Faculty Bibliography

BACKGROUND:Despite evidence of socio-demographic disparities in outcomes of COVID-19, little is known about characteristics and clinical outcomes of patients admitted to public hospitals during the COVID-19 outbreak. OBJECTIVE:To assess demographics, comorbid conditions, and clinical factors associated with critical illness and mortality among patients diagnosed with COVID-19 at a public hospital in New York City (NYC) during the first month of the COVID-19 outbreak. DESIGN/METHODS:Retrospective chart review of patients diagnosed with COVID-19 admitted to NYC Health + Hospitals / Bellevue Hospital from March 9th to April 8th, 2020. RESULTS:A total of 337 patients were diagnosed with COVID-19 during the study period. Primary analyses were conducted among those requiring supplemental oxygen (n = 270); half of these patients (135) were admitted to the intensive care unit (ICU). A majority were male (67.4%) and the median age was 58 years. Approximately one-third (32.6%) of hypoxic patients managed outside the ICU required non-rebreather or non-invasive ventilation. Requirement of renal replacement therapy occurred in 42.3% of ICU patients without baseline end-stage renal disease. Overall, 30-day mortality among hypoxic patients was 28.9% (53.3% in the ICU, 4.4% outside the ICU). In adjusted analyses, risk factors associated with mortality included dementia (adjusted risk ratio (aRR) 2.11 95%CI 1.50-2.96), age 65 or older (aRR 1.97, 95%CI 1.31-2.95), obesity (aRR 1.37, 95%CI 1.07-1.74), and male sex (aRR 1.32, 95%CI 1.04-1.70). CONCLUSION/CONCLUSIONS:COVID-19 demonstrated severe morbidity and mortality in critically ill patients. Modifications in care delivery outside the ICU allowed the hospital to effectively care for a surge of critically ill and severely hypoxic patients.

The opioid/overdose crisis in the United States and Canada has claimed hundreds of thousands of lives and has become a major field for research and interventions. It has embroiled pharmaceutical companies in lawsuits and possible bankruptcy filings. Effective interventions and policies toward this and future drug-related outbreaks may be improved by understanding the sociostructural roots of this outbreak. Much of the literature on roots of the opioid/overdose outbreak focuses on (1) the actions of pharmaceutical companies in inappropriately promoting the use of prescription opioids; (2) "deaths of despair" based on the deindustrialization of much of rural and urban Canada and the United States, and on the related marginalization and demoralization of those facing lifetimes of joblessness or precarious employment in poorly paid, often dangerous work; and (3) increase in occupationally-induced pain and injuries in the population. All three of these roots of the crisis-pharmaceutical misconduct and unethical marketing practices, despair based on deindustrialization and increased occupational pain-can be traced back, in part, to what has been called the "one-sided class war" that became prominent in the 1970s, became institutionalized as neo-liberalism in and since the 1980s, and may now be beginning to be challenged. We describe this one-sided class war, and how processes it sparked enabled pharmaceutical corporations in their misconduct, nurtured individualistic ideologies that fed into despair and drug use, weakened institutions that created social support in communities, and reduced barriers against injuries and other occupational pain at workplaces by reducing unionization, weakening surviving unions, and weakening the enforcement of rules about workplace safety and health. We then briefly discuss the implications of this analysis for programs and policies to mitigate or reverse the opioid/overdose outbreak.

INTRODUCTION/BACKGROUND:Prescription Drug Monitoring Program data can provide insights into a patient's likelihood of an opioid overdose, yet clinicians and public health officials lack indicators to identify individuals at highest risk accurately. A predictive model was developed and validated using Prescription Drug Monitoring Program prescription histories to identify those at risk for fatal overdose because of any opioid or illicit opioids. METHODS:From December 2018 to July 2019, a retrospective cohort analysis was performed on Maryland residents aged 18-80 years with a filled opioid prescription (n=565,175) from January to June 2016. Fatal opioid overdoses were identified from the Office of the Chief Medical Examiner and were linked at the person-level with Prescription Drug Monitoring Program data. Split-half technique was used to develop and validate a multivariate logistic regression with a 6-month lookback period and assessed model calibration and discrimination. RESULTS:Predictors of any opioid-related fatal overdose included male sex, age 65-80 years, Medicaid, Medicare, 1 or more long-acting opioid fills, 1 or more buprenorphine fills, 2 to 3 and 4 or more short-acting schedule II opioid fills, opioid days' supply ≥91 days, average morphine milligram equivalent daily dose, 2 or more benzodiazepine fills, and 1 or more muscle relaxant fills. Model discrimination for the validation cohort was good (area under the curve: any, 0.81; illicit, 0.77). CONCLUSIONS:A model for predicting fatal opioid overdoses was developed using Prescription Drug Monitoring Program data. Given the recent national epidemic of deaths involving heroin and fentanyl, it is noteworthy that the model performed equally well in identifying those at risk for overdose deaths from both illicit and prescription opioids.

BACKGROUND:Predicting which individuals who are prescribed buprenorphine for opioid use disorder are most likely to experience an overdose can help target interventions to prevent relapse and subsequent consequences. METHODS:We used Maryland prescription drug monitoring data from 2015 to identify risk factors for nonfatal opioid overdoses that were identified in hospital discharge records in 2016. We developed a predictive risk model for prospective nonfatal opioid overdoses among buprenorphine patients (N = 25,487). We estimated a series of models that included demographics plus opioid, buprenorphine and benzodiazepine prescription variables. We applied logistic regression to generate performance measures. RESULTS:About 3.24% of the study cohort had ≥1 nonfatal opioid overdoses. In the model with all predictors, odds of nonfatal overdoses among buprenorphine patients were higher among males (OR = 1.39, 95% CI:1.21-1.62) and those with more buprenorphine pharmacies (OR = 1.19, 95% CI:1.11-1.28), 1+ buprenorphine prescription paid by Medicaid (OR = 1.21, 95% CI:1.02-1.48), Medicare (OR = 1.93, 95% CI:1.63-2.43), or a commercial plan (OR = 1.98, 95% CI:1.30-2.89), 1+ opioid prescription paid by Medicare (OR = 1.30, 95% CI:1.03-1.68), and more benzodiazepine prescriptions (OR = 1.04, 95% CI:1.02-1.05). The odds were lower among those with longer days of buprenorphine (OR = 0.64, 95% CI:0.60-0.69) or opioid (OR = 0.79, 95% CI:0.65-0.95) supply. The model had moderate predictive ability (c-statistic = 0.69). CONCLUSIONS:Several modifiable risk factors, such as length of buprenorphine treatment, may be targets for interventions to improve clinical care and reduce harms. This model could be practically implemented with common prescription-related information and allow payers and clinical systems to better target overdose risk reduction interventions, such as naloxone distribution.

BACKGROUND:Opioid use disorder (OUD) is highly prevalent among justice-involved individuals. While risk for overdose and other adverse consequences of opioid use are heightened among this population, most justice-involved individuals and other high-risk groups experience multiple barriers to engagement in opioid agonist treatment. METHODS:This paper describes the development of Project Connections at Re-Entry (PCARE), a low-threshold buprenorphine treatment program that engages vulnerable patients in care through a mobile van parked directly outside the Baltimore City Jail. Patients are referred by jail staff or can walk in from the street. The clinical team includes an experienced primary care physician who prescribes buprenorphine, a nurse, and a peer recovery coach. The team initiates treatment for those with OUD and refers those with other needs to appropriate providers. Once stabilized, patients are transitioned to longer-term treatment programs or primary care for buprenorphine maintenance. This paper describes the process of developing this program, patient characteristics and initial outcomes for the first year of the program, and implications for public health practice. RESULTS:From November 15, 2017 through November 30, 2018, 220 people inquired about treatment services and completed an intake interview, and 190 began treatment with a buprenorphine/naloxone prescription. Those who initiated buprenorphine were primarily male (80.1%), African American (85.1%), had a mean age of 44.1 (SD = 12.2), and a mean of 24.0 (SD = 13.6) years of opioid use. The majority of patients (94.4%) had previous criminal justice involvement, were unemployed (72.9%) and were unstably housed (70.8%). Over a third (32.1%) of patients had previously overdosed. Of those who began treatment, 67.9% returned for a second visit or more, and 31.6% percent were still involved in treatment after 30 days. Of those who initiated care, 20.5% have been transferred to continue buprenorphine treatment at a partnering site. CONCLUSIONS:The PCARE program illustrates the potential for low-threshold buprenorphine treatment to engage populations who are justice-involved and largely disconnected from care. While more work is needed to improve treatment retention among vulnerable patients and engaging persons in care directly after release from detention, offering on-demand, flexible and de-stigmatizing treatment may serve as a first point to connect high-risk populations with the healthcare system and interventions that reduce risk for overdose and related harms.

BACKGROUND AND OBJECTIVES/OBJECTIVE:During adolescence, mental health problems may increase the risk of initiating combustible cigarette use. However, it is unknown if this association extends to electronic cigarettes (e-cigarettes). We examined whether internalizing and externalizing problems were associated with initiation of e-cigarette, combustible cigarette, and dual-product use among adolescents. METHODS:Participants were drawn from the Population Assessment of Tobacco and Health Study, a nationally representative longitudinal study of US adolescents followed from 2013 to 2015. The study sample included 7702 adolescents aged 12 to 17 years who at baseline reported no lifetime use of tobacco products. We examined the respective associations between baseline internalizing and externalizing problems and initiating use of e-cigarettes, combustible cigarettes, or both at 1-year follow-up. RESULTS:Compared with adolescents with low externalizing problems, adolescents with high externalizing problems were significantly more likely to initiate use of e-cigarettes (adjusted relative risk ratio [aRRR] = 2.78; 95% confidence interval [CI]: 1.76-4.40), combustible cigarettes (aRRR = 5.59; 95% CI: 2.63-11.90), and both products (aRRR = 2.23; 95% CI: 1.15-4.31). Adolescents with high internalizing problems were at increased risk of initiating use of e-cigarettes (aRRR = 1.61; 95% CI: 1.12-2.33) but not combustible cigarettes or both products. CONCLUSIONS:Mental health problems are associated with increased risk for initiating e-cigarette, combustible cigarette, and dual-product use in adolescence. This association is more consistent for externalizing problems than internalizing problems. Addressing mental health problems could be a promising target for preventing initiation of nicotine- and/or tobacco-product use by adolescents.

Prior studies on substance use in Brazil have not focused on opioid misuse, previously thought to be nearly non-existent. This paper presents new findings on heroin and non-medical use of opioid analgesics. Data come from the 2015 Brazilian Household Survey on Substance Use (BHSU-3), a nationally representative survey estimating epidemiological parameters related to substance use by residents across Brazil. BHSU-3 used stratified multi-stage probability sampling across multiple geographic domains of interest, resulting in 16,273 interviews with household residents. Lifetime heroin use among Brazilians was 0.3 (95% C.I:0.2-0.4). Lifetime, past-year, and past-month non-medical use of opioid analgesics were respectively 2.9 (95%C.I.:2.3-3.4), 1.4 (95%C.I.:1.1-1.7) and 0.6 (95%C.I.:0.4-0.8). Past-year prevalence of non-medical opioid analgesics use was lower among males [Prevalence Ratio (PR): 0.54 (95% C.I.:0.36-0.78)], those aged 12-24 [0.56 (95% C.I.:0.34-0.92)], persons with monthly family incomes between R$1,501-3,000 [0.59 (95% C.I.:0.38-0.92)] or greater than R$3,000 [0.64 (95% C.I.:0.42-0.98)], and persons who were unemployed [0.65 (95% C.I.:0.46-0.92)]. Non-medical use of opioids in Brazil may be more prevalent than previously recognised. Proper measurement and evaluation of opioid misuse across Brazil and other Latin American countries is critical to understand and prevent opioid-related harms.