The social experience of uncertainty: a qualitative analysis of emergency department care for suspected pneumonia for the design of decision support.

Background: This study sought to understand the process of clinical decision-making for suspected pneumonia by emergency departments (ED) providers in Veterans Affairs (VA) Medical Centers. The long-term goal of this work is to create clinical decision support tools to reduce unwarranted variation in diagnosis and treatment of suspected pneumonia.

Methods: Semi-structured qualitative interviews were conducted with 16 ED clinicians from 9 VA facilities demonstrating variation in antibiotic and hospitalization decisions.

A Linguistic Analysis Examining the Impact of COVID-19 on Pneumonia Diagnosis and Disease Models.

Written clinical language embodies and reflects the clinician's mental models of disease. Prior to the COVID-19 pandemic, pneumonia was shifting away from concern for healthcare-associated pneumonia and toward recognition of heterogeneity of pathogens and host response. How these models are reflected in clinical language or whether they were impacted by the pandemic has not been studied.

Hospital admission decisions for older Veterans with community-onset pneumonia: An analysis of 118 U.S. Veterans Affairs Medical Centers.

Objectives: Age is important for prognosis in community-onset pneumonia, but how it influences admission decisions in the emergency department (ED) is not well characterized. Using clinical data from the electronic health record in a national cohort, we examined pneumonia hospitalization patterns, variation, and relationships with mortality among older versus younger Veterans.

Methods: In a retrospective cohort of patients ≥ 18 years presenting to EDs with a diagnosis of pneumonia at 118 VA Medical Centers January 1, 2006, to December 31, 2016, we compared observed, predicted, and residual hospitalization risk for Veterans < 70, 70-79, and ≥ 80 years of age using generalized estimating equations and machine learning models with 71 patient factors.

Development and evaluation of an interoperable natural language processing system for identifying pneumonia across clinical settings of care and institutions.

Objective: To evaluate the feasibility, accuracy, and interoperability of a natural language processing (NLP) system that extracts diagnostic assertions of pneumonia in different clinical notes and institutions.

Materials And Methods: A rule-based NLP system was designed to identify assertions of pneumonia in 3 types of clinical notes from electronic health records (EHRs): emergency department notes, radiology reports, and discharge summaries. The lexicon and classification logic were tailored for each note type.

Trends in Illness Severity, Hospitalization, and Mortality for Community-Onset Pneumonia at 118 US Veterans Affairs Medical Centers.

Background: Deaths from pneumonia were decreasing globally prior to the COVID-19 pandemic, but it is unclear whether this was due to changes in patient populations, illness severity, diagnosis, hospitalization thresholds, or treatment. Using clinical data from the electronic health record among a national cohort of patients initially diagnosed with pneumonia, we examined temporal trends in severity of illness, hospitalization, and short- and long-term deaths.

Design: Retrospective cohort PARTICIPANTS: All patients >18 years presenting to emergency departments (EDs) at 118 VA Medical Centers between 1/1/2006 and 12/31/2016 with an initial clinical diagnosis of pneumonia and confirmed by chest imaging report.

Computerized Mortality Prediction for Community-acquired Pneumonia at 117 Veterans Affairs Medical Centers.

Computerized severity assessment for community-acquired pneumonia could improve consistency and reduce clinician burden. To develop and compare 30-day mortality-prediction models using electronic health record data, including a computerized score with all variables from the original Pneumonia Severity Index (PSI) except confusion and pleural effusion ("ePSI score") versus models with additional variables. Among adults with community-acquired pneumonia presenting to emergency departments at 117 Veterans Affairs Medical Centers between January 1, 2006, and December 31, 2016, we compared an ePSI score with 10 novel models employing logistic regression, spline, and machine learning methods using PSI variables, age, sex and 26 physiologic variables as well as all 69 PSI variables.

Abdominal aortic aneurysm with inferior vena cava compression in association with deep venous thrombosis.

Deep venous thrombosis (DVT) of the lower extremity may be caused by external compression of the inferior vena cava (IVC) by a neighboring mass. A 55-year-old male presented with 8 months of intermittent left lower extremity swelling and signs of chronic venous stasis. Duplex ultrasound showed extensive DVT in the left leg.

Voltage-gated potassium channel KCNV2 (Kv8.2) contributes to epilepsy susceptibility.

Mutations in voltage-gated ion channels are responsible for several types of epilepsy. Genetic epilepsies often exhibit variable severity in individuals with the same mutation, which may be due to variation in genetic modifiers. The Scn2a(Q54) transgenic mouse model has a sodium channel mutation and exhibits epilepsy with strain-dependent severity.

Fine mapping of an epilepsy modifier gene on mouse Chromosome 19.

Mutations in voltage-gated sodium channels are associated with several types of human epilepsy. Variable expressivity and penetrance are common features of inherited epilepsy caused by sodium channel mutations, suggesting that genetic modifiers may influence clinical severity. The mouse model Scn2a(Q54) has an epilepsy phenotype due to a mutation in Scn2a that results in elevated persistent sodium current.