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1.
Epilepsia ; 65(8): 2255-2269, 2024 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-39119799

RESUMEN

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.


Asunto(s)
Lesiones Traumáticas del Encéfalo , Epilepsia , Veteranos , Humanos , Lesiones Traumáticas del Encéfalo/mortalidad , Lesiones Traumáticas del Encéfalo/complicaciones , Veteranos/estadística & datos numéricos , Masculino , Femenino , Adulto , Epilepsia/mortalidad , Persona de Mediana Edad , Estudios Retrospectivos , Estados Unidos/epidemiología , Factores de Tiempo , Estudios de Cohortes , Anciano , Modelos de Riesgos Proporcionales
2.
Artículo en Inglés | MEDLINE | ID: mdl-39038102

RESUMEN

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.

3.
Mil Med ; 2024 Feb 24.
Artículo en Inglés | MEDLINE | ID: mdl-38401164

RESUMEN

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.

4.
J Am Coll Radiol ; 21(7): 1010-1023, 2024 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-38369043

RESUMEN

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 χ2 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.


Asunto(s)
Disparidades en Atención de Salud , Dolor de la Región Lumbar , Pautas de la Práctica en Medicina , Humanos , Dolor de la Región Lumbar/cirugía , Dolor de la Región Lumbar/terapia , Femenino , Masculino , Persona de Mediana Edad , Pautas de la Práctica en Medicina/estadística & datos numéricos , Utah , Adulto , Radiografía Intervencional , Estudios de Cohortes , Modalidades de Fisioterapia , Factores Socioeconómicos , Factores de Riesgo
5.
Health Aff Sch ; 1(4): qxad047, 2023 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-38756741

RESUMEN

Variation in availability, format, and standardization of patient attributes across health care organizations impacts patient-matching performance. We report on the changing nature of patient-matching features available from 2010-2020 across diverse care settings. We asked 38 health care provider organizations about their current patient attribute data-collection practices. All sites collected name, date of birth (DOB), address, and phone number. Name, DOB, current address, social security number (SSN), sex, and phone number were most commonly used for cross-provider patient matching. Electronic health record queries for a subset of 20 participating sites revealed that DOB, first name, last name, city, and postal codes were highly available (>90%) across health care organizations and time. SSN declined slightly in the last years of the study period. Birth sex, gender identity, language, country full name, country abbreviation, health insurance number, ethnicity, cell phone number, email address, and weight increased over 50% from 2010 to 2020. Understanding the wide variation in available patient attributes across care settings in the United States can guide selection and standardization efforts for improved patient matching in the United States.

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