Since the 1990s, Veterans Health Administration (VHA) has maintained a registry of Veterans with Spinal Cord Injuries and Disorders (SCI/Ds) to guide clinical care, policy, and research. Historically, methods for collecting and recording data for the VHA SCI/D Registry (VSR) have required significant time, cost, and staffing to maintain, were susceptible to missing data, and caused delays in aggregation and reporting. Each subsequent data collection method was aimed at improving these issues over the last several decades. This paper describes the development and validation of a case-finding and data-capture algorithm that uses primary clinical data, including diagnoses and utilization across 9 million VHA electronic medical records, to create a comprehensive registry of living and deceased Veterans seen for SCI/D services since 2012. A multi-step process was used to develop and validate a computer algorithm to create a comprehensive registry of Veterans with SCI/D whose records are maintained in the enterprise wide VHA Corporate Data Warehouse. Chart reviews and validity checks were used to validate the accuracy of cases that were identified using the new algorithm. An initial cohort of 28,202 living and deceased Veterans with SCI/D who were enrolled in VHA care from 10/1/2012 through 9/30/2017 was validated. Tables, reports, and charts using VSR data were developed to provide operational tools to study, predict, and improve targeted management and care for Veterans with SCI/Ds. The modernized VSR includes data on diagnoses, qualifying fiscal year, recent utilization, demographics, injury, and impairment for 38,022 Veterans as of 11/2/2022. This establishes the VSR as one of the largest ongoing longitudinal SCI/D datasets in North America and provides operational reports for VHA population health management and evidence-based rehabilitation. The VSR also comprises one of the only registries for individuals with non-traumatic SCI/Ds and holds potential to advance research and treatment for multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and other motor neuron disorders with spinal cord involvement. Selected trends in VSR data indicate possible differences in the future lifelong care needs of Veterans with SCI/Ds. Future collaborative research using the VSR offers opportunities to contribute to knowledge and improve health care for people living with SCI/Ds.

Posttraumatic headache (PTH) is a common debilitating condition arising from head injury and is highly prevalent among military service members and veterans with traumatic brain injury (TBI). Diagnosis and treatment for PTH is still evolving, and surprisingly little is known about the putative mechanisms that drive these headaches. This manuscript describes the design of a randomized clinical trial of two nonpharmacological (i.e., behavioral) interventions for posttraumatic headache. Design of this trial required careful consideration of PTH diagnosis and inclusion criteria, which was challenging due to the lack of standard clinical characteristics in PTH unique from other types of headaches. The treatments under study differed in clinical focus and dose (i.e., number of treatment sessions), but the trial was designed to balance the treatments as well as possible. Finally, while the primary endpoints for pain research can vary from assessments of pain intensity to objective and subjective functional measures, this trial of PTH interventions chose carefully to establish clinically relevant endpoints and to maximize the opportunity to detect significant differences between groups with two primary outcomes. All these issues are discussed in this manuscript.

BACKGROUND: The interaction between cardiorespiratory fitness (CRF) and incidence of atrial fibrillation (AF) and the interaction between obesity and incidence of AF have been explored separately. Therefore, we evaluated the association between CRF, body mass index (BMI), and risk of developing AF in a cohort of middle-aged and older US Veterans.
METHODS: Symptom limited exercise tests (ETT) were conducted among 16,397 Veterans (97% male) from January 9,1987 to December 31,2017. No history of AF was evident at the time of the ETTs. CRF was expressed as quartiles of peak metabolic equivalents (METs) achieved within each age decile. Weight status was classified as normal (BMI < 25 kg/m2), overweight (BMI 25-30 kg/m2), obese (BMI 30-35 kg/m2), or severely obese (BMI > 35 kg/m2). Multivariable Cox proportional hazards regression models were used to compare the association between BMI, CRF categories, and incidence of AF.
RESULTS: Over a median follow-up of 10.7 years, 2,155 (13.1%) developed AF. Obese and severely obese subjects had 13% and 32% higher risks for incidence of AF, respectively, vs. normal weight subjects. Overweight and obese subjects in the most fit quartile had 50% decline in AF risk compared to the least-fit subjects. Severely obese subjects had marked increases in AF risk (~50-60%) regardless of fitness level. Risk of developing AF increases with higher BMI and lower CRF.
CONCLUSIONS: Improving CRF should be advocated when assessing those at risk for developing AF.