Trends in opioid exposures among young children reported to United States poison centers from 2016 to 2023.

INTRODUCTION: The objective of this study was to update and expand on previous studies of opioid exposures among young children reported to America's Poison Centers, and to describe how fentanyl and medications for opioid use disorder have contributed. METHODS: This retrospective study investigated 34,632 reports of single-substance opioid exposure from 2016 to 2023 involving pediatric patients aged one month to six years old. Descriptive statistics, tests for data normality, and significance testing were performed where applicable. RESULTS: Of 34,632 reported exposures, 96.7% were unintentional. The median age of exposure was 2.0 years (IQR 1.33-3.0 years). Reported exposures decreased by 57.5% over the study period (r = -0.96; P < 0.001). However, there was a 300% absolute increase in deaths and major effects (r = 0.96; P < 0.001). Exposures resulting in minor, no effect, not followed, or unable to follow decreased 66.2% (r = -0.99; P < 0.001). Buprenorphine was most frequently involved, comprising 23.4% of reported exposures. Buprenorphine (OR 1.93; P < 0.001) and methadone (OR 14.98; P < 0.001) were associated with an increased risk of severe effects when compared to other prescription drugs (OR: 1). There was an absolute increase of 512% over time in reports of heroin, fentanyl, synthetic non-pharmaceutical opioids (r = 0.92; P < 0.001), which were also associated with severe effects (OR 20.1; P < 0.001). DISCUSSION: Pediatric opioid exposures have previously been reported to be relatively stable. It is likely the 57.5% reduction is exaggerated due to underreporting from health care providers. However, decreases in exposures are presumed to be balanced throughout the dataset and, therefore, without differential impact on other points of analysis. Our study highlights the continued need for enhanced poisoning prevention strategies. CONCLUSIONS: The relative severity of poisonings reported to poison centers worsened over the study period. The opioids implicated have shifted away from hydrocodone, oxycodone, and tramadol, and towards fentanyl and buprenorphine.

Preventing Pediatric Opioid Poisoning: Unusual Sources and Scenarios.

This retrospective study analyzed 230 pediatric opioid exposures from a statewide poison control center over a 5-year period. Most exposures involved pharmaceutical opioids and children below 2-years-old. Narrative details were reviewed to identify uncommon sources of opioids involved in poisoning and highlight the need for tailored prevention strategies and guidance.

Neighborhood-Level Risk Factors for Severe Hyperglycemia among Emergency Department Patients without a Prior Diabetes Diagnosis.

A person's place of residence is a strong risk factor for important diagnosed chronic diseases such as diabetes. It is unclear whether neighborhood-level risk factors also predict the probability of undiagnosed disease. The objective of this study was to identify neighborhood-level variables associated with severe hyperglycemia among emergency department (ED) patients without a history of diabetes. We analyzed patients without previously diagnosed diabetes for whom a random serum glucose value was obtained in the ED. We defined random glucose values ≥ 200 mg/dL as severe hyperglycemia, indicating probable undiagnosed diabetes. Patient addresses were geocoded and matched with neighborhood-level socioeconomic measures from the American Community Survey and claims-based surveillance estimates of diabetes prevalence. Neighborhood-level exposure variables were standardized based on z-scores, and a series of logistic regression models were used to assess the association of selected exposures and hyperglycemia adjusting for biological and social individual-level risk factors for diabetes. Of 77,882 ED patients without a history of diabetes presenting in 2021, 1,715 (2.2%) had severe hyperglycemia. Many geospatial exposures were associated with uncontrolled hyperglycemia, even after controlling for individual-level risk factors. The most strongly associated neighborhood-level variables included lower markers of educational attainment, higher percentage of households where limited English is spoken, lower rates of white-collar employment, and higher rates of Medicaid insurance. Including these geospatial factors in risk assessment models may help identify important subgroups of patients with undiagnosed disease.