to RS and suggests future strategies for improved detection. Citation Format: Erin M Parry, Ignaty Leshchiner, Romain Guieze, Connor Johnson, Eugen Tausch, Sameer A Parikh, Camilla K Lemvigh, Conor Messer, Filippo Utro, Chaya Levovitz, Kahn Rhrissorrakrai, Matthew S Davids, Julien Broseus, Shuqiang Li, Ziao Lin, Binyamin A Knisbacher, Christof Schneider, Laura Z Rassenti, Thomas J Kipps, Nitin Jain, William Wierda, Florence Cymbalista, Neil E Kay, Kenneth J Livak, Brian P Danysh, Chip Stewart, Donna Neuberg, Jennifer R Brown, Laxmi Paridi, Stephan Stilgenbauer, Gaddy Getz, Catherine Wu. Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome [abstract]. In: Proceedings of the Third AACR International Meeting: Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2022 Jun 23-26; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2022;3(5_Suppl):Abstract nr A13.