Survival Differences in Asian and Hispanic Patients With In-Hospital Cardiac Arrest.

Background: Although they are fast-growing populations in the United States, little is known about survival outcomes of Hispanic and Asian patients after in-hospital cardiac arrest.

Methods And Results: In Get With The Guidelines-Resuscitation, we identified Asian, Hispanic, and White adults with in-hospital cardiac arrest during 2005 to 2023. Using multivariable models, we compared rates of survival to discharge separately for Asian and Hispanic patients versus White patients, as well as rates of sustained return of spontaneous circulation for ≥20 minutes and favorable neurologic survival as secondary outcomes.

Interpreting Population Mean Treatment Effects in the Kansas City Cardiomyopathy Questionnaire: A Patient-Level Meta-Analysis.

Importance: The Kansas City Cardiomyopathy Questionnaire (KCCQ) is a commonly used outcome in heart failure trials. While comparing means between treatment groups improves statistical power, mean treatment effects do not necessarily reflect the clinical benefit experienced by individual patients.

Objective: To evaluate the association between mean KCCQ treatment effects and the proportions of patients experiencing clinically important improvements across a range of clinical trials and heart failure etiologies.

Walking time to nearest public automated external defibrillator for out-of-hospital cardiac arrest in a major U.S. city.

Background: How frequently out-of-hospital cardiac arrest (OHCA) occurs within a reasonable walking distance to the nearest public automated external defibrillator (AED) has not been well studied.

Methods: As Kansas City, Missouri has a comprehensive city-wide public AED registry, we identified adults with an OHCA in Kansas City during 2019-2022 in the Cardiac Arrest Registry to Enhance Survival. Using AED location data from the registry, we computed walking times between OHCAs and the nearest registered AED using the Haversine formula, a mapping algorithm to calculate walking distance in miles from one location to another.

Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification.

The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic health records (EHRs). However, clinically routine modalities such as imaging and diagnostic codes can be asynchronous and irregularly sampled over different time scales which are obstacles to longitudinal multimodal learning. In this work, we propose a transformer-based multimodal strategy to integrate repeat imaging with longitudinal clinical signatures from routinely collected EHRs for SPN classification.

AI Body Composition in Lung Cancer Screening: Added Value Beyond Lung Cancer Detection.

Background An artificial intelligence (AI) algorithm has been developed for fully automated body composition assessment of lung cancer screening noncontrast low-dose CT of the chest (LDCT) scans, but the utility of these measurements in disease risk prediction models has not been assessed. Purpose To evaluate the added value of CT-based AI-derived body composition measurements in risk prediction of lung cancer incidence, lung cancer death, cardiovascular disease (CVD) death, and all-cause mortality in the National Lung Screening Trial (NLST). Materials and Methods In this secondary analysis of the NLST, body composition measurements, including area and attenuation attributes of skeletal muscle and subcutaneous adipose tissue, were derived from baseline LDCT examinations by using a previously developed AI algorithm.

Stratification of Lung Cancer Risk with Thoracic Imaging Phenotypes.

In lung cancer screening, estimation of future lung cancer risk is usually guided by demographics and smoking status. The role of constitutional profiles of human body, a.k.

Body composition assessment with limited field-of-view computed tomography: A semantic image extension perspective.

Field-of-view (FOV) tissue truncation beyond the lungs is common in routine lung screening computed tomography (CT). This poses limitations for opportunistic CT-based body composition (BC) assessment as key anatomical structures are missing. Traditionally, extending the FOV of CT is considered as a CT reconstruction problem using limited data.

Extending the value of routine lung screening CT with quantitative body composition assessment.

Certain body composition phenotypes, like sarcopenia, are well established as predictive markers for post-surgery complications and overall survival of lung cancer patients. However, their association with incidental lung cancer risk in the screening population is still unclear. We study the feasibility of body composition analysis using chest low dose computed tomography (LDCT).

Intrinsic Evaluation of Contextual and Non-contextual Word Embeddings using Radiology Reports.

Many clinical natural language processing methods rely on non-contextual word embedding (NCWE) or contextual word embedding (CWE) models. Yet, few, if any, intrinsic evaluation benchmarks exist comparing embedding representations against clinician judgment. We developed intrinsic evaluation tasks for embedding models using a corpus of radiology reports: term pair similarity for NCWEs and cloze task accuracy for CWEs.

Cancer Risk Estimation Combining Lung Screening CT with Clinical Data Elements.

Purpose: To develop a model to estimate lung cancer risk using lung cancer screening CT and clinical data elements (CDEs) without manual reading efforts.

Materials And Methods: Two screening cohorts were retrospectively studied: the National Lung Screening Trial (NLST; participants enrolled between August 2002 and April 2004) and the Vanderbilt Lung Screening Program (VLSP; participants enrolled between 2015 and 2018). Fivefold cross-validation using the NLST dataset was used for initial development and assessment of the co-learning model using whole CT scans and CDEs.

Inference-based correction of multi-site height and weight measurement data in the All of Us research program.

Objective: Measurement and data entry of height and weight values are error prone. Aggregation of medical record data from multiple sites creates new challenges prompting the need to identify and correct errant values. We sought to characterize and correct issues with height and weight measurement values within the All of Us (AoU) Research Program.

Development and Characterization of a Chest CT Atlas.

A major goal of lung cancer screening is to identify individuals with particular phenotypes that are associated with high risk of cancer. Identifying relevant phenotypes is complicated by the variation in body position and body composition. In the brain, standardized coordinate systems (e.

Prevalence and associated risk factors of Shigella flexneri isolated from drinking water and retail raw foods in Peshawar, Pakistan.

This study was designed to investigate the prevalence and associated risk factors of Shigella flexneri isolated from drinking water and retail raw food samples in Peshawar, Pakistan. A total of 1,020 different samples were collected from various areas of Peshawar between January 2016 and May 2017, followed by identification of S. flexneri through biochemical, serological, and 16S rRNA gene sequencing.

Disseminated pulmonary histoplasmosis in immunocompetent patients: a common epidemiological exposure.

We describe the initial presentation, diagnostic work-up and treatment of three adult immunocompetent men who presented within a short time frame of each other to an academic medical centre with acute respiratory distress syndrome. Their presentation was found to be secondary to a large inoculum of histoplasmosis from remodelling a building with bat droppings infestation. We discuss the pathophysiology of histoplasmosis and highlight the importance of exposure history in patients with acute respiratory failure and why patients with the occupational risk of exposure to fungal inoculum should wear protective respirator gear.

Targeting epigenetics for treatment of BRAF mutated metastatic melanoma with decitabine in combination with vemurafenib: A phase lb study.

Introduction: Epigenetic modifications play an important role in progression and development of resistance in BRAF positive metastatic melanoma. Therefore, we hypothesized that the action of vemurafenib (BRAF inhibitor) can be made more effective by combining with low dose decitabine (a DNA methyltransferase inhibitor). The primary objective of this phase lb study was to determine the dose limiting toxicity and maximum tolerated dose of combination of subcutaneous decitabine with oral vemurafenib in patients with BRAF positive metastatic melanoma with or without any prior treatment.