Drug and alcohol dependence · 2022
Use of laboratory data for illicit drug use surveillance and identification of socioeconomic risk factors.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Azimi Vahid, Jackups Ronald, Farnsworth Christopher W, Budelier Melissa M
Аннотация
BACKGROUND: Drug overdose is the leading cause of death among people 25-44 years of age in the United States. Existing drug surveillance methods are important for prevention and directing treatment, but are limited by delayed reporting and lack of geographic granularity.
METHODS: Laboratory urine drug screen and complete metabolic panel data from patients presenting to the emergency department was used to observe long-term and short-term temporal and geospatial changes at the zip code-level in St. Louis. Multivariate linear regression was performed to investigate associations between zip code-level socioeconomic factors and drug screening positivity rates.
RESULTS: An increase in the fentanyl positive drug screens was seen during the initial COVID-19 shutdown period in the spring of 2020. A decrease in cocaine positivity was seen in the fall and winter of 2020, with a return to baseline coinciding with the second major COVID-19 shutdown in the summer of 2021. These changes appeared to be independent of changes in emergency department utilization as measured by complete metabolic panels ordered. Significant short-term changes in fentanyl and cocaine positivity rates between specific time periods were able to be localized to individual zip codes. Zip code-level multivariate analysis demonstrated independent associations between socioeconomic/demographic factors and fentanyl/cocaine positivity rates as determined by laboratory drug screening data.
CONCLUSIONS: Analyzing clinical laboratory drug screening data can enable a more temporally and geographically granular view of population-level drug use surveillance. Additionally, laboratory data can be utilized to find population-level socioeconomic associations with illicit drug use, presenting a potential avenue for the use of this data to guide public health and healthcare policy decisions.
METHODS: Laboratory urine drug screen and complete metabolic panel data from patients presenting to the emergency department was used to observe long-term and short-term temporal and geospatial changes at the zip code-level in St. Louis. Multivariate linear regression was performed to investigate associations between zip code-level socioeconomic factors and drug screening positivity rates.
RESULTS: An increase in the fentanyl positive drug screens was seen during the initial COVID-19 shutdown period in the spring of 2020. A decrease in cocaine positivity was seen in the fall and winter of 2020, with a return to baseline coinciding with the second major COVID-19 shutdown in the summer of 2021. These changes appeared to be independent of changes in emergency department utilization as measured by complete metabolic panels ordered. Significant short-term changes in fentanyl and cocaine positivity rates between specific time periods were able to be localized to individual zip codes. Zip code-level multivariate analysis demonstrated independent associations between socioeconomic/demographic factors and fentanyl/cocaine positivity rates as determined by laboratory drug screening data.
CONCLUSIONS: Analyzing clinical laboratory drug screening data can enable a more temporally and geographically granular view of population-level drug use surveillance. Additionally, laboratory data can be utilized to find population-level socioeconomic associations with illicit drug use, presenting a potential avenue for the use of this data to guide public health and healthcare policy decisions.