Search

Fire facilitates erosion through changes in vegetation and soil, with major postfire erosion commonly occurring even with moderate rainfall. As climate warms, the western United States (U.S.) is experiencing an intensifying fire regime and increasing frequency of extreme rain. We evaluated whether these hydroclimatic changes are evident in patterns of postfire erosion by modeling hillslope erosion following all wildfires larger than 100 km2 in California from 1984 to 2021. Our results show that annual statewide postfire hillslope erosion has increased significantly over time. To supplement the hillslope erosion modeling, we compiled modeled and measured postfire debris‐flow volumes. We find that, in northern California, more than 50% of fires triggering the top 20 values of sediment mass and sediment yield occurred in the most recent decade (between 2011 and 2021). In southern California, the postfire sediment budget was dominated by debris flows, which showed no temporal trend. Our analysis reveals that 57% of postfire sediment erosion statewide occurred upstream of reservoirs, indicating potential impacts to reservoir storage capacity and thus increased risk to water‐resource security with ongoing climate change. Plain Language Summary: Large amounts of soil erode following wildfire, particularly if heavy rainfall occurs on the burned area within the first year after the fire. Climate change is increasing wildfires as well as extreme rain in many regions, including California. We investigated whether documented changes in fire and climate in California in the years 1984–2021 resulted in measurable changes in the amount or patterns of sediment produced from soil erosion following wildfire. Using a combination of models and measurements, we estimated annual postfire sediment erosion statewide, and separately for northern and southern California. We found that postfire erosion increased statewide over the time frame of interest. In southern California, postfire sediment erosion is dominated by debris flows, which are a liquefied mix of rock, mud, and soil, and no clear temporal patterns are apparent. In northern California, most cases of major postfire erosion occurred recently between 2011 and 2021. Most of the sediment mass eroded postfire statewide in the years 1984–2021 occurred upstream of reservoirs, rather than in places where sediment would move downstream directly to the ocean. These results indicate increasing pressure on water resources from postfire erosion with ongoing climate change. Key Points: First multi‐decadal assessment of postfire sediment mobilization in a region with rapidly intensifying fire and hydroclimate regimesThe mass of sediment eroded from hillslopes after wildfire has increased significantly in California since the 1980sMost postfire sediment erosion occurred upstream of reservoirs, indicating a growing risk to water security [ABSTRACT FROM AUTHOR]

Background: A partnered evaluation project with Veterans Health Administration Physical Medicine and Rehabilitation program office uses a partner-engaged approach to characterize and evaluate the national implementation of traumatic brain injury (TBI)Intensive Evaluation and Treatment Program (IETP)., Objective: This paper illustrates a partner-engaged approach to contextualizing the IETP within an implementation research logic model (IRLM) to inform program sustainment and spread., Setting: The project was conducted at five IETP sites: Tampa, Richmond, San Antonio, Palo Alto, and Minneapolis., Participants: Partners included national and site program leaders, clinicians, Department of Defense Referral Representatives, and researchers. Participants included program staff ( n  = 46) and Service Members/Veterans ( n  = 48)., Design: This paper represents a component of a larger participatory-based concurrent mixed methods quality improvement project., Main Measures: Participant scripts and demographic surveys., Methods: Datasets were analyzed using rapid iterative content analysis; IETP model was iteratively revised with partner feedback. Each site had an IETP clinical team member participate. The IRLM was contextualized within the Consolidated Framework for Implementation Research (CFIR); systematic consensus building expert reviewed implementation strategies; RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance); and Implementation Outcomes Framework (IOF)., Results: Analyses and partner feedback identified key characteristics, determinants, implementation strategies, mechanisms, and outcomes., Conclusions: This partner-engaged IRLM informs implementation and sustainment of a rehabilitation program for individuals with TBI. Findings will be leveraged to examine implementation, standardize core outcome measurements, and inform knowledge translation., Competing Interests: Authors declare there is no conflict of interest., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc.)

Background: All federal agencies are required to support appropriation requests with evidence and evaluation (US Public Law 115-435; the Evidence Act). The StrAtegic PoLicy EvIdence-Based Evaluation CeNTer (SALIENT) is 1 of 6 centers that help the Department of Veterans Affairs (VA) meet this requirement., Objective: Working with the existing VA evaluation structure, SALIENT evaluations will contribute to (1) optimize policies and programs for veteran populations; (2) improve outcomes regarding health, equity, cost, and provider well-being; (3) advance the science of dissemination and knowledge translation; and (4) expand the implementation and dissemination science workforce., Methods: We leverage the Lean Sprint methodology (iterative, incremental, rule-governed approach to clearly defined, and time-boxed work) and 3 cores to develop our evaluation plans collaboratively with operational partners and key stakeholders including veterans, policy experts, and clinicians. The Operations Core will work with evaluation teams to develop timelines, facilitate work, monitor progress, and guide quality improvement within SALIENT. The Methods Core will work with evaluation teams to identify the most appropriate qualitative, quantitative, and mixed methods approaches to address each evaluation, ensure that the analyses are conducted appropriately, and troubleshoot when problems with data acquisition and analysis arise. The Knowledge Translation (KT) Core will target key partners and decision makers using a needs-based market segmentation approach to ensure that needs are incorporated in the dissemination of knowledge. The KT Core will create communications briefs, playbooks, and other materials targeted at these market segments to facilitate implementation of evidence-based practices and maximize the impact of evaluation results., Results: The SALIENT team has developed a center infrastructure to support high-priority evaluations, often to be responsive to shifting operational needs and priorities. Our team has engaged in our core missions and operations to rapidly evaluate a high-priority areas, develop a comprehensive Lean Sprint systems redesign approach to training, and accelerate rapid knowledge translation., Conclusions: With an array of interdisciplinary expertise, operational partnerships, and integrated resources, SALIENT has an established and evolving infrastructure to rapidly develop and implement high-impact evaluations. Projects are developed with sustained efficiency approaches that can pivot to new priorities as needed and effectively translate knowledge for key stakeholders and policy makers, while creating a learning health system infrastructure to foster the next generation of evaluation and implementation scientists., International Registered Report Identifier (irrid): PRR1-10.2196/59830., (©Mary Jo Pugh, Jolie N Haun, P Jon White, Gerald Cochran, April F Mohanty, Lisa M McAndrew, Adam J Gordon, Richard E Nelson, Megan E Vanneman, Diana E Naranjo, Rachel C Benzinger, Audrey L Jones, Jacob Kean, Susan L Zickmund, Angela Fagerlin. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 19.09.2024.)

Introduction: MRI represents one of the clinical tools at the forefront of research efforts aimed at identifying diagnostic and prognostic biomarkers following traumatic brain injury (TBI). Both volumetric and diffusion MRI findings in mild TBI (mTBI) are mixed, making the findings difficult to interpret. As such, additional research is needed to continue to elucidate the relationship between the clinical features of mTBI and quantitative MRI measurements., Material and Methods: Volumetric and diffusion imaging data in a sample of 976 veterans and service members from the Chronic Effects of Neurotrauma Consortium and now the Long-Term Impact of Military-Relevant Brain Injury Consortium observational study of the late effects of mTBI in combat with and without a history of mTBI were examined. A series of regression models with link functions appropriate for the model outcome were used to evaluate the relationships among imaging measures and clinical features of mTBI. Each model included acquisition site, participant sex, and age as covariates. Separate regression models were fit for each region of interest where said region was a predictor., Results: After controlling for multiple comparisons, no significant main effect was noted for comparisons between veterans and service members with and without a history of mTBI. However, blast-related mTBI were associated with volumetric reductions of several subregions of the corpus callosum compared to non-blast-related mTBI. Several volumetric (i.e., hippocampal subfields, etc.) and diffusion (i.e., corona radiata, superior longitudinal fasciculus, etc.) MRI findings were noted to be associated with an increased number of repetitive mTBIs versus., Conclusions: In deployment-related mTBI, significant findings in this cohort were only observed when considering mTBI sub-groups (blast mechanism and total number/dose). Simply comparing healthy controls and those with a positive mTBI history is likely an oversimplification that may lead to non-significant findings, even in consortium analyses., (© The Association of Military Surgeons of the United States 2024.)

Objective: Epilepsy is associated with significant mortality risk. There is limited research examining how traumatic brain injury (TBI) timing affects mortality in relation to the onset of epilepsy. We aimed to assess the temporal relationship between epilepsy and TBI regarding mortality in a cohort of post-9/11 veterans., Methods: This retrospective cohort study included veterans who received health care in the Defense Health Agency and the Veterans Health Administration between 2000 and 2019. For those diagnosed with epilepsy, the index date was the date of first antiseizure medication or first seizure; we simulated the index date for those without epilepsy. We created the study groups by the index date and first documented TBI: (1) controls (no TBI, no epilepsy), (2) TBI only, (3) epilepsy only, (4) TBI before epilepsy, (5) TBI within 6 months after epilepsy, and (6) TBI >6 months after epilepsy. Kaplan-Meier estimates of all-cause mortality were calculated, and log-rank tests were used to compare unadjusted cumulative mortality rates among groups compared to controls. Cox proportional hazard models were used to compute hazard ratios (HRs) with 95% confidence intervals (CIs)., Results: Among 938 890 veterans, 27 436 (2.92%) met epilepsy criteria, and 264 890 (28.22%) had a TBI diagnosis. Mortality was higher for veterans with epilepsy than controls (6.26% vs. 1.12%; p < .01). Veterans with TBI diagnosed ≤6 months after epilepsy had the highest mortality hazard (HR = 5.02, 95% CI = 4.21-5.99) compared to controls, followed by those with TBI before epilepsy (HR = 4.25, 95% CI = 3.89-4.58), epilepsy only (HR = 4.00, 95% CI = 3.67-4.36), and TBI >6 months after epilepsy (HR = 2.49, 95% CI = 2.17-2.85). These differences were significant across groups., Significance: TBI timing relative to epilepsy affects time to mortality; TBI within 6 months after epilepsy or before epilepsy diagnosis was associated with earlier time to death compared to those with epilepsy only or TBI >6 months after epilepsy., (© 2024 The Author(s). Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Objective: To assess individual- and neighborhood-level sociodemographic factors associating with providers' ordering of nonpharmacologic treatments for patients with low back pain (LBP), specifically physical therapy, image-guided interventions, and lumbar surgery., Methods: Our cohort included all patients diagnosed with LBP from 2000 to 2017 in a statewide database of all hospitals and ambulatory surgical facilities within Utah. We compared sociodemographic and clinical characteristics of (1) patients with LBP who received any treatment with those who received none and (2) patients with LBP who received invasive LBP treatments with those who only received noninvasive LBP treatments using the Student's t test, Wilcoxon's rank-sum tests, and Pearson's χ 2 tests, as applicable, and two separate multivariate logistic regression models: (1) to determine whether sociodemographic characteristics were risk factors for receiving any LBP treatments and (2) risk factors for receiving invasive LBP treatments., Results: Individuals in the most disadvantaged neighborhoods were less likely to receive any nonpharmacologic treatment orders (odds ratio [OR] 0.74 for most disadvantaged, P < .001) and received fewer invasive therapies (0.92, P = .018). Individual-level characteristics correlating with lower rates of treatment orders were female sex, Native Hawaiian or other Pacific Islander race (OR 0.50, P < .001), Hispanic ethnicity (OR 0.77, P < .001), single or unmarried status (OR 0.69, P < .001), and no insurance or self-pay (OR 0.07, P < .001)., Conclusion: Neighborhood and individual sociodemographic variables associated with treatment orders for LBP with Area Deprivation Index, sex, race or ethnicity, insurance, and marital status associating with receipt of any treatment, as well as more invasive image-guided interventions and surgery., (Copyright © 2024 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Introduction: The DoD and VA Infrastructure for Clinical Intelligence (DaVINCI) data-sharing initiative has bridged the gap between DoD and VA data. DaVINCI utilizes the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to map DoD and VA-specific health care codes to a standardized terminology. Although OMOP CDM provides a standardized longitudinal view of health care concepts, it fails in capturing multiple and changing relationships beneficiaries have with DoD and VA as it has a static (vs. yearly) person characteristic table. Furthermore, DoD and VA utilize different policies and terminology to identify their respective beneficiaries, which makes it difficult to track patients longitudinally. The primary purpose of this report is to provide a methodology for categorizing beneficiaries and creating continuous longitudinal patient records to maximize the use of the joint DoD and VA data in DaVINCI., Materials and Methods: For calendar year 2000-2020, we combined DoD and VA OMOP CDM and source databases to uniquely categorize beneficiaries into the following hierarchical groups: Active Duty, Guard, and Reserve Service Members (ADSMs); Separatees; Retirees; Veterans; and Deceased. Once the cohorts were identified, we examined calendar year 2020 health care utilization data using the OMOP VISIT&#95;OCCURRENCE, DRUG&#95;EXPOSURE, MEASUREMENT, and PROCEDURE tables. We also used the Defense Enrollment and Eligibility Reporting System source table to derive enrollment periods for DoD beneficiaries. As VA does not have enrollment plans, we utilized the VA's priority groups (1-5) in the SPATIENT source table to crosswalk the DoD's enrollment concept to the VA. We then assessed lengths of continuous enrollments in DoD and VA and the impact of appending the longitudinal records together., Results: The majority of the ADSMs utilized the DoD system, but about 60,557 (3%) were seen in the VA for varied types of care. The market share of care provided to ADSMs by the VA varied by specialty and location. For Retirees, the split between DoD (1,625,874 [75%]) and VA (895,992 [41%]) health care utilization was more significant. The value added for utilizing DaVINCI in longitudinal studies was the highest for researchers normally limited to DoD data only. For beneficiaries who had 5 years of continuous enrollment, DaVINCI increased the potential study population by over 202% compared to using DoD data alone and by over 14% compared to VA data alone. Among beneficiaries with 20 years of continuous enrollment, DaVINCI increased the potential study population by over 133% compared to DoD data and by nearly 39% compared to VA data., Conclusions: DaVINCI has successfully combined DoD and VA data and utilized OMOP CDM to standardize health care concepts. However, to fully maximize the potential of DaVINCI's DoD and VA OMOP databases, researchers must uniquely categorize the DaVINCI cohort and build longitudinal patient records across DoD and VA. Because of the low other health insurance rates among DoD enrollees and their choice to enroll to a DoD Primary Care Manager, we believe this population to be the least censored in the DoD. Applying a similar concept through VA's priority groups (1-5) would enable researchers to follow ADSMs as they transition from the military., (© The Association of Military Surgeons of the United States 2022. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)