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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.

Objectives: To determine the positive predictive value (PPV) of algorithms to identify patients with major (at the ankle or more proximal) lower extremity amputation (LEA) using Department of Veterans Affairs electronic medical records (EMR) and to evaluate whether PPV varies by sex, age, and race., Design: We conducted a validation study comparing EMR determined LEA status to self-reported LEA (criterion standard)., Setting: Veterans who receive care at the Department of Veterans Affairs., Participants: We invited a national sample of patients (N=699) with at least 1 procedure or diagnosis code for major LEA to participate. We oversampled women, Black men, and men ≤40 years of age., Interventions: Not applicable., Main Outcome Measure: We calculated PPV estimates and false negative percentages for 7 algorithms using EMR LEA procedure and diagnosis codes relative to self-reported major LEA., Results: A total of 466 veterans self-reported their LEA status (68%). PPVs for the 7 algorithms ranged from 89% to 100%. The algorithm that required a single diagnosis or procedure code had the lowest PPV (89%). The algorithm that required at least 1 procedure code had the highest PPV (100%) but also had the highest proportion of false negatives (66%). Algorithms that required at least 1 procedure code or 2 or more diagnosis codes 1 month to 1 year apart had high PPVs (98%-99%) but varied in terms of false negative percentages. PPV estimates were higher among men than women but did not differ meaningfully by age or race, after accounting for sex., Conclusion: PPVs were higher if 1 procedure or at least 2 diagnosis codes were required; the difference between algorithms was marked by sex. Investigators should consider trade-offs between PPV and false negatives to identify patients with LEA using EMRs.

Background and Aims: Gastrointestinal (GI) symptoms are well-recognized manifestations of coronavirus disease 2019 (COVID-19). Our primary objective was to evaluate the association between GI symptoms and COVID-19 severity., Methods: In this nationwide cohort of US veterans, we evaluated GI symptoms (nausea/vomiting/diarrhea) reported 30 days before and including the date of positive SARS-CoV-2 testing (March 1, 2020, to February 20, 2021). All patients had ≥1 year of prior baseline data and ≥60 days follow-up relative to the test date. We used propensity score (PS)-weighting to balance covariates in patients with vs without GI symptoms. The primary composite outcome was severe COVID-19, defined as hospital admission, intensive care unit admission, mechanical ventilation, or death within 60 days of positive testing., Results: Of 218,045 SARS-CoV-2 positive patients, 29,257 (13.4%) had GI symptoms. After PS weighting, all covariates were balanced. In the PS-weighted cohort, patients with vs without GI symptoms had severe COVID-19 more often (29.0% vs 17.1%; P < .001). When restricted to hospitalized patients (14.9%; n=32,430), patients with GI symptoms had similar frequencies of intensive care unit admission and mechanical ventilation compared with patients without symptoms. There was a significant age interaction; among hospitalized patients aged ≥70 years, lower COVID-19-associated mortality was observed in patients with vs without GI symptoms, even after accounting for COVID-19-specific medical treatments., Conclusion: In the largest integrated US health care system, SARS-CoV-2-positive patients with GI symptoms experienced severe COVID-19 outcomes more often than those without symptoms. Additional research on COVID-19-associated GI symptoms may inform preventive efforts and interventions to reduce severe COVID-19., (© 2022 Published by Elsevier Inc. on behalf of the AGA Institute.)

Objective: To examine the effect of cigarette smoking (CS) status and total testosterone (TT) levels after testosterone replacement therapy (TRT) on all-cause mortality, myocardial infarction (MI), and stroke in male smokers and nonsmokers without history of MI and stroke., Participants and Methods: Data from 18,055 males with known CS status and low TT levels who received TRT at the Veterans Health Administration between December 1, 1999, and May 31, 2014, were grouped into (1) current smokers with normalized TT, (2) current smokers with nonnormalized TT, (3) nonsmokers with normalized TT, and (4) nonsmokers with nonnormalized TT. Combined effect of CS status and TT level normalization after TRT on all-cause mortality, MI, and stroke was compared using propensity score-weighted Cox proportional hazard models., Results: Normalization of serum TT levels in nonsmokers was associated with a significant decrease in all-cause mortality (hazard ratio [HR]=0.526; 95% CI, 0.477-0.581; P <.001) and MI (HR=0.717; 95% CI, 0.522-0.986; P <.001). Among current smokers, normalization of serum TT levels was associated with a significant decrease in only all-cause mortality (HR=0.563; 95% CI, 0.488-0.649; P <.001) without benefit in MI (HR=1.096; 95% CI, 0.698-1.720; P =.69). Importantly, compared with nonsmokers with normalized TT, all-cause mortality (HR=1.242; 95% CI, 1.104-1.396; P <.001), MI (HR=1.706; 95% CI, 1.242-2.342; P =.001), and stroke (HR=1.590; 95% CI, 1.013-2.495; P =.04) were significantly higher in current smokers with normalized TT., Conclusion: We conclude that active CS may negate the protective effect of testosterone level normalization on all-cause mortality and MI after TRT.