Trajectories of Self-Reported Opioid Use Among Patients With HIV Engaged in Care: Results From a National Cohort Study.

BACKGROUND: No prior studies have characterized long-term patterns of opioid use regardless of source or reason for use among patients with HIV (PWH). We sought to identify trajectories of self-reported opioid use and their correlates among a national sample of PWH engaged in care. SETTING: Veterans Aging Cohort Study, a prospective cohort including PWH receiving care at 8 US Veterans Health Administration (VA) sites. METHODS: Between 2002 and 2018, we assessed past year opioid use frequency based on self-reported "prescription painkillers" and/or heroin use at baseline and follow-up. We used group-based trajectory models to identify opioid use trajectories and multinomial logistic regression to determine baseline factors independently associated with escalating opioid use compared to stable, infrequent use. RESULTS: Among 3702 PWH, we identified 4 opioid use trajectories: (1) no lifetime use (25%); (2) stable, infrequent use (58%); (3) escalating use (7%); and (4) de-escalating use (11%). In bivariate analysis, anxiety; pain interference; prescribed opioids, benzodiazepines and gabapentinoids; and marijuana use were associated with escalating opioid group membership compared to stable, infrequent use. In multivariable analysis, illness severity, pain interference, receipt of prescribed benzodiazepine medications, and marijuana use were associated with escalating opioid group membership compared to stable, infrequent use. CONCLUSION: Among PWH engaged in VA care, 1 in 15 reported escalating opioid use. Future research is needed to understand the impact of psychoactive medications and marijuana use on opioid use and whether enhanced uptake of evidence-based treatment of pain and psychiatric symptoms can prevent escalating use among PWH

Relation of age and race with hospital death after acute myocardial infarction

BACKGROUND: Prior studies have suggested that young blacks with acute myocardial infarction (AMI) may have higher hospital mortality rates than whites of similar age. However, the influence of age and race on short-term death has not been explored in detail. We examined the relation of age and race on short-term death in a large AMI population and ascertained the factors that may have contributed to differences in mortality rates. METHODS: We compared the crude and adjusted hospital mortality rates stratified by age among 40,903 blacks and 501,995 whites with AMI enrolled in the National Registry of Myocardial Infarction-2 in 1482 participating US hospitals from June 1994 through March 1998. RESULTS: Overall crude mortality was lower among blacks compared with whites (10.9% vs 12.0%, P \u3c.0001). However, blacks had a significantly higher crude mortality rate compared with the whites in the age groups \u3c65 years (\u3c45 years, and 5-year age groups between 45 and 64 years). There was a statistically significant interaction between age and black race on hospital death (P value for interaction \u3c.001). Each 5-year decrement in age from 85 years was associated with 7.2% higher odds of death in blacks compared with whites (95% CI, 5.7% to 7.6%). After adjusting for differences in the baseline, clinical presentation, early treatment, and hospital characteristics, 5-year decrements in age was still associated with increases in the odds for death in blacks compared with whites (5.4%; 95% CI, 3.6% to 7.2%). This interaction between age and black race was present in both sexes but was stronger among men. CONCLUSIONS: Blacks younger than 65 years had higher hospital mortality rates compared with whites hospitalized for AMI, and decreasing age was associated with progressively higher risk of hospital death for blacks. Differences in the clinical presentation, early treatment, and hospital characteristics could only partly explain this age-race interaction

Associations between stopping prescriptions for opioids, length of opioid treatment, and overdose or suicide deaths in US veterans: observational evaluation.

OBJECTIVE: To examine the associations between stopping treatment with opioids, length of treatment, and death from overdose or suicide in the Veterans Health Administration. DESIGN: Observational evaluation. SETTING: Veterans Health Administration. PARTICIPANTS: 1 394 102 patients in the Veterans Health Administration with an outpatient prescription for an opioid analgesic from fiscal year 2013 to the end of fiscal year 2014 (1 October 2012 to 30 September 2014). MAIN OUTCOME MEASURES: A multivariable Cox non-proportional hazards regression model examined death from overdose or suicide, with the interaction of time varying opioid cessation by length of treatment (≤30, 31-90, 91-400, and >400 days) as the main covariates. Stopping treatment with opioids was measured as the time when a patient was estimated to have no prescription for opioids, up to the end of the next fiscal year (2014) or the patient's death. RESULTS: 2887 deaths from overdose or suicide were found. The incidence of stopping opioid treatment was 57.4% (n799 668) overall, and based on length of opioid treatment was 32.0% (≤30 days), 8.7% (31-90 days), 22.7% (91-400 days), and 36.6% (>400 days). The interaction between stopping treatment with opioids and length of treatment was significant (P400 days). Descriptive life table data suggested that death rates for overdose or suicide increased immediately after starting or stopping treatment with opioids, with the incidence decreasing over about three to 12 months. CONCLUSIONS: Patients were at greater risk of death from overdose or suicide after stopping opioid treatment, with an increase in the risk the longer patients had been treated before stopping. Descriptive data suggested that starting treatment with opioids was also a risk period. Strategies to mitigate the risk in these periods are not currently a focus of guidelines for long term use of opioids. The associations observed cannot be assumed to be causal; the context in which opioid prescriptions were started and stopped might contribute to risk and was not investigated. Safer prescribing of opioids should take a broader view on patient safety and mitigate the risk from the patient's perspective. Factors to address are those that place patients at risk for overdose or suicide after beginning and stopping opioid treatment, especially in the first three months

Buprenorphine Use and Courses of Care for Opioid Use Disorder Treatment Within the Veterans Health Administration.

Background Retention of patients in buprenorphine medication treatment for opioid use disorder (B-MOUD) reduces harms associated with opioid use disorder (OUD). We sought to characterize the patients receiving B-MOUD and courses of B-MOUD in a large healthcare system. Methods We conducted a retrospective, open cohort study of patients with OUD who either did or did not receive B-MOUD courses within the Veterans Health Administration (VHA) from January 2006 through July 2019, using VHA clinical data. We compared patients receiving or not receiving B-MOUD, characterized B-MOUD courses (e.g., length and doses), and examined persistence, across patient characteristics, over time. We used analyses for normally or non-normally distributed continuous variables, categorical data, and persistence over time (Kaplan-Meier persistence curves). Results We identified 255,726 Veterans with OUD; 40,431 (15.8%) had received 63,929 B-MOUD courses. Compared to patients with OUD without B-MOUD, patients with B-MOUD were younger, more often of white race, and had more co-morbidities. The frequency of new B-MOUD starts and prevalent B-MOUD patients ranged from 1550 and 1989 in 2007 to 8146 and 16,505 in 2018, respectively. The median duration of B-MOUD was 157 (IQR: 37–537) days for all courses and 33.8% patients had more than one course. The average proportion days covered was 90% (SD: 0.15), and the average prescribed daily dose was 13.44 (SD: 6.5). Conclusions Within a VHA B-MOUD cohort, courses increased more than 10-fold from 2006 to 2016 with nearly half of patients experiencing multiple courses. Patient demographics seem to dictate the length of courses