Protocol for a pragmatic trial of Cannabidiol (CBD) to improve chronic pain symptoms among United States Veterans.

BACKGROUND: Chronic pain affects over 100 million Americans, with a disproportionately high number being Veterans. Chronic pain is often difficult to treat and responds variably to medications, with many providing minimal relief or having adverse side effects that preclude use. Cannabidiol (CBD) has emerged as a potential treatment for chronic pain, yet research in this area remains limited, with few studies examining CBD's analgesic potential. Because Veterans have a high need for improved pain care, we designed a clinical trial to investigate CBD's effectiveness in managing chronic pain symptoms among Veterans. We aim to determine whether CBD oral solution compared to placebo study medication is associated with greater improvement in the Patient Global Impression of Change (PGIC). METHODS: We designed a randomized, double-blind, placebo-controlled, pragmatic clinical trial with 468 participants. Participants will be randomly assigned in a 1:1 ratio to receive either placebo or a CBD oral solution over a 4-week period. The trial is remote via a smartphone app and by shipping study materials, including study medication, to participants. We will compare the difference in PGIC between the CBD and placebo group after four weeks and impacts on secondary outcomes (e.g., pain severity, pain interference, anxiety, suicide ideation, and sleep disturbance). DISCUSSION: Once complete, this trial will be among the largest to date investigating the efficacy of CBD for chronic pain. Findings from this clinical trial will contribute to a greater knowledge of CBD's analgesic potential and guide further research. Given the relative availability of CBD, our findings will help elucidate the potential of an accessible option for helping to manage chronic pain among Veterans. TRIAL REGISTRATION: This protocol is registered at clinicaltrials.gov under study number NCT06213233.

Gender-Affirming Hormone Treatment and Metabolic Syndrome Among Transgender Veterans.

Importance: Gender-affirming hormone treatment (GAHT) is a common therapy for transgender individuals to reduce gender dysphoria and improve quality of life. Clarifying the long-term effects of GAHT remains a priority in transgender health research. Objective: To explore whether sex hormones (estradiol and testosterone) are associated with the development of metabolic syndrome in transgender veterans compared with cisgender veterans. Design, Setting, and Participants: This retrospective, longitudinal cohort study used International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis codes for gender dysphoria from the Veterans Health Administration national database to identify transfeminine and transmasculine veterans receiving documented feminizing (estradiol) or masculinizing (testosterone) treatment from January 1, 2006, to December 31, 2019, and for whom the GAHT initiation date and metabolic syndrome component-related data were available. Transgender veterans were matched to cisgender referents. Exposure: Gender-affirming hormone treatment. Main Outcomes and Measures: Metabolic syndrome z-scores were calculated based on body mass index, systolic blood pressure, and levels of high-density lipoprotein cholesterol, triglycerides, and blood glucose. Changes in mean z-scores were compared among the transgender and cisgender groups before and after the index date (corresponding to GAHT initiation) using a repeated-measures analysis of variance model. Results: The cohort included 1290 participants: 645 transgender (494 [38.3%] transfeminine, 151 [11.7%] transmasculine) and 645 cisgender (280 [21.7%] female, 365 [28.3%] male). Mean (SD) age at the index date was 41.3 (13.2) years. Metabolic syndrome z-scores changed significantly over time and differed significantly across groups. Overall, transmasculine veterans had the greatest percentage increase in mean (SEM) z-scores after vs before the index date (298.0% [57.0%]; P < .001), followed by cisgender females (108.3% [27.5%]; P < .001), cisgender males (49.3% [27.5%]; P = .02), and transfeminine persons (3.0% [10.7%]; P = .77). Conclusions and Relevance: In this cohort study, in both cisgender and transgender veterans, estradiol was associated with reduced metabolic syndrome risk, whereas testosterone was associated with increased risk. However, transmasculine individuals had the greatest risk and transfeminine individuals had the lowest risk of metabolic syndrome associated with these hormones. This is relevant for the management of metabolic syndrome risk factors in cisgender and transgender individuals and to potentially predict the risk of atherosclerotic cardiovascular disease, type 2 diabetes, systolic hypertension, insulin resistance, and nonalcoholic fatty liver disease.

Does smoking cessation reduce other substance use, psychiatric symptoms, and pain symptoms? Results from an emulated hypothetical randomized trial of US veterans.

BACKGROUND: Quitting smoking may lead to improvement in substance use, psychiatric symptoms, and pain, especially among high-risk populations who are more likely to experience comorbid conditions. However, causal inferences regarding smoking cessation and its subsequent benefits have been limited. METHODS: We emulated a hypothetical open-label randomized control trial of smoking cessation using longitudinal observational data of HIV-positive and HIV-negative US veterans from 2003-2015 in the Veterans Aging Cohort Study. We followed individuals from the first time they self-reported current cigarette smoking (baseline). We categorized participants as quitters or non-quitters at the first follow-up visit (approximately 1 year after baseline). Using inverse probability weighting to adjust for confounding and selection bias, we estimated odds ratios for improvement of co-occurring conditions (unhealthy alcohol use, cannabis use, illicit opioid use, cocaine use, depressive symptoms, anxiety symptoms, and pain symptoms) at second follow-up (approximately 2 years after baseline) for those who quit smoking compared to those who did not, among individuals who had the condition at baseline. RESULTS: Of 4,165 eligible individuals (i.e., current smokers at baseline), 419 reported no current smoking and 2,330 reported current smoking at the first follow-up. Adjusted odds ratios (95% confidence intervals) for associations between quitting smoking and improvement of each condition at second follow-up were: 2.10 (1.01, 4.35) for unhealthy alcohol use, 1.75 (1.00, 3.06) for cannabis use, 1.10 (0.58, 2.08) for illicit opioid use, and 2.25 (1.20, 4.24) for cocaine use, 0.78 (0.44, 1.38) for depressive symptoms, 0.93 (0.58, 1.49) for anxiety symptoms, and 1.31 (0.84, 2.06) for pain symptoms. CONCLUSIONS: While a causal interpretation of our findings may not be warranted, we found evidence for decreased substance use among veterans who quit cigarette smoking but none for the resolution of psychiatric conditions or pain symptoms. Findings suggest the need for additional resources combined with smoking cessation to reduce psychiatric and pain symptoms for high-risk populations.

Spironolactone Reduces the Risk of Death in Veterans With Heart Failure With Preserved Ejection Fraction.

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a complex syndrome increasing in prevalence and affecting millions worldwide but with limited evidence-based therapies. Results from explanatory clinical trials suggest that spironolactone may help to improve outcomes in patients with HFpEF. We sought to investigate the effectiveness of spironolactone in reducing death and hospitalization outcomes for patients with HFpEF in a real-world setting. METHODS AND RESULTS: We used electronic health records from the US Veterans Affairs (VA) health care system between 2002 and 2012 to identify patients with HFpEF who were followed longitudinally through 2014 using a validated algorithm. Among our HFpEF cohort that is 96% men, 85% White individuals, and aged 74±11 years, 3690 spironolactone users and 49 191 nonusers were identified and followed for a median of 2.9 (interquartile range [IQR], 1.5-2.4) and 3.3 (IQR, 1.6-5.9) years, respectively. We evaluated the effect of spironolactone use on all-cause death and number of days hospitalized per year for heart failure or for any cause by fitting generalized estimating equation-based Poisson and negative binomial models. Crude rates of 10.3 versus 13.5 deaths and 394.0 versus 485.9 days hospitalized were observed per 100 person-years for spironolactone users versus nonusers, respectively. After multivariable adjustment, there was a 21% reduction (95% CI, 13-29; P<0.0001) in rate of all-cause death among spironolactone users compared with nonusers and no statistically significant difference in days hospitalized for all causes or heart failure. CONCLUSIONS: In a real-world national cohort of patients with HFpEF, spironolactone use reduced all-cause death and demonstrated a favorable trend in reducing the burden of hospitalizations.

Linked Exposures Across Databases: an exposure common data elements aggregation framework to facilitate clinical exposure review.

Understanding the health outcomes of military exposures is of critical importance for Veterans, their health care team, and national leaders. Approximately 43% of Veterans report military exposure concerns to their VA providers. Understanding the causal influences of environmental exposures on health is a complex exposure science task and often requires interpreting multiple data sources; particularly when exposure pathways and multi-exposure interactions are ill-defined, as is the case for complex and emerging military service exposures. Thus, there is a need to standardize clinically meaningful exposure metrics from different data sources to guide clinicians and researchers with a consistent model for investigating and communicating exposure risk profiles. The Linked Exposures Across Databases (LEAD) framework provides a unifying model for characterizing exposures from different exposure databases with a focus on providing clinically relevant exposure metrics. Application of LEAD is demonstrated through comparison of different military exposure data sources: Veteran Military Occupational and Environmental Exposure Assessment Tool (VMOAT), Individual Longitudinal Exposure Record (ILER) database, and a military incident report database, the Explosive Ordnance Disposal Information Management System (EODIMS). This cohesive method for evaluating military exposures leverages established information with new sources of data and has the potential to influence how military exposure data is integrated into exposure health care and investigational models.

Supporting nursing faculty to teach veteran's care: a mixed method, multi-intervention study.

OBJECTIVES: This study aimed to (a) describe nurse educators' attitudes towards veterans after workshop participation, (b) evaluate the effectiveness of the workshop and timed digital interventions (TDI) on nurse educators' integration of veteran-centered content into their courses and curricula, and (c) describe nurse educators' experiences with transferring learning from the workshop to teaching practice. METHODS: A longitudinal multi-intervention, multi-method pilot study was conducted using pre- and post-workshop surveys and interviews. RESULTS: Twenty-six nurse faculty reported a neutral attitude toward working with veterans during the pre-workshop survey period. TDIs kept veteran-centered content fresh on faculty minds, yielding evidence of integration into nursing courses. CONCLUSIONS: Nursing faculty preparation and development is crucial to effectively integrate specific veteran care content into nursing education to ensure a competent and culturally sensitive workforce. Integrating TDIs using widely accessible technologies is a cost-effective way of increasing engagement with new information and bridge implementation gaps associated with traditional professional development activities.

Internet-Guided Cognitive Behavioral Therapy for Insomnia Among Patients With Traumatic Brain Injury: A Randomized Clinical Trial.

Importance: Many military service members and veterans report insomnia after sustaining traumatic brain injury (TBI). Limitations of first-line treatment, cognitive-behavioral therapy for insomnia (CBT-I), include availability of qualified clinicians, low completion rates, and cost. Objective: To investigate the feasibility and efficacy of internet-guided CBT-I (eCBT-I) in military service members and veterans with insomnia and a history of TBI. Design, Setting, and Participants: This randomized clinical trial of fully remote internet-based interventions and evaluations was conducted from September 1, 2020, to June 30, 2021, with 3 months of follow-up. Participants included a volunteer sample of military service members and veterans aged 18 to 64 years with a history of mild TBI/concussion and at least moderately severe insomnia defined as an insomnia severity index (ISI) score of greater than 14 and Pittsburgh Sleep Quality Index of greater than 4. Self-reported race, ethnicity, and educational level were generally representative of the US military. Data were analyzed from October 21, 2021, to April 29, 2024. Intervention: Internet-based CBT-I delivered over 6 weekly lesson modules with assigned homework activities. Main Outcomes and Measures: The prespecified primary outcome measure was change in ISI score over time. Prespecified secondary outcome measures included self-reported measures of depression symptoms, posttraumatic stress disorder (PTSD) symptoms, sleep quality, migraine impact, and fatigue. Results: Of 204 people screened, 125 were randomized 3:1 to eCBT-I vs online sleep education, and 106 completed baseline evaluations (83 men [78.3%]; mean [SD] age, 42 [12] years). Of these, 22 participants (20.8%) were Hispanic or Latino and 78 (73.6%) were White. Fifty participants completed postintervention evaluations, and 41 completed the 3-month follow-up. Baseline mean (SD) ISI scores were 19.7 (4.0) in those randomized to eCBT-I and 18.9 (5.0) in those randomized to sleep education. After intervention, mean (SD) ISI scores were 13.7 (5.6) in those randomized to eCBT-I and 16.6 (5.7) in those randomized to sleep education. The difference in the extent of reduction in ISI scores between groups was 3.5 (95% CI,-6.5 to -0.4 [P = .03]; Cohen d, -0.32 [95% CI, -0.70 to -0.04]). In the eCBT-I group, the extent of insomnia improvement correlated with the extent of depressive symptom improvement (Spearman ρ = 0.68 [P < .001]), PTSD symptoms (ρ = 0.36 [P = .04]), sleep quality (ρ = 0.54 [P = .001]), and fatigue impact (ρ = -0.58 [P < .001]) but not migraine-related disability. Conclusions and Relevance: The findings of this randomized clinical trial suggest that fully remote eCBT-I was moderately feasible and effective for self-reported insomnia and depression symptoms in military service members and veterans with a history of TBI. There is great potential benefit for eCBT-I due to low availability and cost of qualified CBT-I clinicians, although optimization of completion rates remains a challenge. Future studies may use home-based objective sleep assessments and should increase study retention. Trial Registration: ClinicalTrials.gov Identifier: NCT04377009.

Why Do Veterans Not Respond as Well as Civilians to Trauma-Focused Therapies for PTSD?

ABSTRACT: This column first reviews evidence that veterans have poorer response to trauma-focused therapies for PTSD compared to civilians. We then consider several explanations for this trend, starting with gender as a possible confounding variable. We also examine other hypotheses, including the effects of the military acculturation process, the unique influences of military traumas, such as combat and military sexual traumas, and the roles of traumatic brain injuries (TBIs) and moral injury. Future research, we conclude, must determine whether gender explains the differences in trauma-focused therapy response. If so, then the underlying reasons must be further explored. If not, then we must determine the unique characteristics of the veteran population that make it more resistant to treatment. Mining these elements will help us adapt our trauma-focused therapies to better help this population and close the response-rate gap.

Intensity, Characteristics, and Factors Associated With Receipt of Care Coordination Among High-Risk Veterans in the Veterans Health Administration.

BACKGROUND: The Veterans Health Administration (VHA) has initiatives underway to enhance the provision of care coordination (CC), particularly among high-risk Veterans. Yet, evidence detailing the characteristics of and who receives VHA CC is limited. OBJECTIVES: We examined intensity, timing, setting, and factors associated with VHA CC among high-risk Veterans. RESEARCH DESIGN: We conducted a retrospective observational cohort study, following Veterans for 1 year after being identified as high-risk for hospitalization or mortality, to characterize their CC. Demographic and clinical factors predictive of CC were identified via multivariate logistic regression. SUBJECTS: A total of 1,843,272 VHA-enrolled high-risk Veterans in fiscal years 2019-2021. MEASURES: We measured 5 CC variables during the year after Veterans were identified as high risk: (1) receipt of any service, (2) number of services received, (3) number of days to first service, (4) number of days between services, and (5) type of visit during which services were received. RESULTS: Overall, 31% of high-risk Veterans in the sample received CC during one-year follow-up. Among Veterans who received ≥1 service, a median of 2 [IQR (1, 6)] services were received. Among Veterans who received ≥2 services, there was a median of 26 [IQR (10, 57)] days between services. Most services were received during outpatient psychiatry (46%) or medicine (16%) visits. Veterans' sociodemographic and clinical characteristics were associated with receipt of CC. CONCLUSIONS: A minority of Veterans received CC in the year after being identified as high-risk, and there was variation in intensity, timing, and setting of CC. Research is needed to examine the fit between Veterans' CC needs and preferences and VHA CC delivery.

Natural Language Processing Algorithm to Extract Multiple Myeloma Stage From Oncology Notes in the Veterans Affairs Healthcare System.

PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement in large databases is often lacking. We aimed to develop and validate a natural language processing (NLP) algorithm to extract oncologists' documentation of stage in the national Veterans Affairs (VA) Healthcare System. METHODS: Using nationwide electronic health record (EHR) and cancer registry data from the VA Corporate Data Warehouse, we developed and validated a rule-based NLP algorithm to extract oncologist-determined MM stage. To that end, a clinician annotated MM stage within over 5,000 short snippets of clinical notes, and annotated MM stage at MM treatment initiation for 200 patients. These were allocated into snippet- and patient-level development and validation sets. We developed MM stage extraction and roll-up algorithms within the development sets. After the algorithms were finalized, we validated them using standard measures in held-out validation sets. RESULTS: We developed algorithms for three different MM staging systems that have been in widespread use (Revised International Staging System [R-ISS], International Staging System [ISS], and Durie-Salmon [DS]) and for stage reported without a clearly defined system. Precision and recall were uniformly high for MM stage at the snippet level, ranging from 0.92 to 0.99 for the different MM staging systems. Performance in identifying for MM stage at treatment initiation at the patient level was also excellent, with precision of 0.92, 0.96, 0.90, and 0.86 and recall of 0.99, 0.98, 0.94, and 0.92 for R-ISS, ISS, DS, and unclear stage, respectively. CONCLUSION: Our MM stage extraction algorithm uses rule-based NLP and data aggregation to accurately measure MM stage documented in oncology notes and pathology reports in VA's national EHR system. It may be adapted to other systems where MM stage is recorded in clinical notes.

Subjective cognitive concerns, APOE ε4, PTSD symptoms, and risk for dementia among older veterans.

BACKGROUND: Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups. METHODS: Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older. RESULTS: PTSD symptoms (B = 0.50-0.52, p < 1E-250) and probable TBI (B = 0.05-0.19, p = 1.51E-07 - 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13-1.21), APOE ε4 (HR = 1.73-2.05) and SCC (HR = 1.18-1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18). CONCLUSIONS: The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors.

The Impact of User Engagement With Exposure Components on Posttraumatic Stress Symptoms in an mHealth Mobile App: Secondary Analysis of a Randomized Controlled Trial.

Background: Mobile mental health apps are a cost-effective option for managing mental health problems, such as posttraumatic stress disorder (PTSD). The efficacy of mobile health (mHealth) apps depends on engagement with the app, but few studies have examined how users engage with different features of mHealth apps for PTSD. Objective: This study aims to examine the relationship between app engagement indices and PTSD symptom reduction using data from an unblinded pilot randomized controlled trial of "Renew" (Vertical Design), an exposure-based app for PTSD with and without coaching support. Because exposure is an effective approach for treating PTSD, we expected that engagement with exposure activities would be positively related to symptom reduction, over and above overall app usage. Methods: Participants were veterans (N=69) with clinically significant PTSD symptoms who were recruited online using Facebook advertisements and invited to use the Renew app as often as they wanted over a 6-week period. Participants completed screening and assessments online but provided informed consent, toured the app, and completed feedback interviews via telephone. We assessed users' self-reported PTSD symptoms before and after a 6-week intervention period and collected app usage data using a research-instrumented dashboard. To examine overall app engagement, we used data on the total time spent in the app, the number of log-in days, and the number of points that the user gained in the app. To examine engagement with exposure components, we used data on total time spent completing exposure activities (both in vivo and imaginal), the number of in vivo exposure activities completed, and the number of characters written in response to imaginal exposure prompts. We used hierarchical regression analyses to test the effect of engagement indices on change in PTSD symptoms. Results: Usage varied widely. Participants spent an average of 166.09 (SD 156.52) minutes using Renew, over an average of 14.7 (SD 10.71) mean log-in days. Engagement with the exposure components of the app was positively associated with PTSD symptom reduction (F6,62=2.31; P=.04). Moreover, this relationship remained significant when controlling for overall engagement with the app (ΔF3,62=4.42; P=.007). The number of characters written during imaginal exposure (ß=.37; P=.009) and the amount of time spent completing exposure activities (ß=.36; P=.03) were significant contributors to the model. Conclusions: To our knowledge, this is the first study to show a relationship between symptom improvement and engagement with the active therapeutic components of an mHealth app (ie, exposure) for PTSD. This relationship held when controlling for overall app use, which suggests that it was engagement with exposure, specifically, that was associated with symptom change. Future work to identify ways of promoting greater engagement with self-guided exposure may help improve the effectiveness of mHealth apps for PTSD.

Impacts of Telehealth Adoption on the Quality of Care for Individuals With Serious Mental Illness: Retrospective Observational Analysis of Veterans Affairs Administrative Data.

Background: Telehealth implementation can be challenging for persons with serious mental illness (SMI), which may impact their quality of care and health outcomes. The literature on telehealth's impacts on SMI care outcomes is mixed, necessitating further investigation. Objective: We examined the impacts of facility-level telehealth adoption on quality of care metrics over time among patients with SMI. Methods: We analyzed Veterans Affairs (VA) administrative data across 138 facilities from January 2021 to December 2022. We performed longitudinal mixed-effects regressions to identify the relationships between the proportion of facility-level telehealth visits and SMI specialty care quality metrics: engagement with primary care; access and continuity of care across a range of mental health services including psychotherapy or psychosocial rehabilitation, SMI-specific intensive outpatient programs, and intensive case management; and continuity of mental health care after a high-risk event (eg, suicide attempt). Results: Facilities with a higher proportion of telehealth visits had reduced access and continuity of physical and mental health care for patients with SMI (P<.05). Higher telehealth adoption was associated with reduced primary care engagement (z=-4.04; P<.001), reduced access to and continuity in SMI-specific intensive case management (z=-4.49; P<.001; z=-3.15; P<.002), reductions in the continuity of care within psychotherapy and psychosocial rehabilitation (z=-3.74; P<.001), and continuity of care after a high-risk event (z=-2.46; P<.01). Telehealth uptake initially increased access to intensive outpatient but did not improve its continuity over time (z=-4.47; P<.001). Except for continuity within SMI-specific intensive case management (z=2.62; P<.009), continuity did not improve over time as telehealth became routinized. Conclusions: Although telehealth helped preserve health care access during the pandemic, telehealth may have tradeoffs with regard to quality of care for some individuals with SMI. These data suggest that engagement strategies used by SMI-specific intensive case management may have preserved quality and could benefit other settings. Strategies that enhance telehealth implementation-selected through a health equity lens-may improve quality of care among patients with SMI.

Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.

BACKGROUND AND OBJECTIVE: To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validated while incorporating a Veteran sample. DERIVATION COHORT: Adults (age ≥ 18 yr) hospitalized outside the ICU with a diagnosis of COVID-19 for model development to the Veterans Health Administration (VHA) (n = 80 hospitals). VALIDATION COHORT: External validation occurred in a VHA cohort of 34 hospitals, as well as six non-Veteran health systems for further external validation (n = 21 hospitals) between 2020 and 2023. PREDICTION MODEL: eXtreme Gradient Boosting machine learning methods were used, and performance was assessed using the area under the receiver operating characteristic curve and compared with the National Early Warning Score (NEWS). The primary outcome was transfer to the ICU or death within 24 hours of each new variable observation. Model predictor variables included demographics, vital signs, structured flowsheet data, and laboratory values. RESULTS: A total of 96,908 admissions occurred during the study period, of which 59,897 were in the Veteran sample and 37,011 were in the non-Veteran sample. During external validation in the Veteran sample, the model demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.88. This was significantly higher than NEWS (0.79; p < 0.01). In the non-Veteran sample, the model also demonstrated excellent discrimination (0.86 vs. 0.79 for NEWS; p < 0.01). The top three variables of importance were eosinophil percentage, mean oxygen saturation in the prior 24-hour period, and worst mental status in the prior 24-hour period. CONCLUSIONS: We used machine learning methods to develop and validate a highly accurate early warning score in both Veterans and non-Veterans hospitalized with COVID-19. The model could lead to earlier identification and therapy, which may improve outcomes.

Protein Identification for Stroke Progression via Mendelian Randomization in Million Veteran Program and UK Biobank.

BACKGROUND: Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke. METHODS: We performed genome-wide association studies for subsequent major adverse cardiovascular events (MACE; ncases=51 929; ncontrols=39 980) and subsequent arterial ischemic stroke (AIS; ncases=45 120; ncontrols=46 789) after the first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (protein quantitative trait loci) to determine the effect of 1463 plasma protein abundances on subsequent MACE using Mendelian randomization. RESULTS: Two variants were significantly associated with subsequent cardiovascular events: rs76472767 near gene RNF220 (odds ratio, 0.75 [95% CI, 0.64-0.85]; P=3.69×10-8) with subsequent AIS and rs13294166 near gene LINC01492 (odds ratio, 1.52 [95% CI, 1.37-1.67]; P=3.77×10-8) with subsequent MACE. Using Mendelian randomization, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 ([C-C motif chemokine 27], effect odds ratio, 0.77 [95% CI, 0.66-0.88]; adjusted P=0.05) and TNFRSF14 ([tumor necrosis factor receptor superfamily member 14], effect odds ratio, 1.42 [95% CI, 1.24-1.60]; adjusted P=0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation. CONCLUSIONS: We found evidence that 2 proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets.

Rural veteran perception of healthcare access in South Carolina and Florida: a qualitative study.

BACKGROUND: Access to mental and physical healthcare in rural areas is challenging for Veterans and their families but essential for good health. Even though recent research has revealed some of the challenges rural Veterans face accessing healthcare, a complete understanding of the gap in access is still unclear. METHODS: This qualitative study aimed to explore participants' perceptions of healthcare access. Structured interviews were conducted with 124 Veterans and spouses of Veterans from rural qualifying counties in South Carolina and Florida. RESULTS: The study's results revealed five main dimensions of access: geographic proximity, transportation, communication, cultural competence, and resources. Distance to service needed can negatively impact access for Veterans and their families in general, especially for those whose health is declining or who cannot drive because of their age. Lack of transportation, problems with transportation services, and lack of public transportation can lead to delays in care. Additionally, the lack of communication with the Veterans Affairs (VA) Health System and with the healthcare team, as well as inefficient communication among the healthcare team, lack of coordination of care between the VA health system and community providers, and the lack of cultural competence of healthcare providers and contracted personnel made access to services even more challenging. CONCLUSIONS: Improving communication can help to develop a sense of trust between Veterans and the VA, and between Veterans and spouses with the healthcare team. It can also lead to increased patient satisfaction. Ensuring healthcare providers and contracted personnel are culturally competent to talk and treat Veterans can improve patient trust and adherence to treatment. Lastly, resource-related challenges included financial problems, lack of prompt access to appointments, lack of providers, limited access to local clinics and hospitals, limited local programs available, and reimbursement issues.

Perception of Ridesharing Among Veterans With Cardiovascular Diseases in the Era of the MISSION Act.

The Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018 expanded veteran's access to community care leading to increased utilization of non-Veterans Affairs (VA) care and prompting concerns about the sustainability and cost-effectiveness of this care model for the VA. This study seeks to explore veterans' attitudes toward ridesharing services as a means of accessing VA-based cardiovascular care. This cross-sectional, quality improvement study utilized a 7-question survey administered to patients in an urban VA Heart Center to assess transportation preferences and opinions on ridesharing. Participants were more likely to support ridesharing if they held a positive opinion of rideshare ( P = 0.024), felt safe utilizing rideshare ( P = 0.025), or were undergoing invasive procedures ( P = 0.007). Distance traveled did not influence support of ridesharing ( P = 0.617). In conclusion, investing in ridesharing for veterans may provide a cost-effective means to improve VA access and continuity of care regardless of distance.

Something to Chew on; Plate-Waste at an Ontario Veteran's Centre.

There is paucity of data assessing levels of food/beverage waste in long-term care (LTC) facilities, especially in Ontario. Observations in the Veteran's Centre (VC) at Sunnybrook Health Sciences Centre (Sunnybrook) indicated food/beverage waste may be high, potentially impacting sustainability efforts within our institution. Before proceeding with waste reduction efforts, we conducted a comprehensive 3-day waste-audit of food/beverage items provided to VC residents with the goal of understanding the extent of food/beverage waste at VC, items wasted, and any other factors that may inform future changes. Our results indicate that 28% of items served to residents were wasted. Lunch was the meal with greatest waste at 31% and waste of solid items was 12% higher than that of liquids. We observed a large variability in waste between residents and within each resident, with 15% of residents wasting >50% of items provided. This study provides a deeper insight into the magnitude of food/beverage waste in a LTC population and highlights the importance of considering individualized strategies to address waste to avoid negative impact on residents.