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Objectives: Clinical note section identification helps locate relevant information and could be beneficial for downstream tasks such as named entity recognition. However, the traditional supervised methods suffer from transferability issues. This study proposes a new framework for using large language models (LLMs) for section identification to overcome the limitations., Materials and Methods: We framed section identification as question-answering and provided the section definitions in free-text. We evaluated multiple LLMs off-the-shelf without any training. We also fine-tune our LLMs to investigate how the size and the specificity of the fine-tuning dataset impacts model performance., Results: GPT4 achieved the highest F 1 score of 0.77. The best open-source model (Tulu2-70b) achieved 0.64 and is on par with GPT3.5 (ChatGPT). GPT4 is also found to obtain F 1 scores greater than 0.9 for 9 out of the 27 (33%) section types and greater than 0.8 for 15 out of 27 (56%) section types. For our fine-tuned models, we found they plateaued with an increasing size of the general domain dataset. We also found that adding a reasonable amount of section identification examples is beneficial., Discussion: These results indicate that GPT4 is nearly production-ready for section identification, and seemingly contains both knowledge of note structure and the ability to follow complex instructions, and the best current open-source LLM is catching up., Conclusion: Our study shows that LLMs are promising for generalizable clinical note section identification. They have the potential to be further improved by adding section identification examples to the fine-tuning dataset., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objective: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener" that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API)., Methods: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and artificial intelligence (AI) for processing unstructured text., Results: Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across 5 healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements., Discussion and Conclusion: Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs, (2) increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: The application of Natural Language Processing (NLP) in the clinical domain is important due to the rich unstructured information in clinical documents, which often remains inaccessible in structured data. When applying NLP methods to a certain domain, the role of benchmark datasets is crucial as benchmark datasets not only guide the selection of best-performing models but also enable the assessment of the reliability of the generated outputs. Despite the recent availability of language models (LMs) capable of longer context, benchmark datasets targeting long clinical document classification tasks are absent., Materials and Methods: To address this issue, we propose LCD benchmark, a benchmark for the task of predicting 30-day out-of-hospital mortality using discharge notes of MIMIC-IV and statewide death data. We evaluated this benchmark dataset using baseline models, from bag-of-words and CNN to instruction-tuned large language models. Additionally, we provide a comprehensive analysis of the model outputs, including manual review and visualization of model weights, to offer insights into their predictive capabilities and limitations., Results and Discussion: Baseline models showed 28.9% for best-performing supervised models and 32.2% for GPT-4 in F1-metrics. Notes in our dataset have a median word count of 1687. Our analysis of the model outputs showed that our dataset is challenging for both models and human experts, but the models can find meaningful signals from the text., Conclusion: We expect our LCD benchmark to be a resource for the development of advanced supervised models, or prompting methods, tailored for clinical text. The benchmark dataset is available at https://github.com/Machine-Learning-for-Medical-Language/long-clinical-doc.

Platform trials are generally regarded as an innovative approach to address clinical valuation of early stage candidates, regardless of modality as the evidence evolves. As a type of randomized clinical trial (RCT) design construct in which multiple interventions are evaluated concurrently against a common control group allowing new interventions to be added and the control group to be updated throughout the trial, they provide a dynamic and efficient mechanism to compare and potentially discriminate new treatment candidates. Their recent use in the evaluation of new therapies for COVID-19 has spurred new interest in the approach. The paucity of platform trials is less influenced by the novelty and operational requirements as opposed to concerns regarding the sharing of intellectual property (IP) and the lack of infrastructure to operationalize the conduct in the context of IP and data sharing. We provide a mechanism how this can be accomplished through the use of a digital research environment (DRE) providing a safe and secure platform for clinical researchers, quantitative and physician scientists to analyze and develop tools (e.g., models) on sensitive data with the confidence that the data and models developed are protected. A DRE, in this context, expands on the concept of a trusted research environment (TRE) by providing remote access to data alongside tools for analysis in a securely controlled workspace, while allowing data and tools to be findable, accessible, interoperable, and reusable (FAIR), version-controlled, and dynamically grow in size or quality as a result of each treatment evaluated in the trial., Competing Interests: Declaration of competing interest The authors declare no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

Background: Mechanical thrombectomy (MT) is the standard of care for acute ischemic stroke (AIS) patients with large vessel occlusion (LVO). The SOFAST study collected clinical evidence on the safety and efficacy of the 6 French SOFIA Flow Plus aspiration catheter (SOFIA 6F) when used as first-line treatment., Methods: This was a prospective, multicenter investigation to assess the safety and efficacy of SOFIA 6F used for first-line aspiration. Anterior circulation LVO stroke patients were enrolled. The primary endpoint was the final modified Thrombolysis in Cerebral Infarction (mTICI)≥2b rate. Secondary endpoints included first-pass and first-line mTICI≥2b rates, times from arteriotomy to clot contact and mTICI≥2b, and 90-day modified Rankin Scale (mRS)≤2. First-line and final mTICI scores were adjudicated by an independent imaging core lab. Safety events were assessed by an independent clinical events adjudicator., Results: A total of 108 patients were enrolled across 12 centers from July 2020 to June 2022. Median age was 67 years, median National Institutes of Health Stroke Scale (NIHSS) was 15.5, and 56.5% of patients received intravenous thrombolytics. At the end of the procedure, 97.2%, 85.2%, and 55.6% of patients achieved mTICI≥2b, ≥2c, and 3, respectively. With SOFIA 6F first-line aspiration, 87.0%, 79.6%, and 52.8% achieved mTICI≥2b, ≥2c, and 3, respectively. After the first pass, 75.0%, 70.4%, and 50.9% achieved mTICI≥2b, ≥2c, and 3, respectively. Median times from arteriotomy to clot contact and successful revascularization were 12 and 17 min, respectively. At 90 days, 66.7% of patients achieved mRS≤2., Conclusions: First-line aspiration with SOFIA 6F is safe and effective with high revascularization rates and short procedure times., Competing Interests: Competing interests: DG: research funding from the National Institutes of Health, Focused Ultrasound Foundation, MicroVention, University of Calgary, and University of Maryland Medical Center; consultant for Navigantis. CS: research support from MicroVention, National Institutes of Health/National Institute of Neurological Disorders and Stroke (NIH/NINDS), Balt, Penumbra, Medtronic, Cerenovus, Route 92, MIVI, Stryker; consultant for Medtronic, Stryker, Balt, Werfen, Viz.ai, MicroVention; shareholder for Neurotechnology Investors, REIST. DHS: consultant for Medtronic, Stryker, and Kaneka; speaker for Medtronic; proctor for Medtronic; grant support from MicroVention; advisory board for Scientia and Vasorum; stockholder of Scientia and Vasorum. GT: consultant for Dynamed, Medtronic, and Penumbra. DF: consultant for Medtronic, Cerenovus, MicroVention, Penumbra, Stryker, Balt USA, MENTICE, Neurogami, RAPID. AI, RAPID Medical, Phenox Medical, Scientia Medical, Perfuze, Vesalio; proctor for Medtronic, MicroVention; research support from MicroVention, Penumbra, Stryker, Balt USA, Siemens; advisory board on Arsenal Medical, NVMed, Perfuze; stock holder in Neurogami, Arsenal Medical, Scientia Medical, NVMed, and Perfuze., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Inflammatory central nervous system (CNS) diseases, such as multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), are characterized by humoral immune abnormalities. Anti-MOG antibodies are not specific to MOGAD, with their presence described in MS. Autoantibodies may also be present and play a role in various neurodegenerative diseases. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease driven by motor neuron dysfunction. While immune involvement in ALS has been recognized, the presence of antibodies targeting CNS myelin antigens has not been established. We aimed to establish a live cell-based assay for quantification of serum anti-MOG IgG1 in patients with CNS diseases, including MS and ALS. In total, 771 serum samples from the John L. Trotter MS Center and the Northeast ALS Consortium were examined using a live cell-based assay for detection of anti-MOG IgG1. Samples from three cohorts were tested in blinded fashion: healthy control (HC) subjects, patients with clinically diagnosed MOGAD, and an experimental group of ALS and MS patients. All samples from established MOGAD cases were positive for anti-MOG antibodies, while all HC samples were negative. Anti-MOG IgG1 was detected in 65 of 658 samples (9.9%) from MS subjects and 4 of 108 (3.7%) samples from ALS subjects. The presence of serum anti-MOG IgG1 in MS and ALS patients raises questions about the contribution of these antibodies to disease pathophysiology as well as accuracy of diagnostic approaches for CNS inflammatory diseases., (Published by Elsevier B.V.)

Short-interfering RNA (siRNA) has gained significant interest for treatment of neurological diseases by providing the capacity to achieve sustained inhibition of nearly any gene target. Yet, achieving efficacious drug delivery throughout deep brain structures of the CNS remains a considerable hurdle. We herein describe a lipid-siRNA conjugate that, following delivery into the cerebrospinal fluid (CSF), is transported effectively through perivascular spaces, enabling broad dispersion within CSF compartments and through the CNS parenchyma. We provide a detailed examination of the temporal kinetics of gene silencing, highlighting potent knockdown for up to five months from a single injection without detectable toxicity. Single-cell RNA sequencing further demonstrates gene silencing activity across diverse cell populations in the parenchyma and at brain borders, which may provide new avenues for neurological disease-modifying therapies.

Competing Interests: DSB reports being an Associate Editor of Radiation Oncology at HemOnc.org (no financial compensation, unrelated to this work, and recieving funding from American Association for Cancer Research, unrelated to this work. HJWLA reports advising and consulting for Onc.AI, Love Health, Sphera, Editas, AstraZeneca, and Bristol Myers Squibb, unrelated to this work. RHM reports being on an Advisory Board for ViewRay and AstraZeneca; Consulting for Varian Medical Systems and Sio Capital Management; and honorarium from Novartis and Springer Nature. JL reports research funding from Viewray, NH Theraguix, and Varian. ML reports advisory and consulting for Pfizer, Gilead, Novartis, and AstraZeneca, unrelated to this work. BHK reports research funding from Botha-Chan Low Grade Glioma Consortium (National institutes of Health [NIH]-USA K08DE030216-01). All other authors declare no competing interests. The authors acknowledge financial support from the Woods Foundation (DSB, RHM, BHK, and HJWLA) NIH (NIH-USA U54CA274516-01A1 (SC, MG, BHK, HJWLA, GKS, and DSB), NIH-USA U24CA194354 (HJWLA), NIH-USA U01CA190234 (HJWLA), NIH-USA U01CA209414 (HJWLA), and NIH-USA R35CA22052 (HJWLA), NIH-NIDA R01DA051464 (MA), R01GM114355 (GKS), NIH-USA R01LM012973 (TM and MA), NIH-USA R01MH126977 (TM), NIH-USA U54 TW012043-01 (JG and LAC), NIH-USA OT2OD032701 (JG and LAC), NIH-USA R01EB017205 (LAC), and the EU European Research Council (HJWLA 866504), all outside of the submitted work. All data collected and generated in this study, after de-identification, are available at https://github.com/AIM-Harvard/OncQA. SC: conceptualisation, data curation, formal analysis, investigation, methodology, visualisation, and writing (original draft, review, and editing). MG: conceptualisation, data curation, and formal analysis. SM, FH EH, BHK, FEC, JL: data curation, investigation, and methodology. RHM: data curation, investigation, methodology, and writing (review and editing). HJWLA: investigation, methodology, resources, and writing (review and editing). JG: formal analysis, investigation, methodology, visualisation, and writing (review and editing). TM and GKS: formal analysis, investigation, methodology, and writing (review and editing). ML data curation, formal analysis, investigation, and methodology. LAC formal analysis, investigation, supervision, and writing (review and editing). MA: conceptualisation, data curation, formal analysis, investigation, methodology, supervision, and writing (review and editing). DSB: conceptualisation, data curation, formal analysis, investigation, methodology, supervision, visualisation, resources, and writing (original draft, review, and editing). SC and DSB directly accessed and verified the underlying data reported in the manuscript. All authors have full access to all the data in the study and accept responsibility to submit for publication.

Background: The optimal recanalization goal and number of endovascular thrombectomy (EVT) passes for elderly patients with large vessel occlusion strokes is unclear., Methods: Consecutive patients 80 years or older undergoing EVT were identified from 2016 to 2022 at a single center. Clinical information, procedural details, and modified treatment in cerebral ischemia (mTICI) scores were collected. Primary outcome was modified Rankin scale (mRS) at 90 days. Bivariate and multivariable analyses were conducted to assess associations between mTICI scores, EVT passes, and 90-day outcomes., Results: One hundred twenty-six patients were identified. At 90 days, mTICI 2b recanalization resulted in high rates of poor outcomes (8.7% functional independence and 60.9% mortality) not significantly different from mTICI 0, 1 or 2a (median mRS 6 vs. 6, P = 0.61). Complete recanalization (mTICI 2c or 3) led to significantly better mRS outcomes at 90 days compared to mTICI 2b (median mRS 4 vs. 6, adjusted P = 0.038), with 26.8% functional independence and 37.8% mortality. In multivariable analysis, complete recanalization was significantly associated with better 90-day outcomes than mTICI 2b or lower recanalization (odds ratio 4.24 [95% Confidence interval 1.46-12.3]; P = 0.002), while the number of passes was not independently associated with worse outcomes (P = 0.98)., Conclusions: For octogenarians, mTICI 2b recanalization yields limited clinical benefit and results in poor 90-day outcomes. In contrast, complete recanalization is independently associated with significantly better outcomes. Thus, once the decision is made to pursue EVT in the elderly, mTICI 2c or better recanalization should be the angiographic goal. Providers should not withhold thrombectomy passes based on age alone., (Copyright © 2024. Published by Elsevier Inc.)

Objective: The timely stratification of trauma injury severity can enhance the quality of trauma care but it requires intense manual annotation from certified trauma coders. The objective of this study is to develop machine learning models for the stratification of trauma injury severity across various body regions using clinical text and structured electronic health records (EHRs) data., Materials and Methods: Our study utilized clinical documents and structured EHR variables linked with the trauma registry data to create 2 machine learning models with different approaches to representing text. The first one fuses concept unique identifiers (CUIs) extracted from free text with structured EHR variables, while the second one integrates free text with structured EHR variables. Temporal validation was undertaken to ensure the models' temporal generalizability. Additionally, analyses to assess the variable importance were conducted., Results: Both models demonstrated impressive performance in categorizing leg injuries, achieving high accuracy with macro-F1 scores of over 0.8. Additionally, they showed considerable accuracy, with macro-F1 scores exceeding or near 0.7, in assessing injuries in the areas of the chest and head. We showed in our variable importance analysis that the most important features in the model have strong face validity in determining clinically relevant trauma injuries., Discussion: The CUI-based model achieves comparable performance, if not higher, compared to the free-text-based model, with reduced complexity. Furthermore, integrating structured EHR data improves performance, particularly when the text modalities are insufficiently indicative., Conclusions: Our multi-modal, multiclass models can provide accurate stratification of trauma injury severity and clinically relevant interpretations., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: While endovascular thrombectomy (EVT) is beneficial for patients with acute large vessel occlusion ischemic strokes, a significant portion of patients still do poorly despite successful recanalization. Identifying patients at high risk for poor outcomes can be helpful for future clinical trial design and optimizing acute stroke triage., Methods: Consecutive EVT patients were identified from 2016 to 2021 at a Comprehensive Stroke Center, and clinical information was recorded. Poor outcome was defined as a 90-day modified Rankin Scale (mRS) of 4 or greater despite achieving a modified thrombolysis in cerebral infarction (mTICI) score of 2b or greater. Multivariable regression analyses were used to identify risk factors for poor outcomes, and a scoring system was constructed., Results: 483 patients with successful recanalization were identified. From a randomly selected training cohort (n = 357), the 10-point BAND score was constructed from independent risk factors for poor outcomes: baseline disability (1 point: baseline mRS ≥ 2), age (1 point: 60-69 years, 2 points: 70-79 years, 3 points: 80-84 years, 4 points: 85 years or older), NIHSS (2 points: 13-17, 3 points: 18-22, and 4 points: ≥ 23), and delay from last known normal (1 point: ≥ 6 h). The BAND score was significantly associated with rates of poor outcomes (p < 0.001), and it achieved an area under the receiver-operating characteristic curve (AUC) of 0.80 (95 %CI 0.76-0.85) in our training cohort and 0.78 (95 %CI 0.70-0.86) in our validation cohort (n = 126). Overall, the BAND score had a significantly higher AUC value than the widely validated THRIVE score and the THRIVE-EVT calculation (p = 0.001 and 0.029, respectively). Among patients with high BAND scores (7 or higher), 88.2 % had poor outcomes., Conclusion: The BAND score is a simple tool to predict poor outcomes despite successful recanalization. Future studies are needed to confirm the BAND score's external validity., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Albumin continues to be used routinely by cardiac anaesthesiologists perioperatively despite lack of evidence for improved outcomes. The Multicenter Perioperative Outcomes Group (MPOG) data ranked our institution as one of the highest intraoperative albumin users during cardiac surgery. Therefore, we designed a quality improvement project (QIP) to introduce a bundle of interventions to reduce intraoperative albumin use in cardiac surgical patients., Methods: Our institutional MPOG data were used to analyse the FLUID-01-C measure that provides the number of adult cardiac surgery cases where albumin was administered intraoperatively by anaesthesiologists from 1 July 2019 to 30 June 2022. The QIP involved introduction of the following interventions: (1) education about appropriate albumin use and indications (January 2021), (2) email communications reinforced with OR teaching (March 2021), (3) removal of albumin from the standard pharmacy intraoperative medication trays (April 2021), (4) grand rounds presentation discussing the QIP and highlighting the interventions (May 2021) and (5) quarterly provider feedback (starting July 2021). Multivariable segmented regression models were used to assess the changes from preintervention to postintervention time period in albumin utilisation, and its total monthly cost., Results: Among the 5767 cardiac surgery cases that met inclusion criteria over the 3-year study period, 16% of patients received albumin intraoperatively. The total number of cases that passed the metric (albumin administration was avoided), gradually increased as our interventions went into effect. Intraoperative albumin utilisation (beta=-101.1, 95% CI -145 to -56.7) and total monthly cost of albumin (beta=-7678, 95% CI -10712 to -4640) demonstrated significant decrease after starting the interventions., Conclusions: At a single academic cardiac surgery programme, implementation of a bundle of simple and low-cost interventions as part of a coordinated QIP were effective in significantly decreasing intraoperative use of albumin, which translated into considerable costs savings., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: This study combines two innovative mouse models in a major gene discovery project to assess the influence of host genetics on asbestos related disease (ARD). Conventional genetics studies provided evidence that some susceptibility to mesothelioma is genetic. However, the identification of host modifier genes, the roles they may play, and whether they contribute to disease susceptibility remain unknown. Here we report a study designed to rapidly identify genes associated with mesothelioma susceptibility by combining the Collaborative Cross (CC) resource with the well-characterised MexTAg mesothelioma mouse model. Methods: The CC is a powerful mouse resource that harnesses over 90% of common genetic variation in the mouse species, allowing rapid identification of genes mediating complex traits. MexTAg mice rapidly, uniformly, and predictably develop mesothelioma, but only after asbestos exposure. To assess the influence of host genetics on ARD, we crossed 72 genetically distinct CC mouse strains with MexTAg mice and exposed the resulting CC-MexTAg (CCMT) progeny to asbestos and monitored them for traits including overall survival, the time to ARD onset (latency), the time between ARD onset and euthanasia (disease progression) and ascites volume. We identified phenotype-specific modifier genes associated with these traits and we validated the role of human orthologues in asbestos-induced carcinogenesis using human mesothelioma datasets. Results: We generated 72 genetically distinct CCMT strains and exposed their progeny (2,562 in total) to asbestos. Reflecting the genetic diversity of the CC, there was considerable variation in overall survival and disease latency. Surprisingly, however, there was no variation in disease progression, demonstrating that host genetic factors do have a significant influence during disease latency but have a limited role once disease is established. Quantitative trait loci (QTL) affecting ARD survival/latency were identified on chromosomes 6, 12 and X. Of the 97-protein coding candidate modifier genes that spanned these QTL, eight genes ( CPED1, ORS1, NDUFA1, HS1BP3, IL13RA1, LSM8, TES and TSPAN12 ) were found to significantly affect outcome in both CCMT and human mesothelioma datasets. Conclusion: Host genetic factors affect susceptibility to development of asbestos associated disease. However, following mesothelioma establishment, genetic variation in molecular or immunological mechanisms did not affect disease progression. Identification of multiple candidate modifier genes and their human homologues with known associations in other advanced stage or metastatic cancers highlights the complexity of ARD and may provide a pathway to identify novel therapeutic targets., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Fisher, Patrick, Hoang, Marcq, Behrouzfar, Young, Miller, Robinson, Bueno, Nowak, Lesterhuis, Morahan and Lake.)

As patients continue to live longer from diseases that predispose them to right ventricular (RV) dysfunction or failure, many more patients will require surgery for acute or chronic health issues. Because RV dysfunction results in significant perioperative morbidity if not adequately assessed or managed, understanding appropriate assessment and treatments is important in preventing subsequent morbidity and mortality in the perioperative period. In light of the epidemiology of right heart disease, a working knowledge of right heart anatomy and physiology and an understanding of the implications of right-sided heart function for perioperative care are essential for perioperative practitioners. However, a significant knowledge gap exists concerning this topic. This manuscript is one part of a collection of papers from the PeriOperative Quality Initiative (POQI) IX Conference focusing on "Current Perspectives on the Right Heart in the Perioperative Period." This review aims to provide perioperative clinicians with an essential understanding of right heart physiology by answering five key questions on this topic and providing an explanation of seven fundamental concepts concerning right heart physiology., (© 2024. The Author(s).)

Background: Real-time surveillance of emerging infectious diseases necessitates a dynamically evolving, computable case definition, which frequently incorporates symptom-related criteria. For symptom detection, both population health monitoring platforms and research initiatives primarily depend on structured data extracted from electronic health records., Objective: This study sought to validate and test an artificial intelligence (AI)-based natural language processing (NLP) pipeline for detecting COVID-19 symptoms from physician notes in pediatric patients. We specifically study patients presenting to the emergency department (ED) who can be sentinel cases in an outbreak., Methods: Subjects in this retrospective cohort study are patients who are 21 years of age and younger, who presented to a pediatric ED at a large academic children's hospital between March 1, 2020, and May 31, 2022. The ED notes for all patients were processed with an NLP pipeline tuned to detect the mention of 11 COVID-19 symptoms based on Centers for Disease Control and Prevention (CDC) criteria. For a gold standard, 3 subject matter experts labeled 226 ED notes and had strong agreement (F 1 -score=0.986; positive predictive value [PPV]=0.972; and sensitivity=1.0). F 1 -score, PPV, and sensitivity were used to compare the performance of both NLP and the International Classification of Diseases, 10th Revision (ICD-10) coding to the gold standard chart review. As a formative use case, variations in symptom patterns were measured across SARS-CoV-2 variant eras., Results: There were 85,678 ED encounters during the study period, including 4% (n=3420) with patients with COVID-19. NLP was more accurate at identifying encounters with patients that had any of the COVID-19 symptoms (F 1 -score=0.796) than ICD-10 codes (F 1 -score =0.451). NLP accuracy was higher for positive symptoms (sensitivity=0.930) than ICD-10 (sensitivity=0.300). However, ICD-10 accuracy was higher for negative symptoms (specificity=0.994) than NLP (specificity=0.917). Congestion or runny nose showed the highest accuracy difference (NLP: F 1 -score=0.828 and ICD-10: F 1 -score=0.042). For encounters with patients with COVID-19, prevalence estimates of each NLP symptom differed across variant eras. Patients with COVID-19 were more likely to have each NLP symptom detected than patients without this disease. Effect sizes (odds ratios) varied across pandemic eras., Conclusions: This study establishes the value of AI-based NLP as a highly effective tool for real-time COVID-19 symptom detection in pediatric patients, outperforming traditional ICD-10 methods. It also reveals the evolving nature of symptom prevalence across different virus variants, underscoring the need for dynamic, technology-driven approaches in infectious disease surveillance., (©Andrew J McMurry, Amy R Zipursky, Alon Geva, Karen L Olson, James R Jones, Vladimir Ignatov, Timothy A Miller, Kenneth D Mandl. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 04.04.2024.)

Sexual transmission of enteric pathogens among men who have sex with men (MSM) is well documented, although whether providers are cognizant of this risk when MSM patients present with gastrointestinal symptoms has not been studied. Over 34 months at a major tertiary metropolitan medical system, this study retrospectively analyzed 436 BioFire FilmArray Gastrointestinal results from 361 patients documented as MSM. An extensive chart review was performed, including specific sexual behaviors, socioeconomic risk factors, and whether providers charted a sexual history when a patient presented for care. Overall BioFire positivity rate was 62% with no significant difference in positivity between persons living with HIV and those without. Patients charted as sexually active had a significantly increased odds ratio (OR) of a positive result compared to those who were not. Anilingus had the highest OR. Providers charted any type of sexual history in 40.6% of cases, and HIV/infectious disease providers were significantly more likely to do this compared to other subspecialties. Sexual transmission of enteric pathogens within MSM is ongoing, and patients are at risk regardless of living with HIV. Not all sexual behaviors have the same associated risk, highlighting opportunities to decrease transmission. Increased provider vigilance and better patient education on sexual transmission of enteric pathogens are needed to reduce the disease burden., Importance: Our work adds several key findings to the growing body of literature describing the epidemiology of enteric pathogens as sexually transmitted infections among men who have sex with men (MSM). We analyzed clinical test results, housing status, provider awareness, sexual behaviors, and symptoms for 361 patients. We found that any sexual activity was associated with an increased risk of diarrheal pathogen detection, whereas being unhoused was not a risk factor. These findings suggest separate transmission networks between unhoused persons, who are also at risk of infectious diarrhea, and MSM. Moreover, our study suggested low awareness among patient-facing clinicians that diarrheal pathogens can be sexually transmitted. Together, our findings indicate an important opportunity to disrupt transmission cycles by educating clinicians on how to assess and counsel MSM patients., Competing Interests: The authors declare no conflict of interest.

Background and Objectives: Magnetic resonance-guided focused ultrasound (MRgFUS) central lateral thalamotomy (CLT) has not yet been validated for treating refractory neuropathic pain (NP). Our aim was to assess the safety and potential efficacy of MRgFUS CLT for refractory NP., Methods: In this prospective, nonrandomized, single-arm, investigator-initiated phase I trial, patients with NP for more than 6 months related to phantom limb pain, spinal cord injury, or radiculopathy/radicular injury and who had undergone at least one previous failed intervention were eligible. The main outcomes were safety profile and pain as assessed using the brief pain inventory, the pain disability index, and the numeric rating scale. Medication use and the functional connectivity of the default mode network (DMN) were also assessed., Results: Ten patients were enrolled, with nine achieving successful ablation. There were no serious adverse events and 12 mild/moderate severity events. The mean age was 50.9 years (SD: 12.7), and the mean symptom duration was 12.3 years (SD: 9.7). Among eight patients with a 1-year follow-up, the brief pain inventory decreased from 7.6 (SD: 1.1) to 3.8 (SD: 2.8), with a mean percent decrease of 46.3 (SD: 40.6) (paired t -test, P = .017). The mean pain disability index decreased from 43.0 (SD: 7.5) to 25.8 (SD: 16.8), with a mean percent decrease of 39.3 (SD: 41.6) ( P = .034). Numeric rating scale scores decreased from a mean of 7.2 (SD: 1.8) to 4.0 (SD: 2.8), with a mean percent decrease of 42.8 (SD: 37.8) ( P = .024). Patients with predominantly intermittent pain or with allodynia responded better than patients with continuous pain or without allodynia, respectively. Some patients decreased medication use. Resting-state functional connectivity changes were noted, from disruption of the DMN at baseline to reactivation of connectivity between DMN nodes at 3 months., Conclusion: MRgFUS CLT is feasible and safe for refractory NP and has potential utility in reducing symptoms as measured by validated pain scales., (Copyright © Congress of Neurological Surgeons 2023. All rights reserved.)

Background: Large vessel recanalization (LVR) before endovascular therapy (EVT) for acute large vessel ischemic strokes is a poorly understood phenomenon. Better understanding of predictors for LVR is important for optimizing stroke triage and patient selection for bridging thrombolysis., Methods: In this retrospective cohort study, consecutive patients presenting to a comprehensive stroke center for EVT treatment were identified from 2018 to 2022. Demographic information, clinical characteristics, intravenous thrombolysis (IVT) use, and LVR before EVT were recorded. Factors independently associated with different rates of LVR were identified, and a prediction model for LVR was constructed., Results: 640 patients were identified. 57 (8.9%) patients had LVR before EVT. A minority (36.4%) of LVR patients had significant improvements in National Institutes of Health Stroke Scale. Independent predictors for LVR were identified and used to construct the 8-point HALT score: hyperlipidemia (1 point), atrial fibrillation (1 point), location of vascular occlusion (internal carotid: 0 points, M1: 1 point, M2: 2 points, vertebral/basilar: 3 points), and thrombolysis at least 1.5 hours before angiography (3 points). The HALT score had an area under the receiver-operating curve (AUC) of 0.85 (95% CI 0.81 to 0.90, P<0.001) for predicting LVR. LVR before EVT occurred in only 1 of 302 patients (0.3%) with low (0-2) HALT scores., Conclusions: IVT at least 1.5 hours before angiography, site of vascular occlusion, atrial fibrillation, and hyperlipidemia are independent predictors for LVR. The 8-point HALT score proposed in this study may be a valuable tool for predicting LVR before EVT., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Although loss of TAR DNA-binding protein 43 kDa (TDP-43) splicing repression is well documented in postmortem tissues of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), whether this abnormality occurs during early-stage disease remains unresolved. Cryptic exon inclusion reflects loss of function of TDP-43, and thus detection of proteins containing cryptic exon-encoded neoepitopes in cerebrospinal fluid (CSF) or blood could reveal the earliest stages of TDP-43 dysregulation in patients. Here we use a newly characterized monoclonal antibody specific to a TDP-43-dependent cryptic epitope (encoded by the cryptic exon found in HDGFL2) to show that loss of TDP-43 splicing repression occurs in ALS-FTD, including in presymptomatic C9orf72 mutation carriers. Cryptic hepatoma-derived growth factor-like protein 2 (HDGFL2) accumulates in CSF at significantly higher levels in familial ALS-FTD and sporadic ALS compared with controls and is elevated earlier than neurofilament light and phosphorylated neurofilament heavy chain protein levels in familial disease. Cryptic HDGFL2 can also be detected in blood of individuals with ALS-FTD, including in presymptomatic C9orf72 mutation carriers, and accumulates at levels highly correlated with those in CSF. Our findings indicate that loss of TDP-43 cryptic splicing repression occurs early in disease progression, even presymptomatically, and that detection of the HDGFL2 cryptic neoepitope serves as a potential diagnostic biomarker for ALS, which should facilitate patient recruitment and measurement of target engagement in clinical trials., (© 2024. The Author(s).)

The types of clinical notes in electronic health records (EHRs) are diverse and it would be great to standardize them to ensure unified data retrieval, exchange, and integration. The LOINC Document Ontology (DO) is a subset of LOINC that is created specifically for naming and describing clinical documents. Despite the efforts of promoting and improving this ontology, how to efficiently deploy it in real-world clinical settings has yet to be explored. In this study we evaluated the utility of LOINC DO by mapping clinical note titles collected from five institutions to the LOINC DO and classifying the mapping into three classes based on semantic similarity between note t itl es and LOINC DO codes. Additionally, we developed a standardization pipeline that automatically maps clinical note titles from multiple sites to suitable LOINC DO codes, without accessing the content of clinical notes. The pipeline can be initialized with different large language models, and we compared the performances between them. The results showed that our automated pipeline achieved an accuracy of 0.90. By comparing the manual and automated mapping results, we analyzed the coverage of LOINC DO in describing multi-site clinical note titles and summarized the potential scope for extension., Competing Interests: Dr. Hua Xu has research-related financial interests in Melax Technologies, Inc., (©2023 AMIA - All rights reserved.)

Objective : To implement an open source, free, and easily deployable high throughput natural language processing module to extract concepts from clinician notes and map them to Fast Healthcare Interoperability Resources (FHIR). Materials and Methods : Using a popular open-source NLP tool (Apache cTAKES), we create FHIR resources that use modifier extensions to represent negation and NLP sourcing, and another extension to represent provenance of extracted concepts. Results : The SMART Text2FHIR Pipeline is an open-source tool, released through standard package managers, and publicly available container images that implement the mappings, enabling ready conversion of clinical text to FHIR. Discussion : With the increased data liquidity because of new interoperability regulations, NLP processes that can output FHIR can enable a common language for transporting structured and unstructured data. This framework can be valuable for critical public health or clinical research use cases. Conclusion : Future work should include mapping more categories of NLP-extracted information into FHIR resources and mappings from additional open-source NLP tools., (©2023 AMIA - All rights reserved.)

Objective: The classification of clinical note sections is a critical step before doing more fine-grained natural language processing tasks such as social determinants of health extraction and temporal information extraction. Often, clinical note section classification models that achieve high accuracy for 1 institution experience a large drop of accuracy when transferred to another institution. The objective of this study is to develop methods that classify clinical note sections under the SOAP ("Subjective," "Object," "Assessment," and "Plan") framework with improved transferability., Materials and Methods: We trained the baseline models by fine-tuning BERT-based models, and enhanced their transferability with continued pretraining, including domain-adaptive pretraining and task-adaptive pretraining. We added in-domain annotated samples during fine-tuning and observed model performance over a varying number of annotated sample size. Finally, we quantified the impact of continued pretraining in equivalence of the number of in-domain annotated samples added., Results: We found continued pretraining improved models only when combined with in-domain annotated samples, improving the F1 score from 0.756 to 0.808, averaged across 3 datasets. This improvement was equivalent to adding 35 in-domain annotated samples., Discussion: Although considered a straightforward task when performing in-domain, section classification is still a considerably difficult task when performing cross-domain, even using highly sophisticated neural network-based methods., Conclusion: Continued pretraining improved model transferability for cross-domain clinical note section classification in the presence of a small amount of in-domain labeled samples., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Many preclinical and clinical studies support the use of antisense oligonucleotides (ASOs) as effective therapeutic strategies. However, acquiring ASOs for research purposes may be limited by partnerships with the pharmaceutical companies. Our lab previously developed an effective ASO strategy to lower human tau and reverse pathology in aged tauopathy model mice. Testing the efficacy of purchased tau lowering ASOs would provide support for these reagents as broad research tools. Purchased mouse and human tau lowering ASOs were infused or injected intracerebroventricularly into wildtype and tau transgenic mice. Following treatment, brain tissue evaluated for ASO distribution and levels of tau mRNA, protein, and phosphorylated tau. We show that purchased ASOs enter cell types of the brain and effectively decrease mouse or human tau mRNA and protein levels. Human tau lowering ASO treatment in PS19 mice decreased phosphorylated tau and gliosis relative to saline-treated PS19 mice, consistent with our previous study using a non-commercial tau lowering ASO. The results of this study demonstrate the efficacy of purchased tau targeting ASOs in vivo to support their broad use by researchers., Competing Interests: TM is a consultant for Ionis Pharmaceuticals and has a licensing agreement with Ionis regarding use of tau ASOs in neurodegenerative syndrome. TM is an inventor on patent/patent application PCT/US2013/031500, nationalized to US Issued Patent 10,273,474 (with corresponding national stage applications or issued patents in Australia, Canada, Europe, and Japan), and on continuation or divisional patent applications (US patent application number 16/298,607 and Australia Issued Patent 2016202220) regarding use of tau ASOs in neurodegenerative syndrome. TM has a licensing agreement with C2N Diagnostics, is a consultant for Biogen, Bioio, Cytokinetics, Disarm Therapeutics, and UCB, and received honorarium from Regeneron Pharmaceuticals and Denali Therapeutics. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Vemula, Schoch and Miller.)

Background: Challenges to revascularization of large vessel occlusions (LVOs) persist. Current stent retrievers have limited effectiveness for removing organized thrombi. The NeVa device is a novel stent retriever designed to capture organized thrombi within the scaffold during retrieval., Objective: To evaluate the safety and effectiveness of revascularization of acute LVOs with the NeVa device., Methods: Prospective, international, multicenter, single-arm, Investigational Device Exemption study to evaluate the performance of the NeVa device in recanalizing LVOs including internal carotid artery, M1/M2 middle cerebral artery, and vertebrobasilar arteries, within 8 hours of onset. Primary endpoint was rate of expanded Treatment in Cerebral Ischemia (eTICI) score 2b-3 within 3 NeVa passes, tested for non-inferiority against a performance goal of 72% with a -10% margin. Additional endpoints included first pass success and 90-day modified Rankin Scale (mRS) score 0-2. Primary composite safety endpoint was 90-day mortality and/or 24-hour symptomatic intracranial hemorrhage (sICH)., Results: From April 2021 to April 2022, 139 subjects were enrolled at 25 centers. Median National Institutes of Health Stroke Scale (NIHSS) score was 16 (IQR 12-20). In the primary analysis population (n=107), eTICI 2b-3 within 3 NeVa passes occurred in 90.7% (97/107; non-inferiority P<0.0001; post hoc superiority P<0.0001). First pass eTICI 2b-3 was observed in 73.8% (79/107), with first pass eTICI 2b67-3 in 69.2% (74/107) and eTICI 2c-3 in 48.6% (52/107). Median number of passes was 1 (IQR 1-2). Final eTICI 2b-3 rate was 99.1% (106/107); final eTICI 2b67-3 rate was 91.6% (98/107); final eTICI 2c-3 rate was 72.9% (78/107). Good outcome (90-day mRS score 0-2) was seen in 65.1% (69/106). Mortality was 9.4% (13/138) with sICH in 5.0% (7/139)., Conclusions: The NeVa device is highly effective and safe for revascularization of LVO strokes and demonstrates superior first pass success compared with a predicate performance goal., Trial Registration Number: NCT04514562., Competing Interests: Competing interests: AJY: consultant: Penumbra, Cerenovus, Vesalio, Zoll Circulation, Philips Neurovascular; individual stocks/stock options: Nicolab; ownership interest: Insera Therapeutics, Galaxy Therapeutics; research funding (principal investigator (PI) or named investigator): Medtronic, Cerenovus, Penumbra, Stryker, Genentech. LS: consultant: Balt, Medtronic, Microvention, Stryker; research funding (PI or named investigator): Philips. AH: consultant: Medtronic, Microvention, Stryker, Penumbra, Cerenovus, Genentech, GE Healthcare, Scientia, Balt, Viz.ai, Insera therapeutics, Proximie, NeuroVasc, NovaSignal, Vesalio, Rapid Medical, Imperative Care. AS: consultant: Microvention, Stryker, Vesalio. AHS: consultant: Amnis Therapeutics, Apellis Pharmaceuticals, Inc., Boston Scientific, Canon Medical Systems USA, Inc., Cardinal Health 200, LLC, Cerebrotech Medical Systems, Inc., Cerenovus, Cerevatech Medical, Inc; inidividual stocks/stock options: Adona Medical, Inc., Amnis Therapeutics, Bend IT Technologies, Ltd., BlinkTBI, Inc, Borvo Medical, Inc., Cerebrotech Medical Systems, Inc., Cerevatech Medical, Inc., Cognition Medical, Collavidence, I; other; Cerenovus EXCELLENT and ARISE II Trial; Medtronic SWIFT PRIME, VANTAGE, EMBOLISE and SWIFT DIRECT Trials; MicroVention FRED Trial; CONFIDENCE Study; MUSC POSITIVE Trial; Penumbra 3D Separator Trial, Research Funding (PI or named investigator); co-investigator for NIH - 1R01EB030092-01, Project Title: High speed angiography at 1000 frames per second; Mentor for Brain Aneurysm Foundation Carol W. Harvey Chair of Research, Sharon Epperson Chai. SG: Consultant; Stryker, Microvention, Medtronic. TRM: Advisor; Carpl AI. MTF: advisor; Cerenovus; research funding (PI or named investigator): Medtronic Neurovascular; researcher: Stryker Neurovascular, Cerenovus, Rapid Medical. DCH: consultant; Stryker Neurovascular, Cerenovus, Chiesi USA, Brainomix, Poseydon Medical; individual stocks/stock options: VizAI and Motif; other: Jacobs Institute/Medtronic, Vesalio., Frontiers in Neurology. MIC: advisor: Celt/Vasorum; consultant: Microvention, Medtronic, Imperative Care, Q'Apel; individual stocks/stock options: Imperative Care, Celt/Vasorum, Synchron, Endostream, Cerebrotech, Q'Apel, RIST, Three Rivers Medical, Neuolutions, Radical Medical, Tulavi, viseon, VMT, Vastrax, Serenity Medical. MF: consultant: Cerenovus, Balt, Jacobs Institute, Kai Medical, Oculus; research funding (PI or named investigator): Vesalio, Genentech, Siemens. MS: consultant: Vesalio., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Opioid-based anesthesia and analgesia is a traditional component of perioperative care for the cardiac surgery patient. Growing enthusiasm for Enhanced Recovery Programs (ERPs) coupled with evidence of potential harm associated with high-dose opioids suggests that we reconsider the role of opioids in cardiac surgery., Methods: An interdisciplinary North American panel of experts, using a structured appraisal of the literature and a modified Delphi method, derived consensus recommendations for optimal pain management and opioid stewardship for cardiac surgery patients. Individual recommendations are graded based on the strength and level of evidence., Results: The panel addressed 4 main topics: the harms associated with historical opioid use, the benefits of more targeted opioid administration, the use of nonopioid medications and techniques, and patient and provider education. A key principle that emerged is that opioid stewardship should apply to all cardiac surgery patients, entailing judicious and targeted use of opioids to achieve optimal analgesia with the fewest potential side effects. The process resulted in the promulgation of 6 recommendations regarding pain management and opioid stewardship in cardiac surgery, focused on avoiding the use of high-dose opioids, as well as encouraging more widespread application of foundational aspects of ERPs, such as the use of multimodal nonopioid medications and regional anesthesia techniques, formal patient and provider education, and structured system-level opioid prescription practices., Conclusions: Based on the available literature and expert consensus, there is an opportunity to optimize anesthesia and analgesia for cardiac surgery patients. Although additional research is needed to establish specific strategies, core principles of pain management and opioid stewardship apply to the cardiac surgery population., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Astrocyte-specific ion pump α2-Na+/K+-ATPase plays a critical role in the pathogenesis of amyotrophic lateral sclerosis (ALS). Here, we test the effect of Atp1a2 mRNA-specific antisense oligonucleotides (ASOs) to induce α2-Na+/K+-ATPase knockdown in the widely used ALS animal model, SOD1*G93A mice. Two ASOs led to efficient Atp1a2 knockdown and significantly reduced SOD1 aggregation in vivo. Although Atp1a2 ASO-treated mice displayed no off-target or systemic toxicity, the ASO-treated mice exhibited an accelerated disease onset and shorter lifespan than control mice. Transcriptomics studies reveal downregulation of genes involved in oxidative response, metabolic pathways, trans-synaptic signaling, and upregulation of genes involved in glutamate receptor signaling and complement activation, suggesting a potential role for these molecular pathways in de-coupling SOD1 aggregation from survival in Atp1a2 ASO-treated mice. Together, these results reveal a role for α2-Na+/K+-ATPase in SOD1 aggregation and highlight the critical effect of temporal modulation of genetically validated therapeutic targets in neurodegenerative diseases., Competing Interests: T.M.M has the following disclosures: Ionis Pharmaceutical, licensing agreement and consulting; C2N, licensing agreement; Biogen, advisory board and clinical studies support, Disarm Therapeutics, consulting; Cytokinetics, consulting, UCB, advisory board. A.B. is a full-time employee and shareholder of F. Hoffmann-La Roche Ltd. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Iyer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction/aims: Analysis of biofluids, especially cerebrospinal fluid (CSF), is critically important for amyotrophic lateral sclerosis (ALS) research. Collection of CSF is typically performed by lumbar puncture (LP). Previous studies have demonstrated the safety of LPs in patients with other neurodegenerative diseases, such as Alzheimer's disease, although there are no published studies of the safety of LPs in patients with ALS. We performed a retrospective analysis of complications resulting from LPs., Methods: This is a retrospective study of LPs performed between 2015 and 2021 on a total of 233 participants (healthy controls [n = 63], ALS [n = 154], and disease controls [n = 16]) as part of clinical research studies at the Washington University ALS Center. We used bivariate logistical analyses looking for associations between participant characteristics and adverse events (AEs), and likelihood ratio tests were used for significance testing., Results: We found an overall AE rate of 21.03%. AEs included headache, back pain, vasovagal syncope, and severe headache requiring epidural blood patch. Participants with ALS were not more likely to experience post-LP AEs compared to controls (odds ratio [OR] 0.61 [0.32-1.18]). Post-LP headaches were significantly less likely in participants with ALS (OR 0.36 [0.15-0.83])., Discussion: Our findings demonstrate that LP is a safe procedure for participants with ALS, with a similar or lower rate of AEs than in participants without ALS., (© 2023 The Authors. Muscle & Nerve published by Wiley Periodicals LLC.)

Exploring the tumour microenvironment provides insight into the unique interaction between the host and tumour. Ultimately, its study improves understanding of how an individual mounts and achieves an anti-tumour immune response. In the context of colorectal cancer, immune biomarkers within the tumour microenvironment outperform traditional histopathological staging in predicting disease recurrence. Multiplex immunofluorescence enables simultaneous assessment of multiple markers to provide a highly accurate classification of immune cells and their spatial characterisation relative to tumour tissue. Further, automated slide staining provides staining consistency and reduces labour costs. Image acquisition using a non-spectral scanner allows more researchers to utilise multiplexed immunofluorescence for translational research. Herein we describe the optimisation process of conducting automated staining using a five-colour, tyramide signal amplification-based multiplex immunofluorescence panel. Using antibodies against CD3, CD8, CD103 and cytokeratin, the panel characterises T cell populations within human colorectal adenocarcinoma tissue. We provide an overview of primary antibody titration and the development of tyramide signal amplification immunofluorescence monoplex assays. We detail the processes of antibody stripping and the role of exogenous horseradish peroxidase inhibition to facilitate multiplexing. An account of determining the staining sequence and fluorophore assignment is provided. We describe image acquisition using a standard fluorescence microscope slide scanner and the management of spectral crosstalk using this system. Finally, we briefly document the digital image analysis required to characterise cells and determine their spatial distribution within the colorectal tumour microenvironment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Peri-procedural blood loss and hemodilution occur in patients undergoing mechanical thrombectomy (MT) for ischemic stroke; however, its relationships with thrombectomy passes, procedure times, and clinical outcomes are unknown., Methods: Consecutive patients undergoing MT for anterior circulation large-vessel occlusion ischemic strokes were identified at a Comprehensive Stroke Center. Clinical information, modified treatment in cerebral ischemia (mTICI) scores, and modified Rankin Scores (mRS) at 90 days were prospectively collected from 2012 to 2021. Hemoglobin measurements before and after MTs were collected retrospectively via chart review, and changes were quantified. Patients with new-onset severe anemia (defined as post-MT hemoglobin less than 10g/dL) were identified. Modified Rankin scale (mRS) at 90 days was used to measure clinical outcomes., Results: Four-hundred and forty-five patients were identified. Hemoglobin decreased 1.27 ± 1.05 g/dL after MT on average. Greater number of thrombectomy passes and longer procedure times were associated with larger decreases in hemoglobin ( p  < 0.001 and p  = 0.002, respectively). 11.5% (51 of 445) of patients had new-onset severe anemia, and this incidence was significantly higher with more thrombectomy passes (6.4% for one pass, 11.9% for two passes, and 17.4% for three or more passes; p  = 0.010). In multivariable analyses, new-onset severe anemia was associated with significantly higher odds of 90-day poor outcomes (mRS 3-6, OR 2.70 [95%CI 1.12-6.51], p  = 0.027) and death (OR 2.73 [95%CI 1.06-7.04], p  = 0.037) compared to mild post-MT anemia., Conclusions: More thrombectomy passes and longer procedure times were significantly associated with larger peri-procedural decreases in hemoglobin. Patients with new-onset hemoglobin less than 10 g/dL are at risk of poor outcomes., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Elevated International Normalized Ratio (INR) is a marker of coagulopathy, but its impact on outcomes following mechanical thrombectomy (MT) in patients with stroke is unclear. This study investigates the impact of mild INR elevations on clinical outcomes following MT., Methods: In this retrospective cohort study, consecutive patients with stroke treated with MT were identified from 2015 to 2020 at a Comprehensive Stroke Center. Demographic information, past medical history, INR, National Institutes of Health Stroke Scale score, use of tissue plasminogen activator, and last known normal to arteriotomy time were recorded. Outcome measures included modified Thrombolysis in Cerebral Infarction (mTICI) score, modified Rankin Scale (mRS) score at 90 days, and intracerebral hemorrhage (ICH). Patients were divided into two groups: normal INR (0.8-1.1) and mildly elevated INR (1.2-1.7)., Results: A total of 489 patients were included for analysis, of which 349 had normal INR and 140 had mildly elevated INR. After multivariable adjustments, mildly elevated INR was associated with lower odds of excellent outcomes (mRS 0-1, OR 0.24, p=0.009), lower odds of functional independence (mRS 0-2, OR 0.38, p=0.038), and higher odds of 90-day mortality (OR 3.45, p=0.018). Elevated INR was not associated with a higher likelihood of ICH, and there were no differences in rates of HI1, HI2, PH1, or PH2 hemorrhagic transformations; however, elevated INR was associated with significantly higher odds of 90-day mortality in patients with ICH (OR 6.22, p=0.024). This effect size was larger than in patients without ICH (OR 3.38, p<0.001)., Conclusion: In patients with stroke treated with MT, mildly elevated INR is associated with worse clinical outcomes after recanalization and may worsen the mortality risk of hemorrhagic transformations., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: Real-world evidence for radiation therapy (RT) is limited because it is often documented only in the clinical narrative. We developed a natural language processing system for automated extraction of detailed RT events from text to support clinical phenotyping., Methods and Materials: A multi-institutional data set of 96 clinician notes, 129 North American Association of Central Cancer Registries cancer abstracts, and 270 RT prescriptions from HemOnc.org was used and divided into train, development, and test sets. Documents were annotated for RT events and associated properties: dose, fraction frequency, fraction number, date, treatment site, and boost. Named entity recognition models for properties were developed by fine-tuning BioClinicalBERT and RoBERTa transformer models. A multiclass RoBERTa-based relation extraction model was developed to link each dose mention with each property in the same event. Models were combined with symbolic rules to create a hybrid end-to-end pipeline for comprehensive RT event extraction., Results: Named entity recognition models were evaluated on the held-out test set with F1 results of 0.96, 0.88, 0.94, 0.88, 0.67, and 0.94 for dose, fraction frequency, fraction number, date, treatment site, and boost, respectively. The relation model achieved an average F1 of 0.86 when the input was gold-labeled entities. The end-to-end system F1 result was 0.81. The end-to-end system performed best on North American Association of Central Cancer Registries abstracts (average F1 0.90), which are mostly copy-paste content from clinician notes., Conclusions: We developed methods and a hybrid end-to-end system for RT event extraction, which is the first natural language processing system for this task. This system provides proof-of-concept for real-world RT data collection for research and is promising for the potential of natural language processing methods to support clinical care., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objective : To determine the target population and optimize the study design of the phase 3 clinical trial evaluating reldesemtiv in participants with amyotrophic lateral sclerosis (ALS). Methods : We evaluated the phase 2 study of reldesemtiv, FORTITUDE-ALS, to inform eligibility criteria and design features that would increase trial efficiency and reduce participant burden of the phase 3 trial. Results : In FORTITUDE-ALS, the effect of reldesemtiv was particularly evident among participants in the intermediate- and fast-progressing tertiles for pre-study disease progression. These participants most often had symptom onset ≤24 months and an ALS Functional Rating Scale-Revised (ALSFRS-R) total score ≤44 at baseline. Compared with the overall FORTITUDE-ALS population, the subgroup meeting these criteria declined by fewer ALSFRS-R points at 12 weeks (difference of least-squares mean [SE] versus placebo 1.84 [0.49] and 0.87 [0.35] for the overall population). These inclusion criteria will be used for the phase 3 clinical trial, COURAGE-ALS, in which the primary outcome is the change in ALSFRS-R total score at week 24. We also measure durable medical equipment use and evaluate strength in muscles expected to change rapidly. To reduce participant burden, study visits are often remote, and strength evaluation is simplified to reduce time and effort. Conclusions : In COURAGE-ALS, the phase 3 clinical trial to evaluate reldesemtiv , the sensitivity of detecting a potential treatment effect may be increased by defining eligibility criteria that limit the proportion of participants who have slower disease progression. Implementing remote visits and simplifying strength measurements will reduce both site and participant burden.ClinicalTrials.gov identifiers: NCT03160898 (FORTITUDE-ALS) and NCT04944784 (COURAGE-ALS).

Background: Opioid use has come under increasing scrutiny, driven in part by the opioid crisis and growing concerns that up to 6% of opioid-naïve patients may become chronic opioid users. This has resulted in a revaluation of perioperative practice. For this reason, we implemented a multidisciplinary pathway to reduce perioperative opioid usage through education and standardization of practice., Methods: A single-centre retrospective evaluation was performed after 1 year, comparing the outcomes to those of the 2 years prior to pathway implementation. Comparisons were made between pre- vs. post pathway change by 2:1 propensity matching between cohorts. Univariate linear regression models were created using demographic variables with those that were p < 0.15 included in the final model and using post-operative opioid use (in oral morphine equivalents, OME) as the primary outcome., Results: We found that intraoperative opioid use was significantly decreased 38.2 mg (28.3) vs. 18.0 mg (40.4) oral morphine equivalents (OME), p < .001, as was post-operative opioid use for the duration of the hospitalization, 46.3 mg (49.5) vs. 35.49 mg (43.7) OME, p = 0.002. In subgroup analysis of those that received some intraoperative opioids (n = 152) and those that received no opioids (n = 34), we found that both groups required fewer opioids in the post-operative period 47.0 mg (47.7) vs. 32.4 mg (40.6) OME, p = 0.001, + intraoperative opioids, 62.4 mg (62.9) vs. 35.8 mg (27.7) OME, p = 0.13, - intraoperative opioids. Time to discharge from the PACU was reduced in both groups 215 min (199) vs. 167 min (122), p < 0.003, + intraoperative opioids and 253 min (270) vs. 167 min (105), p = 0.028, - intraoperative opioids. The duration of time until meeting discharge criteria from PACU was 221 min (205) vs. 170 min (120), p = 0.001. Hospital length of stay (LOS) was significantly reduced 1.4 days (1.3) vs. 1.2 days (0.8), p = 0.005. Both sub-groups demonstrated reduced hospital LOS 1.5 days (1.4) vs. 1.2 days (0.8), p = 0.0047, + intraoperative opioids and 1.7 days (1.6) vs. 1.3 days (0.9), p = 0.0583, - intraoperative opioids. Average pain scores during PACU admission and post-PACU until discharge were not statistically different between cohorts., Conclusions: These findings underscore the effectiveness of a multidisciplinary approach to reduce opioids. Furthermore, it demonstrates improved patient outcomes as measured by both shorter PACU and almost 50% reduction in perioperative opioid use whilst maintaining similar analgesia as indicated by patient-reported pain scores., (© 2023. The Author(s).)

Amphiphilic glycoconjugates offer an important prospect for development as chemical biology tools and biosurfactants. The chemical synthesis of such materials is required to expedite such prospect, compounded by the example of oleyl glycosides. Herein, we report a mild and reliable glycosylation method to access oleyl glucosides, glycosidating oleyl alcohol with α-trichloroacetimidate donors. We demonstrate capability for this methodology, extending it to synthesise the first examples of pyranose-component fluorination and sulfhydryl modifications within glucosides and glucosamines of oleyl alcohol. These compounds provide an exciting series of tools to explore processes and materials that utilise oleyl glycosides, including as probes for glycosphingolipid metabolism., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: High levels of platelet inhibition have been associated with hemorrhagic complications following Pipeline embolization of intracranial aneurysms. We therefore titrate clopidogrel dosing to maintain a moderate level of platelet inhibition using the VerifyNow P2Y12 assay. However, many patients demonstrate dramatic increases in platelet inhibition following treatment despite being on a consistent antiplatelet regimen. We therefore elected to explore the incidence of this phenomenon and possible predisposing factors., Methods: All successful Pipeline aneurysm treatments performed at our institution from 2011 to 2019 with moderate procedure-day platelet inhibition levels as indicated by a VerifyNow PRU of 60-235 were included. Patients who received glycoprotein IIb/IIIa inhibitors and those treated for ruptured/symptomatic lesions were excluded. The incidence of excessive platelet inhibition defined by a PRU<60 within 8 weeks of treatment was noted. Multivariable logistic regression was performed to determined independent predictors of the phenomenon., Results: Some 190 treatments were performed in 178 qualifying patients. A post-procedure PRU <60 occurred following 79% of treatments, documented on average after 8.5 (range 1-47) days. A higher procedure day hematocrit level (P=0.003, OR 1.09, 95% CI 1.029 to 1.152) was an independent predictor of reaching a PRU <60, while intra-procedural midazolam exposure (P=0.044, OR 0.44, 95% CI 0.201 to 0.980) and a higher procedure-day PRU (P=0.047, OR 0.99, 95% CI 0.982 to 1.000) were associated with a reduced odds. Time-since-procedure and hematocrit levels were associated with excessive platelet inhibition when excluding patients who initially demonstrated hyperresponse., Conclusion: Elevations in platelet inhibition were frequently observed following flow diversion with Pipeline., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To identify a cohort of COVID-19 cases, including when evidence of virus positivity was only mentioned in the clinical text, not in structured laboratory data in the electronic health record (EHR)., Materials and Methods: Statistical classifiers were trained on feature representations derived from unstructured text in patient EHRs. We used a proxy dataset of patients with COVID-19 polymerase chain reaction (PCR) tests for training. We selected a model based on performance on our proxy dataset and applied it to instances without COVID-19 PCR tests. A physician reviewed a sample of these instances to validate the classifier., Results: On the test split of the proxy dataset, our best classifier obtained 0.56 F1, 0.6 precision, and 0.52 recall scores for SARS-CoV2 positive cases. In an expert validation, the classifier correctly identified 97.6% (81/84) as COVID-19 positive and 97.8% (91/93) as not SARS-CoV2 positive. The classifier labeled an additional 960 cases as not having SARS-CoV2 lab tests in hospital, and only 177 of those cases had the ICD-10 code for COVID-19., Discussion: Proxy dataset performance may be worse because these instances sometimes include discussion of pending lab tests. The most predictive features are meaningful and interpretable. The type of external test that was performed is rarely mentioned., Conclusion: COVID-19 cases that had testing done outside of the hospital can be reliably detected from the text in EHRs. Training on a proxy dataset was a suitable method for developing a highly performant classifier without labor-intensive labeling efforts., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Text in electronic health records is organized into sections, and classifying those sections into section categories is useful for downstream tasks. In this work, we attempt to improve the transferability of section classification models by combining the dataset-specific knowledge in supervised learning models with the world knowledge inside large language models (LLMs). Surprisingly, we find that zero-shot LLMs out-perform supervised BERT-based models applied to out-of-domain data. We also find that their strengths are synergistic, so that a simple ensemble technique leads to additional performance gains.

The BioNLP Workshop 2023 initiated the launch of a shared task on Problem List Summarization (ProbSum) in January 2023. The aim of this shared task is to attract future research efforts in building NLP models for real-world diagnostic decision support applications, where a system generating relevant and accurate diagnoses will augment the healthcare providers' decision-making process and improve the quality of care for patients. The goal for participants is to develop models that generated a list of diagnoses and problems using input from the daily care notes collected from the hospitalization of critically ill patients. Eight teams submitted their final systems to the shared task leaderboard. In this paper, we describe the tasks, datasets, evaluation metrics, and baseline systems. Additionally, the techniques and results of the evaluation of the different approaches tried by the participating teams are summarized.

Purpose: Radiotherapy (RT) toxicities can impair survival and quality of life, yet remain understudied. Real-world evidence holds potential to improve our understanding of toxicities, but toxicity information is often only in clinical notes. We developed natural language processing (NLP) models to identify the presence and severity of esophagitis from notes of patients treated with thoracic RT., Methods: Our corpus consisted of a gold-labeled data set of 1,524 clinical notes from 124 patients with lung cancer treated with RT, manually annotated for Common Terminology Criteria for Adverse Events (CTCAE) v5.0 esophagitis grade, and a silver-labeled data set of 2,420 notes from 1,832 patients from whom toxicity grades had been collected as structured data during clinical care. We fine-tuned statistical and pretrained Bidirectional Encoder Representations from Transformers-based models for three esophagitis classification tasks: task 1, no esophagitis versus grade 1-3; task 2, grade ≤1 versus >1; and task 3, no esophagitis versus grade 1 versus grade 2-3. Transferability was tested on 345 notes from patients with esophageal cancer undergoing RT., Results: Fine-tuning of PubMedBERT yielded the best performance. The best macro-F1 was 0.92, 0.82, and 0.74 for tasks 1, 2, and 3, respectively. Selecting the most informative note sections during fine-tuning improved macro-F1 by ≥2% for all tasks. Silver-labeled data improved the macro-F1 by ≥3% across all tasks. For the esophageal cancer notes, the best macro-F1 was 0.73, 0.74, and 0.65 for tasks 1, 2, and 3, respectively, without additional fine-tuning., Conclusion: To our knowledge, this is the first effort to automatically extract esophagitis toxicity severity according to CTCAE guidelines from clinical notes. This provides proof of concept for NLP-based automated detailed toxicity monitoring in expanded domains.

Understanding temporal relationships in text from electronic health records can be valuable for many important downstream clinical applications. Since Clinical TempEval 2017, there has been little work on end-to-end systems for temporal relation extraction, with most work focused on the setting where gold standard events and time expressions are given. In this work, we make use of a novel multi-headed attention mechanism on top of a pre-trained transformer encoder to allow the learning process to attend to multiple aspects of the contextualized embeddings. Our system achieves state of the art results on the THYME corpus by a wide margin, in both the in-domain and cross-domain settings.

Generative artificial intelligence (AI) is a promising direction for augmenting clinical diagnostic decision support and reducing diagnostic errors, a leading contributor to medical errors. To further the development of clinical AI systems, the Diagnostic Reasoning Benchmark (DR.BENCH) was introduced as a comprehensive generative AI framework, comprised of six tasks representing key components in clinical reasoning. We present a comparative analysis of in-domain versus out-of-domain language models as well as multi-task versus single task training with a focus on the problem summarization task in DR.BENCH (Gao et al., 2023). We demonstrate that a multi-task, clinically-trained language model outperforms its general domain counterpart by a large margin, establishing a new state-of-the-art performance, with a ROUGE-L score of 28.55. This research underscores the value of domain-specific training for optimizing clinical diagnostic reasoning tasks.