Discharge process for patients experiencing homelessness in the emergency department: A thematic qualitative study.

People experiencing homelessness are more likely to utilize emergency departments than their non-homeless counterparts. However, obtaining a bed in a homeless shelter for patients can be complex. To better understand the challenges of finding a safe discharge plan for homeless patients in the emergency department, our team conducted interviews with emergency department social workers and homeless shelter case managers in the Boston area.

Effects of Low-Level Light Therapy on Resting-State Connectivity Following Moderate Traumatic Brain Injury: Secondary Analyses of a Double-blinded Placebo-controlled Study.

Background Low-level light therapy (LLLT) has been shown to modulate recovery in patients with traumatic brain injury (TBI). However, the impact of LLLT on the functional connectivity of the brain when at rest has not been well studied. Purpose To use functional MRI to assess the effect of LLLT on whole-brain resting-state functional connectivity (RSFC) in patients with moderate TBI at acute (within 1 week), subacute (2-3 weeks), and late-subacute (3 months) recovery phases.

Critical Care in the Austere Environment.

Practice of critical care in austere settings involves navigating rapidly evolving environments, where physical resources, provider availability, and healthcare capacity are constrained. Austere Critical Care focuses on maintaining the highest standard of care possible for patients while also identifying resource limitations, responding to patient surges, and adhering to proper triage practices at the austere site. This includes transferring the patient when able and necessary.

Biomedical text readability after hypernym substitution with fine-tuned large language models.

The advent of patient access to complex medical information online has highlighted the need for simplification of biomedical text to improve patient understanding and engagement in taking ownership of their health. However, comprehension of biomedical text remains a difficult task due to the need for domain-specific expertise. We aimed to study the simplification of biomedical text via large language models (LLMs) commonly used for general natural language processing tasks involve text comprehension, summarization, generation, and prediction of new text from prompts.

Impact of medical technologies may be predicted using constructed graph bibliometrics.

Scientific research is driven by allocation of funding to different research projects based in part on the predicted scientific impact of the work. Data-driven algorithms can inform decision-making of scarce funding resources by identifying likely high-impact studies using bibliometrics. Compared to standardized citation-based metrics alone, we utilize a machine learning pipeline that analyzes high-dimensional relationships among a range of bibliometric features to improve the accuracy of predicting high-impact research.

Hypotension During Vasopressor Infusion Occurs in Predictable Clusters: A Multicenter Analysis.

Published evidence indicates that mean arterial pressure (MAP) below a goal range (hypotension) is associated with worse outcomes, though MAP management failures are common. We sought to characterize hypotension occurrences in ICUs and consider the implications for MAP management. Retrospective analysis of 3 hospitals' cohorts of adult ICU patients during continuous vasopressor infusion.

Entropy removal of medical diagnostics.

Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in a systematic way to quantify the entropy of clinical situations using diagnostic variables (true and false positives and negatives, respectively). Decision tree representations of medical decision-making tools can be generated using diagnostic variables found in literature and entropy removal can be calculated for these tools.

The Certification Matters: A Comparative Performance Analysis of Combat Application Tourniquets versus Non-Certified CAT Look-Alike Tourniquets.

Introduction: The Stop the Bleed campaign provided civilians with tourniquet application training and increased the demand for tourniquets among the general population, which led to the development of new commercially available devices. However, most widely available tourniquets have not undergone testing by regulatory bodies and their efficacy remains unknown.

Study Objective: This study aimed to compare the efficacy and performance of Combat Application Tourniquets (CAT) versus uncertified tourniquets.

Predictors of Mortality in Extracorporeal Membrane Oxygenation Support Patients Following Major Trauma.

Introduction: The usage of extracorporeal membrane oxygenation (ECMO) in trauma patients has increased significantly within the past decade. Despite increased research on ECMO application in trauma patients, there remains limited data on factors predicting morbidity and mortality outcome. Therefore, the primary objective of this study is to describe patient characteristics that are independently associated with mortality in ECMO therapy in trauma patients, to further guide future research.

Circulating cellular clusters are associated with thrombotic complications and clinical outcomes in COVID-19.

We sought to study the role of circulating cellular clusters (CCC) -such as circulating leukocyte clusters (CLCs), platelet-leukocyte aggregates (PLA), and platelet-erythrocyte aggregates (PEA)- in the immunothrombotic state induced by COVID-19. Forty-six blood samples from 37 COVID-19 patients and 12 samples from healthy controls were analyzed with imaging flow cytometry. Patients with COVID-19 had significantly higher levels of PEAs (p value<0.

Network Analysis of Academic Medical Center Websites in the United States.

Healthcare resources are published annually in repositories such as the AHA Annual Survey Database. However, these data repositories are created via manual surveying techniques which are cumbersome in collection and not updated as frequently as website information of the respective hospital systems represented. Also, this resource is not widely available to patients in an easy-to-use format.

Influence of ICU Surge and Capacity on COVID Mortality Across U.S. States and Regions During the COVID-19 Pandemic.

Background: To describe the influence of COVID-19 caseload surges and overall capacity in the intensive care unit (ICU) on mortality among US population and census divisions.

Methods: A retrospective analysis of the national COVID ActNow database between January 1, 2021 until March 1, 2022. The main outcome used was COVID-19 weekly mortality rates, which were calculated and incorporated into several generalized estimation of effects models with predictor variables that included ICU bed capacity, as well as ICU capacity used by COVID cases while adjusting for ratios of vaccinations in populations, case density, and percentage of the population over the age of 65.

Emoji Education: How Students Can Help Increase Health Awareness by Making Emojis.

Emojis can improve health communication, especially when incorporating emojis into traditionally word-only texts. Beyond improving communication, emojis also offer greater access to health care, especially for vulnerable and marginalized populations with limited health literacy. A recent study found that 94% of patients with limited health literacy preferred health reports with emojis.

End-user evaluation of an interface for clinical decision support using predictive algorithms.

There have been decades of interest in advanced computational algorithms with potential for clinical decision support systems (CDSS), yet these have not been widely implemented in clinical practice. One major barrier to dissemination may be a user-friendly interface that integrates into clinical workflows. Complicated or non-intuitive displays may confuse users and may even increase patient management errors.

Looking back on forward-looking COVID models.

Covid Act Now (CAN) developed an epidemiological model that takes various non-pharmaceutical interventions (NPIs) into account and predicts viral spread and subsequent health outcomes. In this study, the projections of the model developed by CAN were back-tested against real-world data, and it was found that the model consistently overestimated hospitalizations and deaths by 25%-100% and 70%-170%, respectively, due in part to an underestimation of the efficacy of NPIs. Other COVID models were also back-tested against historical data, and it was found that all models generally captured the potential magnitude and directionality of the pandemic in the short term.

Comparison of an Emoji-Based Visual Analog Scale With a Numeric Rating Scale for Pain Assessment.

This study surveyed patients admitted to the emergency department or surgical units at a single hospital to compare an emoji-based pain scale with a conventional numeric rating scale.

Planning for the Next Pandemic: Trauma Injuries Require Pre-COVID-19 Levels of High-Intensity Resources.

As hospital systems plan for health care utilization surges and stress, understanding the necessary resources of a trauma system is essential for planning capacity. We aimed to describe trends in high-intensity resource utilization (operating room [OR] usage and intensive care unit [ICU] admissions) for trauma care during the initial months of the COVID-19 pandemic. Trauma registry data (2019 pre-COVID-19 and 2020 COVID-19) were collected retrospectively from 4 level I trauma centers.

Hospital Academic Status and the Volume-Outcome Association in Postoperative Patients Requiring Intensive Care: Results of a Nationwide Analysis of Intensive Care Units in the United States.

To determine whether the outcomes of postoperative patients admitted directly to an intensive care unit (ICU) differ based on the academic status of the institution and the total operative volume of the unit. This was a retrospective analysis using the eICU Collaborative Research Database v2.0, a national database from participating ICUs in the United States.