Identifying Risk Factors for Cardiovascular Events Among Active-Duty Service Members and Veterans Prescribed Nonsteroidal Anti-Inflammatory Drugs (NSAIDs).

Background: Oral NSAIDs are widely used analgesic medications for the treatment of musculoskeletal and inflammatory conditions. NSAIDs are associated with adverse effects that arise from COX enzyme inhibition including cardiovascular events. The combined role of patient and prescription factors associated with NSAID use on cardiovascular risk is not well characterized. Objective: The purpose of this study is to identify the risk factors with cardiovascular events among NSAID users. Methods: This study is a retrospective, nested case-control study, within the DAVINCI database, among active-duty service members and veterans with at least one NSAID pharmacy claim between fiscal year (FY) 2015-FY2020. Inclusion criteria individuals ≥18 years of age received a prescription NSAID for ≥7-day supply and a duration ≥1 month overall. Cases experienced nonfatal myocardial infarction, nonfatal stroke, or new onset heart failure. Ten controls were selected per case. Risk factors were identified through logistic regression modeling. Results: The risk factors with strongest association to the primary outcome included age starting at 45 up to 75 and older, the first 90 days of NSAID exposure, cerebrovascular disease, cardiomyopathy, and history of myocardial infarction. Cox-selectivity and dose did not appear to be clinically significant in their association with cardiovascular events. Conclusion: The results of this study indicate that age, initial NSAID exposure, and comorbidities are more predictive than NSAID-specific factors such as COX-selectivity and dose. The results provide the framework for development of a risk score to improve prediction of NSAID-associated cardiovascular events.

Relationship Between Body Mass Index and Diagnosis of Obesity in the Military Health System Active Duty Population.

OBJECTIVE: The overall rate of obesity is rising in the USA; this is also reflected in the military population. It is important that providers appropriately diagnose obesity and discuss treatment options with their patients.The purpose of this study was to investigate diagnosis of obesity compared to documented body mass index (BMI) in the military health system. METHODS: Institutional review board approval was obtained by the 59th Medical Wing (Lackland Air Force Base, Texas) as an exempt study. This study included active duty military service members aged 18-65 years who sought outpatient care at a military treatment facility from September 2013 to August 2018 with a weight within the range of 31.8-226.8 kg and height between 121.9 and 215.9 cm. Data were collected from the Clinical Data Repository vitals and M2 encounter data to determine the percentage of each sub-population with a diagnosis of obesity according to BMI (≥30 kg/m2) and International Classification of Diseases diagnosis codes. RESULTS: Using BMI, 19.2% of female and 26.8% of male service members can be diagnosed with obesity; however, only 42.2% and 35.1%, respectively, with a BMI ≥30 was diagnosed as such. This discrepancy was consistent among all service branches and BMI ranges. CONCLUSION: This study demonstrates that obesity is underdiagnosed compared to BMI. This may result in insufficient resources being provided to patients to reduce weight. Further investigation is warranted to identify causes of underdiagnosis and potential barriers to diagnosis.

IMPACT OF STRUCTURED INSULIN ORDER SETS ON INPATIENT HYPOGLYCEMIA AND GLYCEMIC CONTROL.

Objective: In hospitalized patients, glycemic excursions outside recommended glycemic targets have been associated with increased morbidity and mortality. Despite recommendations to avoid use of correctional insulin alone for managing hyperglycemia, this approach remains common. We performed a quality improvement project aimed at both reducing hypoglycemic events and promoting increased use of basal insulin by updating our insulin order sets to reflect clinical practice guideline recommendations. Methods: Brooke Army Medical Center correctional insulin order sets were modified to reflect higher treatment thresholds and targets, and a basal insulin order was added with a recommended weight-based starting dose. Pre- and postintervention analyses were performed. Patients were included if they were prescribed subcutaneous insulin during their hospital stay. The following outcomes were measured: (1) glucose levels, and (2) prescriptions for basal insulin. Results: A significant reduction in hypoglycemia events was noted following the intervention (glucose <70 mg/dL: 9.2% pre-intervention vs. 8.8% postintervention; glucose <55 mg/dL: 4.2% pre-intervention vs. 2.2% postintervention). When excluding patients that were ordered correctional insulin alone but did not receive a dose, an increase in basal insulin use was seen (50% pre-intervention vs. 61% postintervention). Rates and severity of hyperglycemia (glucose >180 mg/dL) remained unchanged. Conclusion: The alteration in insulin order set parameters resulted in a significant reduction in hypoglycemia without significant increases in hyperglycemia. Although basal insulin use increased, optimal dosing recommendations were not often utilized. Further interventions are necessary to reduce hyperglycemia. Abbreviations: CPOE = computerized provider order entry; EMR = electronic medical record; HbA1c = hemoglobin A1c; LOS = length of stay; QI = quality improvement; SSI = sliding scale insulin.