Characteristics of fatal opioid overdoses with stimulant involvement in Tennessee: A descriptive study using 2018 State Unintentional Drug Overdose Reporting System Data

Multinational appraisal of the epidemiological distribution of opioid fatalities: a systematic review and meta-analysis

Background

The global or multinational scientific evidence on the distribution of opioid fatality is unknown. Hence, the current study collects epidemiological characteristics to shed light on the ongoing global or multinational opioid crisis and to promote the development of public health prevention/management strategies.

Method

All documents on PRISMA standards were retrieved via electronic databases.

Results

Among the 47 articles relevant to our studies, which depict a total population size of 10,191 individuals, the prevalence of opioid fatal overdose was 15,022 (14.74%). Among the 47 articles, 14 of them reported the gender of the participants, with 22,125 (15.79%) male individuals and 7,235 (5.17%) female individuals, and the age distribution of the participants that was most affected by the overdose was as follows: 29,272 (31.13%) belonged to the 18-34-year-old age group and 25,316 (26.92%) belonged to the less than 18-year-old age group. Eighteen studies qualified for the meta-analysis of the multinational prevalence of fatal opioid overdose, depicting an overall pooled prevalence estimate of 19.66%, with 95% CIs (0.13-0.29), I2 = 99.76% determined using the random-effects model, and Q statistic of 7198.77 (p < 0.0001). The Egger test models of publication bias revealed an insubstantial level of bias (p = 0.015). The subgroup analysis of the study design (cohort or other) revealed that others have the highest prevalence estimate of 34.37, 95% CIs (0.1600-0.5901), I2 = 97.04%, and a sample size of less than 1,000 shows the highest prevalence of 34.66, 95% CIs (0.2039-0.5234), I2 = 97.82%, compared to that of more than 1,000 with a prevalence of 12.28, 95% CIs (0.0675-0.2131), I2 = 99.85%. The meta-regression analysis revealed that sample size (less-than or greater-than 1,000), (p = 0.0098; R2 = 3.83%) is significantly associated with the observed heterogeneity.

Conclusion

Research-based findings of fatal opioid overdose are grossly lacking in middle- and low-income nations. We established that there is a need for opioid fatality surveillance systems in developing nations.

Exploring trends in benzodiazepine-positive fatal drug overdoses in Tennessee, 2019-2021

BACKGROUND

Benzodiazepine-positive overdoses increased between 2019 and 2021 in Tennessee. We sought to determine the changes in the number and characteristics of prescription and illicit benzodiazepine-positive fatal drug overdoses during this period.

MATERIALS AND METHODS

A statewide study was conducted to determine changes in the number and characteristics of benzodiazepine-positive drug overdose decedents using 2019-2021 data from the Tennessee State Unintentional Drug Overdose Reporting System. The analyses were limited to Tennessee residents aged ≥ 18 years. A benzodiazepine-positive overdose was defined as any benzodiazepine on toxicology, regardless of the presence of other substances. Frequencies were generated to compare demographics, circumstances, prescription history, and toxicology between 2019 and 2021 for illicit and prescription benzodiazepine-positive fatal overdoses.

RESULTS

Between 2019 and 2021, 1666 benzodiazepine-positive unintentional or undetermined fatal drug overdoses out of 5916 total overdoses that occurred among adult Tennessee residents with available toxicological information. Prescription benzodiazepines were identified in 80.7% of deaths, whereas illicit benzodiazepines were identified in 12.0% of deaths. Many decedents had an anxiety disorder (45.5%), while over half of all decedents had a history of substance use disorder (52.3%). Most benzodiazepine-positive overdoses involved fentanyl (71.3%).

CONCLUSIONS

This analysis can inform local and regional public health workers to implement focused prevention and intervention efforts for people with co-occurring mental health conditions and substance use disorders to curb overdose epidemics among persons using benzodiazepines in Tennessee. Public health campaigns should focus on educating people on appropriate prescription medication use and the dangers of obtaining substances illicitly. Given the high proportion of opioids in this population, further education also is needed on the dangers of polysubstance drug use. The differences between prescription and illicit benzodiazepine-positive fatal overdoses indicate the need to develop substance-specific prevention and treatment strategies.

Differences in Opioid-Related Deaths in the Appalachian Region in 2018-2021 by State and Rural-Urban County Classification

Introduction The rapid increase in opioid-related deaths since the early 2000s is a major US public health concern. This crisis has transitioned from pharmaceuticals to illicit synthetic opioids and street mixtures. This epidemic has significantly impacted the Appalachian region. This study investigated opioid-related death rates among the Appalachian states, focusing on death rates among urban, suburban, and rural counties. Methods Opioid-related death data from 2018-2021 for the 13 states that make up the Appalachian region were collected using the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database. Opioid analgesic overdose deaths were defined using ICD-10 codes X40-X44, X60-X64, and Y10-Y14, where an opioid analgesic was also coded (T40.2-T40.4). US census data was used to calculate opioid-related death rates by population. Counties were classified as urban, suburban, and rural using the 2013 Rural-Urban Continuum Codes from the US Department of Agriculture. The data were descriptively broken down and reported as either percentages or means. Results Of the opioid-related deaths between 2018 and 2021, 498 counties were identified in the 13 Appalachian states as having reported at least 10 opioid-related deaths per year. Among these counties, 337 (67.7%) were classified as urban/metropolitan, 138 (27.7%) as suburban, and 23 (4.62%) as rural. Overall, mean opioid-related deaths by populations per 1000 among all counties were 0.24 in 2018, 0.24 in 2019, 0.33 in 2020, and 0.38 in 2021. For urban/metropolitan counties, opioid-related deaths per 1000 gradually increased from 0.23 in 2018 to 0.35 in 2021. For suburban counties, the mean opioid-related deaths per 1000 increased from 0.25 in 2018 to 0.43 in 2021. For rural counties, the mean opioid-related deaths per 1000 increased from 0.43 in 2018 to 0.62 in 2021. Conclusion Opioid-related deaths, on average and by population, have risen steadily in the Appalachian region from 2018-2021 across all geographic areas (urban/metropolitan, suburban, rural). Rural counties consistently showed the highest opioid-related deaths per population compared to urban/metropolitan and suburban areas. Addressing social determinants of health such as income level, education level, healthcare access, and community-based interventions is crucial in combating this issue. Community and health system interventions must be implemented to combat the disproportionately high rate of opioid prescribing in the Appalachian region.

Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study

BACKGROUND

Fatal drug overdose surveillance informs prevention but is often delayed because of autopsy report processing and death certificate coding. Autopsy reports contain narrative text describing scene evidence and medical history (similar to preliminary death scene investigation reports) and may serve as early data sources for identifying fatal drug overdoses. To facilitate timely fatal overdose reporting, natural language processing was applied to narrative texts from autopsies.

OBJECTIVE

This study aimed to develop a natural language processing-based model that predicts the likelihood that an autopsy report narrative describes an accidental or undetermined fatal drug overdose.

METHODS

Autopsy reports of all manners of death (2019-2021) were obtained from the Tennessee Office of the State Chief Medical Examiner. The text was extracted from autopsy reports (PDFs) using optical character recognition. Three common narrative text sections were identified, concatenated, and preprocessed (bag-of-words) using term frequency-inverse document frequency scoring. Logistic regression, support vector machine (SVM), random forest, and gradient boosted tree classifiers were developed and validated. Models were trained and calibrated using autopsies from 2019 to 2020 and tested using those from 2021. Model discrimination was evaluated using the area under the receiver operating characteristic, precision, recall, F1-score, and F2-score (prioritizes recall over precision). Calibration was performed using logistic regression (Platt scaling) and evaluated using the Spiegelhalter z test. Shapley additive explanations values were generated for models compatible with this method. In a post hoc subgroup analysis of the random forest classifier, model discrimination was evaluated by forensic center, race, age, sex, and education level.

RESULTS

A total of 17,342 autopsies (n=5934, 34.22% cases) were used for model development and validation. The training set included 10,215 autopsies (n=3342, 32.72% cases), the calibration set included 538 autopsies (n=183, 34.01% cases), and the test set included 6589 autopsies (n=2409, 36.56% cases). The vocabulary set contained 4002 terms. All models showed excellent performance (area under the receiver operating characteristic ≥0.95, precision ≥0.94, recall ≥0.92, F1-score ≥0.94, and F2-score ≥0.92). The SVM and random forest classifiers achieved the highest F2-scores (0.948 and 0.947, respectively). The logistic regression and random forest were calibrated (P=.95 and P=.85, respectively), whereas the SVM and gradient boosted tree classifiers were miscalibrated (P=.03 and P<.001, respectively). "Fentanyl" and "accident" had the highest Shapley additive explanations values. Post hoc subgroup analyses revealed lower F2-scores for autopsies from forensic centers D and E. Lower F2-score were observed for the American Indian, Asian, ≤14 years, and ≥65 years subgroups, but larger sample sizes are needed to validate these findings.

CONCLUSIONS

The random forest classifier may be suitable for identifying potential accidental and undetermined fatal overdose autopsies. Further validation studies should be conducted to ensure early detection of accidental and undetermined fatal drug overdoses across all subgroups.

Substance use and medical outcomes in those age 50 and older involving cocaine and metamfetamine reported to United States poison centers

CONTEXT

Cocaine and metamfetamine use and overdose deaths among United States adults have been increasing in recent years. We examined associations of medical outcomes with co-used opioids and other substances among cocaine, and metamfetamine exposures in people age ≥50 years (N = 9300) reported to the National Poison Data System, 2015-2021.

METHODS

We first described increases in these exposures over time. We fitted generalized linear models for a Poisson distribution with a log link, one for cocaine exposures and the other for metamfetamine exposures, to examine associations of medical outcomes (major effects/death versus all others) with co-used other substances, controlling for exposure year and demographics.

RESULTS

The number of exposures increased steadily during the seven years, but metamfetamine exposures increased more rapidly starting in 2018. One-fifth of cocaine and one-sixth of metamfetamine exposures suffered major effects/death. Co-use of prescription opioids (incident risk ratio = 2.00, 95% CI = 1.76-2.28 for cocaine; incident risk ratio = 1.62, 95% CI = 1.27-2.07 for metamfetamine), illicit fentanyl (incident risk ratio =1.88, 95% CI = 1.08-3.27 for cocaine; incident risk ratio = 2.05, 95% CI = 1.04-4.06 for metamfetamine), heroin (incident risk ratio =1.62, 95% CI = 1.37-1.90 for cocaine), or amfetamine (incident risk ratio =1.73, 95% CI = 1.28-2.33 for cocaine) was associated with a higher likelihood of major effects/death.

DISCUSSION

Increases in the number of cocaine and metamfetamine exposures among older adults reported to poison centers are of concern, and so is the increased risk of major effects/death from polysubstance use, especially prescription and illicit opioids, among these illicit psychostimulant users.

CONCLUSIONS

Healthcare provider screening of individuals at risk of cocaine and/or metamfetamine use and psychoeducation about the dangers of these substance use are needed.

Prevalence of hepatitis C virus among fatal drug overdoses in Tennessee: an analysis using 2019-2020 Tennessee State Unintentional Drug Overdose Reporting System Data

PURPOSE

Given the nature of the co-occurring epidemics of hepatitis C virus (HCV) and fatal stimulant overdose, we sought to assess the prevalence of HCV among opioid and stimulant-positive overdoses.

METHODS

We conducted a cross-sectional study to examine the prevalence of HCV among fatal drug overdoses in Tennessee using 2019-2020 data from the State Unintentional Drug Overdose Reporting System. We defined history of HCV using surveillance data and autopsy reports. Descriptive statistics were calculated for circumstances of overdose deaths for different categories of opioid and stimulant positivity on toxicology.

RESULTS

Between 2019 and 2020, 3570 unintentional or undetermined drug overdose deaths occurred in Tennessee with an available autopsy. History of HCV was found in 24.6% of deaths. When assessing different involvement between stimulants and opioids, the highest prevalence of HCV was found for deaths where methamphetamine and opioids were present in toxicology (35.4%). Scene evidence of injection drug use occurred more frequently among decedents with a history of HCV (P < .0001).

CONCLUSIONS

This analysis while descriptive highlights the importance of linking datasets to enhance infectious disease and drug overdose surveillance. Partnership between communicable disease and drug overdose surveillance teams should continue to identify relationships between disease and drug overdose and strengthen the evidence to tailor crucial treatment and prevention activities.

Associations between Circumstances Surrounding Overdose and Underlying Classes of Polysubstance Overdose Deaths

BACKGROUND

The overdose crisis is worsening, with polysubstance overdose deaths involving psychostimulants increasing in the U.S. Substance-specific prevention and intervention activities may not be as effective for polysubstance use, so we sought to classify substances used among overdose decedents to identify unique factors related to these classes.

METHODS

We used data from the Nevada State Unintentional Drug Overdose Reporting System, Jan 2019-Jun 2021, which comes from death certificates, coroner/medical examiner reports, and postmortem toxicology. Latent class analysis, multinomial logistic regression, and Chi-squared tests determined underlying drug use classes, differences in characteristics and circumstances surrounding overdose, and assessed relationships between circumstances and drug use classes.

RESULTS

We identified four latent classes: (1) prescription drugs (19.1%), (2) predominately methamphetamine (31.4%), (3) multi-drug (28.9%), and (4) opioid and stimulant (20.6%). Compared to other classes, the prescription drug class had a higher percentage of female decedents, from rural counties, with mental health diagnoses, who died at home. The predominately methamphetamine class had a higher percentage of decedents experiencing homelessness. The multi-drug use class had higher percentage of younger and Hispanic decedents. Those in the opioid and stimulant class had higher odds of being recently released from an institutional setting, compared to the multi drug class.

CONCLUSIONS

These underlying classes were associated with several characteristics and circumstances that can prove useful for prevention, treatment, and harm reduction agencies when designing programs and interventions to target specific groups of people at-risk for drug overdose.

Characteristics of fatal drug overdoses among college age decedents in Tennessee, 2019-2020

Purpose

College age persons experienced unique disruptions to their regular lives during the COVID-19 pandemic, sometimes resulting in negative coping mechanisms. We examined changes in the number of and characteristics of college age fatal drug overdoses before and during the early COVID-19 pandemic.

Methods

We conducted a statewide cross-sectional study to determine the changes in the number and characteristics of college age fatal drug overdose decedents before and during the COVID-19 pandemic using 2019-2020 data from the Tennessee State Unintentional Drug Overdose Reporting System. We defined college age as 18-24 years. Frequencies and rates were generated to compare demographics, circumstances, and toxicology between 2019 and 2020.

Results

From 2019 to 2020, 336 college age persons experienced an unintentional or undetermined fatal drug overdose in Tennessee. Characteristics of college age decedents: mean age 21.7 years, 68.5% males, and 71.4% White. Rates of fatal overdoses among college age persons increased 50.0% overall, 150.1% for female decedents, and 141.7% for Black decedents. Fewer people were treated for substance use disorder or mental health conditions (p = 0.0243) in 2020.

Conclusion

This analysis can inform local and regional public health workers to implement focused prevention and intervention efforts to curtail the overdose epidemic among college age persons in Tennessee.