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Human Anatomy and Physiology courses are "gateway" courses that students must pass with high grades in order to proceed through their program of study. However, student pass rates are often low, resulting in students attempting the course multiple times and delaying their graduation. Supplemental instruction performed by peer leaders is one mechanism that has been used to increase student success. The goal of this study was to evaluate the effectiveness of peer-led supplemental instruction by comparing predicted and actual course grades. We learned that students predicted to earn a C achieved higher grades when they utilized supplemental instruction. While those students performed better than predicted, supplemental instruction did not improve ABC rates for the class. We conclude that supplemental instruction can be of benefit for some students.

This paper aims to further explore the impact of need and culture as they relate to orientation, training, development, and administrative policies on regional university adjunct faculty. The use of adjunct faculty has risen considerably over recent years making their university experience more relevant in today's higher education climate. Adjunct faculty express the desire for orientation, training, and professional development. In addition, adjunct faculty find administrative policies extremely isolating in nature as they struggle to develop more meaningful relationships with other faculty, administrators, and students. While adjunct faculty have vast industry experience, they often lack extensive experience in higher education. Considering that adjunct faculty have such a tremendous impact on college students, how they feel about their higher education experience is of great concern. Adjunct faculty effectiveness suffers when they do not receive adequate orientation, training, and development. When adjunct faculty are isolated from the university due to the structure of administrative policy, they become less committed to the overarching goals of the organization and thus less committed to students.

Beginning in the summer of 2019, the College of St. Scholastica endeavored to build a flexible, adaptable EdD program grounded in the guiding principles of CPED. This meant establishing a welcoming and safe program dedicated to cultivating justice-minded change makers. It also meant constructing a curriculum that would accommodate differing student backgrounds, be responsive to fluctuating consumer demands, and function as context-inclusive in an ever-evolving and intersecting space. While this alone was certainly a challenge, we did not anticipate that a global pandemic would present the most significant test of what we had created. To accomplish the aforementioned goals, the program architecture was dependent on the following structural considerations: a broadening of the target participant profile to include students across various social sectors; the use of design thinking as an asset in supporting innovation, creativity and flexibility; the inclusion of credit-bearing "third-place" courses intended to provide open-ended space and place for community building and reflective, intentional action; and an approach to course design that encouraged risk-taking by students with a focus on cultivating mindsets and skills around equity and social justice. None of these attributes on their own provided total protection from seismic societal, cultural or market shifts. Collectively, however, they offered a unique environment for the culturing of a particular type of doctoral experience, unique in its elasticity compared to more traditional, inflexible designs. This essay details the ways in which we attempted to create an inclusive, innovative, flexible structure, as validated (and challenged) by the COVID-19 pandemic.

ImportanceMost research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.ObjectiveTo identify the most common prolonged symptoms experienced by children (aged 6 to 17 years) after SARS-CoV-2 infection, how these symptoms differ by age (school-age [6-11 years] vs adolescents [12-17 years]), how they cluster into distinct phenotypes, and what symptoms in combination could be used as an empirically derived index to assist researchers to study the likely presence of PASC.Design, setting, and participantsMulticenter longitudinal observational cohort study with participants recruited from more than 60 US health care and community settings between March 2022 and December 2023, including school-age children and adolescents with and without SARS-CoV-2 infection history.ExposureSARS-CoV-2 infection.Main outcomes and measuresPASC and 89 prolonged symptoms across 9 symptom domains.ResultsA total of 898 school-age children (751 with previous SARS-CoV-2 infection [referred to as infected] and 147 without [referred to as uninfected]; mean age, 8.6 years; 49% female; 11% were Black or African American, 34% were Hispanic, Latino, or Spanish, and 60% were White) and 4469 adolescents (3109 infected and 1360 uninfected; mean age, 14.8 years; 48% female; 13% were Black or African American, 21% were Hispanic, Latino, or Spanish, and 73% were White) were included. Median time between first infection and symptom survey was 506 days for school-age children and 556 days for adolescents. In models adjusted for sex and race and ethnicity, 14 symptoms in both school-age children and adolescents were more common in those with SARS-CoV-2 infection history compared with those without infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. These symptoms affected almost every organ system. Combinations of symptoms most associated with infection history were identified to form a PASC research index for each age group; these indices correlated with poorer overall health and quality of life. The index emphasizes neurocognitive, pain, and gastrointestinal symptoms in school-age children but change or loss in smell or taste, pain, and fatigue/malaise-related symptoms in adolescents. Clustering analyses identified 4 PASC symptom phenotypes in school-age children and 3 in adolescents.Conclusions and relevanceThis study developed research indices for characterizing PASC in children and adolescents. Symptom patterns were similar but distinguishable between the 2 groups, highlighting the importance of characterizing PASC separately for these age ranges.

Contribution: This study aimed to improve understanding of context-based affordances and barriers to adoption of evidence-based instructional practices (EBIPs) among faculty in electrical and computer engineering (ECE). Context-based influences, including motives, constraints, and feedback mechanisms impacting EBIP adoption across six ECE faculty participants were documented using qualitative analysis. Background: Recent engineering education literature notes that the adoption of EBIPs by engineering faculty is lagging despite increased faculty awareness of EBIPs, belief in their effectiveness, and interest in integrating them. While researchers continue to investigate barriers to faculty adoption of EBIPs in science, technology, engineering, and mathematics education settings, few studies have dedicated examinations within a specific disciplinary context, particularly among ECE faculty members. Research Question: What context-based barriers and affordances influence adoption of EBIPs by ECE faculty members? Methodology: This study qualitatively analyzed data from in-depth interviews with six ECE faculty members from engineering programs throughout the United States. The study applied an iterative combination of case study and thematic analysis techniques to identify context-relevant and unique factors relevant to each individual participant and synthesize the process of decision making when incorporating EBIPs using a systems perspective. Findings: Overall, the approach identified drivers, constraints, and feedback mechanisms in regard to four emergent categories of EBIP adoption cases: (1) no use; (2) discontinued use; (3) in development; and (4) continued use. The study reports examples of context-based influences among the six participants in relation to their level of EBIP adoption, highlighting the substantial variation in faculty experiences with incorporating EBIPs.

As most academic libraries closed in March 2020 to help slow the spread of COVID-19, practitioners started working from home for the first time. After observing impacts on their own work, the authors sought to study the broader effects of remote work on practitioners' professional and personal life by conducting a longitudinal study between July 2020 and June 2021. The authors identified successful and unsuccessful practices and, based on this data, developed recommendations for how employers can support their employees as whole persons to ensure more productive professional performance and healthier personal lives.

This case examines the complex partnership between the university teacher education program and the host school district. Many factors contribute to the expectations and requirements of both institutions, which can at times, conflict in fundamental ways. The theoretical and research-based methods of early childhood coursework are often different than the reality of those classrooms. Furthermore, the adoption of initiatives like, Culturally Responsive Teaching and Leading standards by university teacher education programs must translate to the fieldwork. School and district-wide mandates often overrule best pedagogical and developmentally appropriate practices. With these opposing perspectives how can supervisors bridge the gap between the university classroom and the primary classroom? How can supervisors support teacher candidates and mentor teachers in negotiating rigid curricular programming, and maintain professional partnerships?

BackgroundPrescribing cascades are important contributors to polypharmacy. Little is known about which older adults are at highest risk of experiencing prescribing cascades. We explored which older veterans are at highest risk of the gabapentinoid (including gabapentin and pregabalin)-loop diuretic (LD) cascade, given the dramatic increase in gabapentinoid prescribing in recent years.MethodsUsing Veterans Affairs and Medicare claims data (2010-2019), we performed a prescription sequence symmetry analysis (PSSA) to assess loop diuretic initiation before and after gabapentinoid initiation among older veterans (≥66 years). To identify the cascade, we calculated the adjusted sequence ratio (aSR), which assesses the temporality of LD relative to gabapentinoid initiation. To explore high-risk groups, we used multivariable logistic regression with prescribing order modeled as a binary dependent variable. We calculated adjusted odds ratios (aORs), measuring the extent to which factors are associated with one prescribing order versus another.ResultsOf 151,442 veterans who initiated a gabapentinoid, there were 1,981 patients who initiated a LD within 6 months after initiating a gabapentinoid compared to 1,599 patients who initiated a LD within 6 months before initiating a gabapentinoid. In the gabapentinoid-LD group, the mean age was 73 years, 98% were male, 13% were Black, 5% were Hispanic, and 80% were White. Patients in each group were similar across patient and health utilization factors (standardized mean difference

BackgroundWe examined the association between cannabis use and cardiovascular outcomes among the general population, among never-tobacco smokers, and among younger individuals.Methods and resultsThis is a population-based, cross-sectional study of 2016 to 2020 data from the Behavioral Risk Factor Surveillance Survey from 27 American states and 2 territories. We assessed the association of cannabis use (number of days of cannabis use in the past 30 days) with self-reported cardiovascular outcomes (coronary heart disease, myocardial infarction, stroke, and a composite measure of all 3) in multivariable regression models, adjusting for tobacco use and other characteristics in adults 18 to 74 years old. We repeated this analysis among nontobacco smokers, and among men

All-cause COVID-19 hospitalization ≤ 30 days of infection is a common outcome for severe illness in observational/surveillance studies. Milder COVID-19 disease and COVID-19-specific measurements calls for an evaluation of this endpoint. This was a descriptive, retrospective cohort study of adults ≥ 18 who were established in primary care at Veteran Health Administration (VHA) facilities. The outcome was hospitalization within 30 days of a laboratory-confirmed, symptomatic SARS-CoV-2 infection. Between December 15, 2021 and May 1, 2022, a simple random sample of all VA facilities, excluding Puerto Rico or Philippines, was drawn to identify these hospitalized cases and determine whether hospitalization was due to COVID-19-specific causes. A chart review was conducted to record the inpatient clinical team's diagnosis and whether the inpatient team classified the diagnosis as COVID-19 related or not. These data were used to classify hospitalizations as either due to COVID-19-specific causes (direct manifestations of SARS-CoV-2 infection) or non-COVID-19-specific hospitalizations (incidental SARS-CoV-2 infection), A simple random sample of 9966 (12.3%) all-cause hospitalizations (95% CI: 12.1%, 12.5%) was used to select 300 representative patients. Of these, 226/300 (75.3%) were determined to be COVID-19-specific. COVID-19 pneumonia was most common (147/226, 65.0%). The highest proportion of COVID-19-specific hospitalizations occurred among unvaccinated (85.0%), followed by vaccinated but not boosted (73.7%) and boosted (59.4%) (p

Artificial intelligence in the workplace is becoming increasingly common. These tools are sometimes used to aid users in performing their task, for example, when an artificial intelligence tool assists a radiologist in their search for abnormalities in radiographic images. The use of artificial intelligence brings a wealth of benefits, such as increasing the efficiency and efficacy of performance. However, little research has been conducted to determine how the use of artificial intelligence assistants might affect the user's cognitive skills. In this theoretical perspective, we discuss how artificial intelligence assistants might accelerate skill decay among experts and hinder skill acquisition among learners. Further, we discuss how AI assistants might also prevent experts and learners from recognizing these deleterious effects. We then discuss the types of questions: use-inspired basic cognitive researchers, applied researchers, and computer science researchers should seek to answer. We conclude that multidisciplinary research from use-inspired basic cognitive research, domain-specific applied research, and technical research (e.g., human factors research, computer science research) is needed to (a) understand these potential consequences, (b) design artificial intelligence systems to mitigate these impacts, and (c) develop training and use protocols to prevent negative impacts on users' cognitive skills. Only by answering these questions from multidisciplinary perspectives can we harness the benefits of artificial intelligence in the workplace while preventing negative impacts on users' cognitive skills.

Influenza A viruses (IAV) of avian and swine origin have caused 5 pandemics in the previous 2 centuries (1). Aquatic avian populations, the primary reservoir for IAV, harbor numerous virus [...]

Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer and presents clinically with a high degree of biological heterogeneity and distinct clinical outcomes. The current paradigm of LUAD etiology posits alveolar epithelial type II (AT2) cells as the primary cell of origin, while the role of AT1 cells in LUAD oncogenesis remains unknown. Here, we examine oncogenic transformation in mouse Gram-domain containing 2 (Gramd2)+ AT1 cells via oncogenic KRASG12D. Activation of KRASG12D in AT1 cells induces multifocal LUAD, primarily of papillary histology. Furthermore, KRT8+ intermediate cell states were observed in both AT2- and AT1-derived LUAD, but SCGB3A2+, another intermediate cell marker, was primarily associated with AT1 cells, suggesting different mechanisms of tumor evolution. Collectively, our study reveals that Gramd2+ AT1 cells can serve as a cell of origin for LUAD and suggests that distinct subtypes of LUAD based on cell of origin be considered in the development of therapeutics.

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Abstract Background In recent studies, receipt of chiropractic care has been associated with lower odds of receiving prescription opioids and, among those already prescribed, reduced doses of opioids among patients with non-cancer spine pain. These findings suggest that access to chiropractic services may reduce reliance on opioids for musculoskeletal pain. Objective To assess the impact of chiropractic care on initiation, or continued use, of prescription opioids among patients with non-cancer spine pain. Methods We will search for eligible randomized controlled trials (RCTs) and observational studies indexed in MEDLINE, Embase, AMED, CINAHL, Web of Science, and the Index to Chiropractic Literature from database inception to June 2024. Article screening, data extraction, and risk-of-bias assessment will be conducted independently by pairs of reviewers. We will conduct separate analyses for RCTs and observational studies and pool binary outcomes (e.g. prescribed opioid receipt, long-term opioid use, and higher versus lower opioid dose) as odds ratios (ORs) with associated 95% confidence intervals (CIs). When studies provide hazard ratios (HRs) or relative risks (RRs) for time-to-event data (e.g. time-to-first opioid prescription) or incidence rates (number of opioid prescriptions over time), we will first convert them to an OR before pooling. Continuous outcomes such as pain intensity, sleep quality, or morphine equivalent dose will be pooled as weighted mean differences with associated 95% CIs. We will conduct meta-analyses using random-effects models and explore sources of heterogeneity using subgroup analyses and meta-regression. We will evaluate the certainty of evidence of all outcomes using the GRADE approach and the credibility of all subgroup effects with ICEMAN criteria. Our systematic review will follow the PRISMA statement and MOOSE guidelines. Discussion Our review will establish the current evidence informing the impact of chiropractic care on new or continued prescription opioid use for non-cancer spine pain. We will disseminate our results through peer-reviewed publication and conference presentations. The findings of our review will be of interest to patients, health care providers, and policy-makers. Trial registration Systematic review registration: PROSPERO CRD42023432277.

Background: Throughout the SARS-CoV-2 pandemic, policymakers have had to navigate between recommending voluntary behaviour change and policy-driven behaviour change to mitigate the impact of the virus. While individuals will voluntarily engage in self-protective behaviour when there is an increasing infectious disease risk, the extent to which this occurs and its impact on an epidemic is not known. Methods: This paper describes a deterministic disease transmission model exploring the impact of individual avoidance behaviour and policy-mediated avoidance behaviour on epidemic outcomes during the second wave of SARS-CoV-2 infections in Ontario, Canada (September 1, 2020 to February 28, 2021). The model incorporates an information feedback function based on empirically derived behaviour data describing the degree to which avoidance behaviour changed in response to the number of new daily cases COVID-19. Results: Voluntary avoidance behaviour alone was estimated to reduce the final attack rate by 23.1%, the total number of hospitalizations by 26.2%, and cumulative deaths by 27.5% over 6 months compared to a counterfactual scenario in which there were no interventions or avoidance behaviour. A provincial shutdown order issued on December 26, 2020 was estimated to reduce the final attack rate by 66.7%, the total number of hospitalizations by 66.8%, and the total number of deaths by 67.2% compared to the counterfactual scenario. Conclusion: Given the dynamics of SARS-CoV-2 in a pre-vaccine era, individual avoidance behaviour in the absence of government action would have resulted in a moderate reduction in disease however, it would not have been sufficient to entirely mitigate transmission and the associated risk to the population in Ontario. Government action during the second wave of the COVID-19 pandemic in Ontario reduced infections, protected hospital capacity, and saved lives.

Background: Frailty, rather than age, is associated with postoperative morbidity and mortality. We sought to determine whether preoperative frailty as defined by a novel scoring system could predict the outcomes among older patients undergoing esophagectomy. Methods: We identified patients 65 years or older who underwent esophagectomy between 2011 and 2021 at our institution. Frailty was assessed using the MSK-FI, which consists of 1 component related to functional status and 10 medical comorbidities. We used a multivariable logistic regression model to test for the associations between frailty and short-term outcomes, with continuous frailty score as the predictor and additionally adjusted for age and Eastern Cooperative Oncology Group performance status. Results: In total, 447 patients were included in the analysis (median age of 71 years [interquartile range, 68–75]). Most of the patients underwent neoadjuvant treatment (81%), an Ivor Lewis esophagectomy (86%), and minimally invasive surgery (55%). A total of 22 patients (4.9%) died within 90 days of surgery, 144 (32%) had a major complication, 81 (19%) were readmitted, and 31 (7.2%) were discharged to a facility. Of the patients who died within 90 days, 19 had a major complication, yielding a failure-to-rescue rate of 13%. The risk of 30-day major complications (OR, 1.24 [95% CI, 1.09–1.41]; p = 0.001), readmissions (OR, 1.31 [95% CI, 1.13–1.52]; p < 0.001), and discharge to a facility (OR, 1.86 [95% CI, 1.49–2.37]; p < 0.001) increased with increasing frailty. Frailty and 90-day mortality were not associated. Conclusions: Frailty assessment during surgery decision-making can identify patients with a high risk of morbidity.

Abstract The Iowa State University Veterinary Diagnostic Laboratory detected nineteen human-to-swine reverse zoonoses of the 2022–2023 human seasonal H3N2 between November 2022 and November 2023. Cases from seven U.S. locations were detected: 3 Colorado, 1 Illinois, 1 Indiana, 2 Missouri, 7 North Carolina, 1 Ohio, and 1 Pennsylvania. One additional case was detected in Mexico and two cases were identified from Chile. Case samples were comprised of 4 nasal swabs and 15 oral fluids. Virus was successfully isolated from two of four nasal swab samples, but isolation from oral fluids was unsuccessful. The swine detections of H3 human viruses were classified to one of two human-seasonal H3 clades, 3C.2a1b.2a.2b and 3C.2a1b.2a.2a.1. Phylogenetic inference indicated at minimum 7 reverse zoonotic events occurred, with possible swine-to-swine transmission following the initial spillover. Twelve neuraminidase genes were sequenced, and nine were classified as human-seasonal H3N2 lineage: the remaining were endemic swine IAV NA genes from the N2.2002B, N2.1998, or the N1.Classical lineage, suggesting reassortment. The two viral isolates obtained from nasal swab samples were sequenced and were entirely human-lineage viruses. Seven swine samples with human seasonal H3 were sequenced and revealed co-detections with H1 1A.3.3.3 (gamma), with internal gene segments from both the triple reassortant internal gene (TRIG) and pandemic 2009 lineages. Serologic investigation of samples from swine production systems provided evidence for infection with human seasonal H3N2. One farm in the United States and four farms in Mexico had concurrent virologic evidence. The swine-isolated 3C.2a1b.2a.2b H3N2 was antigenically distinct from endemic 1990.4.A, 2010.1, and 2010.2 swine H3N2 lineages, but retained antigenic similarity to a recent human seasonal H3N2 (A/Darwin/6/2021). Pigs experimentally inoculated with a representative isolate demonstrated replication in the nose and lungs and minimal to mild macroscopic and microscopic lung lesions, but primary pigs did not transmit the virus to indirect contacts. If sustained in the pig population, this human seasonal H3 would represent the first new lineage detected in pigs the 2020 decade and present an emerging threat to swine health and production.

Abstract Sequence-based genetic testing identifies causative variants in ~ 50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. We interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 582 individuals with genetically unsolved DEEs. We identify rare differentially methylated regions (DMRs) and explanatory episignatures to uncover causative and candidate genetic etiologies in 12 individuals. Using long-read sequencing, we identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and four copy number variants. We also identify pathogenic variants associated with episignatures. Finally, we refine the CHD2 episignature using an 850 K methylation array and bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate variants as 2% (12/582) for unsolved DEE cases.

Abstract Artificial intelligence in the workplace is becoming increasingly common. These tools are sometimes used to aid users in performing their task, for example, when an artificial intelligence tool assists a radiologist in their search for abnormalities in radiographic images. The use of artificial intelligence brings a wealth of benefits, such as increasing the efficiency and efficacy of performance. However, little research has been conducted to determine how the use of artificial intelligence assistants might affect the user’s cognitive skills. In this theoretical perspective, we discuss how artificial intelligence assistants might accelerate skill decay among experts and hinder skill acquisition among learners. Further, we discuss how AI assistants might also prevent experts and learners from recognizing these deleterious effects. We then discuss the types of questions: use-inspired basic cognitive researchers, applied researchers, and computer science researchers should seek to answer. We conclude that multidisciplinary research from use-inspired basic cognitive research, domain-specific applied research, and technical research (e.g., human factors research, computer science research) is needed to (a) understand these potential consequences, (b) design artificial intelligence systems to mitigate these impacts, and (c) develop training and use protocols to prevent negative impacts on users’ cognitive skills. Only by answering these questions from multidisciplinary perspectives can we harness the benefits of artificial intelligence in the workplace while preventing negative impacts on users’ cognitive skills.

Patients from historically under-represented racial and ethnic groups are enrolled in cancer clinical trials at disproportionately low rates in the USA1-3. As these patients often have limited English proficiency4-7, we hypothesized that one barrier to their inclusion is the cost to investigators of translating consent documents. To test this hypothesis, we evaluated more than 12,000 consent events at a large cancer centre and assessed whether patients requiring translated consent documents would sign consent documents less frequently in studies lacking industry sponsorship (for which the principal investigator pays the translation costs) than for industry-sponsored studies (for which the translation costs are covered by the sponsor). Here we show that the proportion of consent events for patients with limited English proficiency in studies not sponsored by industry was approximately half of that seen in industry-sponsored studies. We also show that among those signing consent documents, the proportion of consent documents translated into the patient's primary language in studies without industry sponsorship was approximately half of that seen in industry-sponsored studies. The results suggest that the cost of consent document translation in trials not sponsored by industry could be a potentially modifiable barrier to the inclusion of patients with limited English proficiency.

Objective: To assemble and characterize an electronic health record (EHR) dataset for a large cohort of US military Veterans diagnosed with ALS (Amyotrophic Lateral Sclerosis). Methods: An EHR dataset for 19,662 Veterans diagnosed with ALS between January 1, 2000 to December 31, 2020 was compiled from the Veterans Health Administration (VHA) EHR database by a query for ICD9 diagnosis (335.20) or ICD10 diagnosis (G12.21) for Amyotrophic Lateral Sclerosis. Results: The cohort is predominantly male (98.94%) and white (72.37%) with a median age at disease onset of 68 years and median survival from the date of diagnosis of 590 days. With the designation of ALS as a compensable illness in 2009, there was a subsequent increase in the number of Veterans diagnosed per year in the VHA, but no change in median survival. The cohort included a greater-than-expected proportion of individuals whose branch of service at the time of separation was the Army. Conclusions: The composition of the cohort reflects the VHA population who are at greatest risk for ALS. The greater than expected proportion of individuals whose branch of service at the time of separation was the Army suggests the possibility of a branch-specific risk factor for ALS.