Mortality Following Nonfatal Opioid and Sedative/Hypnotic Drug Overdose.
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ABSTRACT: Introduction
Opioid and sedative/hypnotic drug overdoses are major causes of morbidity in the U.S. This study compares 12-month incidence of fatal unintentional drug overdose, suicide, and other mortality among emergency department patients presenting with nonfatal opioid or sedative/hypnotic overdose.Methods
This is a retrospective cohort study using statewide, longitudinally linked emergency department patient record and mortality data from California. Participants comprised all residents presenting to a licensed emergency department at least once in 2009-2011 with nonfatal unintentional opioid overdose, sedative/hypnotic overdose, or neither (a 5% random sample). Participants were followed for 1 year after index emergency department presentation to assess death from unintentional overdose, suicide, or other causes, ascertained using ICD-10 codes. Absolute death rates per 100,000 person years and standardized mortality ratios relative to the general population were calculated. Data were analyzed February-August 2019.Results
Following the index emergency department visit, unintentional overdose death rates per 100,000 person years were 1,863 following opioid overdose, 342 following sedative/hypnotic overdose, and 31 for reference patients without an index overdose (respective standardized mortality ratios of 106.1, 95% CI=95.2, 116.9; 24.5, 95% CI=21.3, 27.6; and 2.6, 95% CI=2.2, 3.0). Suicide mortality rates per 100,000 were 319, 174, and 32 following opioid overdose, sedative/hypnotic overdose, and reference visits, respectively. Natural causes mortality rates per 100,000 were 8,058 (opioid overdose patients), 17,301 (sedative/hypnotic overdose patients), and 3,097 (reference patients).Conclusions
Emergency department patients with nonfatal opioid or sedative/hypnotic drug overdose have exceptionally high risks of death from unintentional overdose, suicide, and other causes. Emergency department-based interventions offer potential for reducing these patients' overdose and other mortality risks.
SUBMITTER: Goldman-Mellor S
PROVIDER: S-EPMC7311279 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ImportanceA recent increase in patients presenting with nonfatal opioid overdoses has focused clinical attention on characterizing their risks of premature mortality.ObjectiveTo describe all-cause mortality rates, selected cause-specific mortality rates, and standardized mortality rate ratios (SMRs) of adults during their first year after nonfatal opioid overdose.Design, setting, and participantsThis US national longitudinal study assesses a cohort of patients aged 18 to 64 years who were Medicaid beneficiaries and experienced nonfatal opioid overdoses. The Medicaid data set included the years 2001 through 2007. Death record information was obtained from the National Death Index. Data analysis occurred from October 2017 to January 2018.Main outcomes and measuresCrude mortality rates per 100 000 person-years were determined in the first year after nonfatal opioid overdose. Standardized mortality rate ratios (SMR) were estimated for all-cause and selected cause-specific mortality standardized to the general population with respect to age, sex, and race/ethnicity.ResultsThe primary cohort included 76 325 adults and 66 736 person-years of follow-up. During the first year after nonfatal opioid overdose, there were 5194 deaths, the crude death rate was 778.3 per 10 000 person-years, and the all-cause SMR was 24.2 (95% CI, 23.6-24.9). The most common immediate causes of death were substance use-associated diseases (26.2%), diseases of the circulatory system (13.2%), and cancer (10.3%). For every cause examined, SMRs were significantly elevated, especially with respect to drug use-associated diseases (SMR, 132.1; 95% CI, 125.6-140.0), HIV (SMR, 45.9; 95% CI, 39.5-53.0), chronic respiratory diseases (SMR, 41.1; 95% CI, 36.0-46.8), viral hepatitis (SMR, 30.6; 95% CI, 22.9-40.2), and suicide (SMR, 25.9; 95% CI, 22.6-29.6), particularly including suicide among females (SMR, 47.9; 95% CI, 39.8-52.3).Conclusions and relevanceIn a US national cohort of adults who had experienced a nonfatal opioid overdose, a marked excess of deaths was attributable to a wide range of substance use-associated, mental health, and medical conditions, underscoring the importance of closely coordinating the substance use, mental health, and medical care of this patient population.
| S-EPMC6143082 | biostudies-literature
Project description:Background:Opioid overdose survivors have an increased risk for death. Whether use of medications for opioid use disorder (MOUD) after overdose is associated with mortality is not known. Objective:To identify MOUD use after opioid overdose and its association with all-cause and opioid-related mortality. Design:Retrospective cohort study. Setting:7 individually linked data sets from Massachusetts government agencies. Participants:17 568 Massachusetts adults without cancer who survived an opioid overdose between 2012 and 2014. Measurements:Three types of MOUD were examined: methadone maintenance treatment (MMT), buprenorphine, and naltrexone. Exposure to MOUD was identified at monthly intervals, and persons were considered exposed through the month after last receipt. A multivariable Cox proportional hazards model was used to examine MOUD as a monthly time-varying exposure variable to predict time to all-cause and opioid-related mortality. Results:In the 12 months after a nonfatal overdose, 2040 persons (11%) enrolled in MMT for a median of 5 months (interquartile range, 2 to 9 months), 3022 persons (17%) received buprenorphine for a median of 4 months (interquartile range, 2 to 8 months), and 1099 persons (6%) received naltrexone for a median of 1 month (interquartile range, 1 to 2 months). Among the entire cohort, all-cause mortality was 4.7 deaths (95% CI, 4.4 to 5.0 deaths) per 100 person-years and opioid-related mortality was 2.1 deaths (CI, 1.9 to 2.4 deaths) per 100 person-years. Compared with no MOUD, MMT was associated with decreased all-cause mortality (adjusted hazard ratio [AHR], 0.47 [CI, 0.32 to 0.71]) and opioid-related mortality (AHR, 0.41 [CI, 0.24 to 0.70]). Buprenorphine was associated with decreased all-cause mortality (AHR, 0.63 [CI, 0.46 to 0.87]) and opioid-related mortality (AHR, 0.62 [CI, 0.41 to 0.92]). No associations between naltrexone and all-cause mortality (AHR, 1.44 [CI, 0.84 to 2.46]) or opioid-related mortality (AHR, 1.42 [CI, 0.73 to 2.79]) were identified. Limitation:Few events among naltrexone recipients preclude confident conclusions. Conclusion:A minority of opioid overdose survivors received MOUD. Buprenorphine and MMT were associated with reduced all-cause and opioid-related mortality. Primary Funding Source:National Center for Advancing Translational Sciences of the National Institutes of Health.
| S-EPMC6387681 | biostudies-literature
Project description:Importance:Timely initiation and referral to treatment for patients with opioid use disorder seen in the emergency department is associated with reduced mortality. It is not known how often commercially insured adults obtain follow-up treatment after nonfatal opioid overdose. Objective:To investigate the incidence of follow-up treatment following emergency department discharge after nonfatal opioid overdose and patient characteristics associated with receipt of follow-up treatment. Design, Setting, and Participants:A retrospective cohort study was conducted using an administrative claims database for a large US commercial insurer, from October 1, 2011, to September 30, 2016. Data analysis was performed from May 1, 2019, to September 26, 2019. Adult patients discharged from the emergency department after an index opioid overdose (no overdose in the preceding 90 days) were included. Patients with cancer and without continuous insurance enrollment were excluded. Main Outcomes and Measures:The primary outcome was follow-up treatment in the 90 days following overdose, defined as a combined outcome of claims for treatment encounters or medications for opioid use disorder (buprenorphine and naltrexone). Analysis was stratified by whether patients received treatment for opioid use disorder in the 90 days before the overdose. Logistic regression models were used to identify patient characteristics associated with receipt of follow-up treatment. Marginal effects were used to report the average adjusted probability and absolute risk differences (ARDs) in follow-up for different patient characteristics. Results:A total of 6451 patients were identified with nonfatal opioid overdose; the mean (SD) age was 45.0 (19.3) years, 3267 were women (50.6%), and 4676 patients (72.5%) reported their race as non-Hispanic white. A total of 1069 patients (16.6%; 95% CI, 15.7%-17.5%) obtained follow-up treatment within 90 days after the overdose. In adjusted analysis of patients who did not receive treatment before the overdose, black patients were half as likely to obtain follow-up compared with non-Hispanic white patients (ARD, -5.9%; 95% CI, -8.6% to -3.6%). Women (ARD, -1.7%; 95% CI, -3.3% to -0.5%) and Hispanic patients (ARD, -3.5%; 95% CI, -6.1% to -0.9%) were also less likely to obtain follow-up. For each additional year of age, patients were 0.2% less likely to obtain follow-up (95% CI, -0.3% to -0.1%). Conclusions and Relevance:Efforts to improve the low rate of timely follow-up treatment following opioid overdose may seek to address sex, race/ethnicity, and age disparities.
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Project description:2,2,2-Trichloroethanol (TCE) is the active form of the sedative hypnotic drug chloral hydrate, one of the oldest sleep medications in the market. Understanding of TCE's action mechanisms to its many targets, particularly within the ion channel family, could benefit from the state-of-the-art computational molecular studies. In this direction, we employed de novo modeling aided by the force field toolkit to develop CHARMM36-compatible TCE parameters. The classical potential energy function was calibrated targeting molecular conformations, local interactions with water molecules, and liquid bulk properties. Reference data comes from both tabulated thermodynamic properties and ab initio calculations at the MP2 level. TCE solvation free energy calculations in water and oil reproduce a lipophilic, yet nonhydrophobic, behavior. Indeed, the potential mean force profile for TCE partition through the phospholipid bilayer reveals the sedative's preference for the interfacial region. The calculated partition coefficient also matches experimental measures. Further validation of the proposed parameters is supported by the model's ability to recapitulate quenching experiments demonstrating TCE binding to bovine serum albumin.
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Project description: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.
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Project description:Background:Benzodiazepines and sedative-hypnotic drugs (BZD/SHDs), such as zopiclone and the antidepressant trazodone, pose risks such as falls, fractures, and confusion, especially for older adults. Use of these drugs in the acute care setting is poorly understood. Objectives:To determine the point prevalence and characteristics of use of BZD/SHDs in hospitals in Nova Scotia, Canada. Methods:A point prevalence survey was conducted for adults admitted to all hospitals with at least 30 acute care beds between May and August 2016. Drugs administered intravenously, patients in long-term care, and patients receiving mental health services, addiction treatment, or critical care were excluded. The proportion of included patients who had received a BZD/SHD within the 24 h before the start of the survey was determined. A descriptive statistical analysis was performed. Results:Overall BZD/SHD prevalence was 34.6% (487/1409) across the 16 eligible hospitals. The average age was 70.3 years, and 150 (30.8%) of the patients were 80 years or older. Among the 585 prescriptions for these patients, commonly used drugs were zopiclone (32.0%), lorazepam (21.9%), and trazodone (21.9%). The most common indications for use were bedtime/daytime sedation (60.0%) and anxiety (12.5%). More than half of the prescriptions (55.7%) had been initiated at home, 37.6% were started in hospital, and the place of initiation was unknown for 6.7%. Benzodiazepines were prescribed more frequently to patients under 65 years than those 80 years or older (41.3% versus 22.2%, p < 0.001) whereas trazodone was more frequently prescribed to the older of these 2 age groups (52.7% versus 14.3%, p < 0.001). Conclusions:BZD/SHDs were frequently used by hospitalized adult patients in Nova Scotia. Trazodone appears to have been substituted for benzodiazepines in the oldest age group. Pharmacists should direct their efforts toward preventing inappropriate initiation of BZD/SHDs in hospital, particularly for elderly patients.
| S-EPMC7308153 | biostudies-literature
Project description:BackgroundOpioid overdose (OD) and related deaths have significantly increased in the United States over the last 2 decades. Existing studies have mostly focused on demographic and clinical risk factors in noncritical care settings. Social and behavioral determinants of health (SBDH) are infrequently coded in the electronic health record (EHR) and usually buried in unstructured EHR notes, reflecting possible gaps in clinical care and observational research. Therefore, SBDH often receive less attention despite being important risk factors for OD. Natural language processing (NLP) can alleviate this problem.ObjectiveThe objectives of this study were two-fold: First, we examined the usefulness of NLP for SBDH extraction from unstructured EHR text, and second, for intensive care unit (ICU) admissions, we investigated risk factors including SBDH for nonfatal OD.MethodsWe performed a cross-sectional analysis of admission data from the EHR of patients in the ICU of Beth Israel Deaconess Medical Center between 2001 and 2012. We used patient admission data and International Classification of Diseases, Ninth Revision (ICD-9) diagnoses to extract demographics, nonfatal OD, SBDH, and other clinical variables. In addition to obtaining SBDH information from the ICD codes, an NLP model was developed to extract 6 SBDH variables from EHR notes, namely, housing insecurity, unemployment, social isolation, alcohol use, smoking, and illicit drug use. We adopted a sequential forward selection process to select relevant clinical variables. Multivariable logistic regression analysis was used to evaluate the associations with nonfatal OD, and relative risks were quantified as covariate-adjusted odds ratios (aOR).ResultsThe strongest association with nonfatal OD was found to be drug use disorder (aOR 8.17, 95% CI 5.44-12.27), followed by bipolar disorder (aOR 2.69, 95% CI 1.68-4.29). Among others, major depressive disorder (aOR 2.57, 95% CI 1.12-5.88), being on a Medicaid health insurance program (aOR 2.26, 95% CI 1.43-3.58), history of illicit drug use (aOR 2.09, 95% CI 1.15-3.79), and current use of illicit drugs (aOR 2.06, 95% CI 1.20-3.55) were strongly associated with increased risk of nonfatal OD. Conversely, Blacks (aOR 0.51, 95% CI 0.28-0.94), older age groups (40-64 years: aOR 0.65, 95% CI 0.44-0.96; >64 years: aOR 0.16, 95% CI 0.08-0.34) and those with tobacco use disorder (aOR 0.53, 95% CI 0.32-0.89) or alcohol use disorder (aOR 0.64, 95% CI 0.42-1.00) had decreased risk of nonfatal OD. Moreover, 99.82% of all SBDH information was identified by the NLP model, in contrast to only 0.18% identified by the ICD codes.ConclusionsThis is the first study to analyze the risk factors for nonfatal OD in an ICU setting using NLP-extracted SBDH from EHR notes. We found several risk factors associated with nonfatal OD including SBDH. SBDH are richly described in EHR notes, supporting the importance of integrating NLP-derived SBDH into OD risk assessment. More studies in ICU settings can help health care systems better understand and respond to the opioid epidemic.
| S-EPMC8663596 | biostudies-literature
Project description:ObjectiveTo determine the association between preoperative benzodiazepine and nonbenzodiazepine receptor agonist ("Z-drugs") use and adverse outcomes after surgery.BackgroundPrescriptions for benzodiazepines and Z-drugs have increased over the past decade. Despite this, the association of preoperative benzodiazepines and Z-drug receipt with adverse outcomes after surgery is unknown.MethodsUsing the Optum Clinformatics Datamart, we performed a retrospective cohort study of adults 18 years or older who underwent any of 10 common surgical procedures between 2010 and 2015. The principal exposure was one or more filled prescriptions for a benzodiazepine or Z-drug in the 90 days before surgery. The primary outcome was any emergency department visit or hospital admission for either (1) a drug related adverse medical event or overdose or (2) a traumatic injury in the 30 days after surgery.ResultsOf 785,346 patients meeting inclusion criteria, 94,887 (12.1%) filled a preoperative prescription for a benzodiazepine or Z-drug. From multivariable logistic regression, benzodiazepine or Z-drug use was associated with an increased odds of an adverse postoperative event [odds ratio 1.13; 95% confidence interval: 1.08-1.18). In a separate regression, coprescription of benzodiazepines or Z-drugs with opioids was associated with a 1.45 odds of an adverse postoperative event (95% confidence interval: 1.37-1.53).ConclusionsPreoperative benzodiazepines and Z-drug use is common and associated with increased odds of adverse outcomes after surgery, particularly when coprescribed with opioids. Counseling on appropriate benzodiazepine and Z-drug use in advance of elective surgery may potentially increase the safety of surgical care.
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Project description:Prescription opioids (POs) such as oxycodone and hydrocodone are highly effective medications for pain management, yet they also present a substantial risk for abuse and addiction. The consumption of POs has been escalating worldwide, resulting in tens of thousands of deaths due to overdose each year. Pharmacokinetic strategies based upon vaccination present an attractive avenue to suppress PO abuse. Herein, the preparation of two active PO vaccines is described that were found to elicit high-affinity antiopioid antibodies through a structurally congruent drug-hapten design. Administration of these vaccines resulted in a significant blockade of opioid analgesic activity, along with an unprecedented increase in drug serum half-life and protection against lethal overdose.
| S-EPMC6434689 | biostudies-literature
Project description:Study objectivePeople with opioid use disorder are vulnerable to disruptions in access to addiction treatment and social support during the COVID-19 pandemic. Our study objective was to understand changes in emergency department (ED) utilization following a nonfatal opioid overdose during COVID-19 compared to historical controls in 6 healthcare systems across the United States.MethodsOpioid overdoses were retrospectively identified among adult visits to 25 EDs in Alabama, Colorado, Connecticut, North Carolina, Massachusetts, and Rhode Island from January 2018 to December 2020. Overdose visit counts and rates per 100 all-cause ED visits during the COVID-19 pandemic were compared with the levels predicted based on 2018 and 2019 visits using graphical analysis and an epidemiologic outbreak detection cumulative sum algorithm.ResultsOverdose visit counts increased by 10.5% (n=3486; 95% confidence interval [CI] 4.18% to 17.0%) in 2020 compared with the counts in 2018 and 2019 (n=3020 and n=3285, respectively), despite a 14% decline in all-cause ED visits. Opioid overdose rates increased by 28.5% (95% CI 23.3% to 34.0%) from 0.25 per 100 ED visits in 2018 to 2019 to 0.32 per 100 ED visits in 2020. Although all 6 studied health care systems experienced overdose ED visit rates more than the 95th percentile prediction in 6 or more weeks of 2020 (compared with 2.6 weeks as expected by chance), 2 health care systems experienced sustained outbreaks during the COVID-19 pandemic.ConclusionDespite decreases in ED visits for other medical emergencies, the numbers and rates of opioid overdose-related ED visits in 6 health care systems increased during 2020, suggesting a widespread increase in opioid-related complications during the COVID-19 pandemic. Expanded community- and hospital-based interventions are needed to support people with opioid use disorder and save lives during the COVID-19 pandemic.
| S-EPMC8449788 | biostudies-literature