Epidemiology of pediatric buprenorphine and methadone exposures reported to the poison centers

Increasing severity of medical outcomes and associated substances in cases reported to United States poison centers

INTRODUCTION

Poison centers provide free expert recommendations on the treatment of a wide variety of toxicological emergencies. Prior studies have called attention to the increasing complexity of cases reported to poison centers. We aimed first, to evaluate the trends in medical outcome severity, over a 15-year period in both the adult and pediatric populations. Second, we described the most frequently reported substances associated with major effect or death.

METHODS

This is a retrospective review of exposures reported to the National Poison Data System from 1 January 2007 through 31 December 2021. All closed cases, for human exposures, reported during the study period were included. We assessed trends in frequencies and rates of medical outcomes and level of care received, among the adult (age greater than 19 years) and pediatric (age 19 years and younger) populations by reason for exposure.

RESULTS

During the study period, the number of adult unintentional exposures resulting in major effect (37.4 percent) and death (65.3 percent) increased. The number of adult intentional exposures resulting in death increased by 233.9 percent and those resulting in a major effect increased by 133.1 percent. The rates of exposures resulting in major effect and death increased among both intentional and unintentional adult exposures. The number of pediatric unintentional exposures resulting in a major effect increased by 76.6 percent and the number of pediatric intentional exposures resulting in death and major effect increased by 122.7 and 190.1 percent, respectively. Moderate, major effect, and death rates increased in pediatric unintentional exposures and moderate and major effect rates increased in pediatric intentional exposures.

CONCLUSIONS

We found a worsening severity of medical outcomes in adult and pediatric cases reported to poison centers. Poison centers are increasingly managing complex cases. Monitoring trends in which substances are associated with severe outcomes is imperative for future strategic prevention efforts.

Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS)

Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utilizes National Poison Data System (NPDS) data. The severity of outcomes was derived from the NPDS Coding Manual. Our database was divided into training (70%) and test (30%) sets. We used a light gradient boosting machine (LGBM), extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR) to predict the outcomes of methadone poisoning. A total of 3847 patients with methadone exposures were included. Our results demonstrated that machine learning models conferred high accuracy and reliability in determining the outcomes of methadone poisoning cases. The performance evaluation showed all models had high accuracy, precision, specificity, recall, and F1-score values. All models could reach high specificity (more than 96%) and high precision (80% or more) for predicting major outcomes. The models could also achieve a high sensitivity to predict minor outcomes. Finally, the accuracy of all models was about 75%. However, XGBoost and LGBM models achieved the best performance among all models. This study showcased the accuracy and reliability of machine learning models in the outcome prediction of methadone poisoning.

Examining buprenorphine diversion through a harm reduction lens: an agent-based modeling study

BACKGROUND

Recent policies have lessened restrictions around prescribing buprenorphine-naloxone (buprenorphine) for the treatment of opioid use disorder (OUD). The primary concern expressed by critics of these policies is the potential for buprenorphine diversion. However, the population-level effects of increased buprenorphine diversion are unclear. If replacing the use of heroin or fentanyl, use of diverted buprenorphine could be protective.

METHODS

Our study aim was to estimate the impact of buprenorphine diversion on opioid overdose using an agent-based model calibrated to North Carolina. We simulated the progression of opioid misuse and opioid-related outcomes over a 5-year period. Our status quo scenario assumed that 50% of those prescribed buprenorphine diverted at least one dose per week to other individuals with OUD and 10% of individuals with OUD used diverted buprenorphine at least once per week. A controlled prescription only scenario assumed that no buprenorphine would be diverted, while an increased diversion scenario assumed that 95% of those prescribed buprenorphine diverted and 50% of individuals with OUD used diverted buprenorphine. We assumed that use of diverted buprenorphine replaced the use of other opioids for that day. Sensitivity analyses increased the risk of overdose when using diverted buprenorphine, increased the frequency of diverted buprenorphine use, and simulated use of diverted buprenorphine by opioid-naïve individuals. Scenarios were compared on opioid overdose-related outcomes over the 5-year period.

RESULTS

Our status quo scenario predicted 10,658 (credible interval [CI]: 9699-11,679) fatal opioid overdoses. A scenario simulating controlled prescription only of buprenorphine (i.e., no diversion) resulted in 10,741 (9895-11,650) fatal opioid overdoses versus 10,301 (9439-11,244) within a scenario simulating increased diversion. Compared to the status quo, the controlled prescription only scenario resulted in a similar number of fatal overdoses, while the scenario with increased diversion of buprenorphine resulted in 357 (3.35%) fewer fatal overdoses. Even when increasing overdose risk while using diverted buprenorphine and incorporating use by opioid naïve individuals, increased diversion did not increase overdoses compared to a scenario with no buprenorphine diversion.

CONCLUSIONS

A similar number of opioid overdoses occurred under modeling conditions with increased rates of buprenorphine diversion among persons with OUD, with non-statistical trends toward lower opioid overdoses. These results support existing calls for low- to no-barrier access to buprenorphine for persons with OUD.