阿片类药物流行的公共卫生监测毒理学试验结果:回顾性分析

Titus Schleyer, Bill Robinson, Samir Parmar, Diane Janowiak, P Joseph Gibson, Val Spangler
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摘要

解决阿片类药物流行问题需要及时了解人口层面的因素,如合法和非法药物流行趋势、过量使用和死亡。目的本研究旨在探讨来自各种来源的活体毒理学测试结果是否可用于监测阿片类药物的流行。方法回顾性分析2018年9月1日至2019年8月31日美国印第安纳州马里恩县24家实验室的标准化、合并和关联毒理学结果。该数据集包括33,787名马里昂县居民和他们的746,681个结果。我们将数据与马里恩县的一般人口统计数据联系起来,并将毒理学结果产生的警报与阿片类药物过量相关的急诊就诊进行比较。19位领域专家帮助构建了分析可视化的原型。主要结果指标包括县和邮政编码的检测阳性情况;有毒理学结果的个体的选定人口统计学;毒理学结果与阿片类药物过量相关急诊科就诊的相关性。结果4%的马里恩县居民至少有1项毒理学结果。整个邮政编码的检测阳性率从3%到19%不等。男性在数据集中的代表性不足。年龄分布与马里恩县相似。阿片类药物毒理学结果警报与阿片类药物过量相关的急诊就诊无关。结论数据格式、完整性和代表性的差异阻碍了毒理学结果的大规模分析;数据输入的变化;病人匹配困难。在这项研究中,毒理学结果并不能预测阿片类药物过量的峰值。需要更大规模、更严格和控制良好的研究来评估毒理学试验在预测阿片类药物过量峰值方面的效用。
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Toxicology Test Results for Public Health Surveillance of the Opioid Epidemic: Retrospective Analysis
Background Addressing the opioid epidemic requires timely insights into population-level factors, such as trends in prevalence of legal and illegal substances, overdoses, and deaths. Objective This study aimed to examine whether toxicology test results of living individuals from a variety of sources could be useful in surveilling the opioid epidemic. Methods A retrospective analysis standardized, merged, and linked toxicology results from 24 laboratories in Marion County, Indiana, United States, from September 1, 2018, to August 31, 2019. The data set consisted of 33,787 Marion County residents and their 746,681 results. We related the data to general Marion County demographics and compared alerts generated by toxicology results to opioid overdose–related emergency department visits. Nineteen domain experts helped prototype analytical visualizations. Main outcome measures included test positivity in the county and by ZIP code; selected demographics of individuals with toxicology results; and correlation of toxicology results with opioid overdose–related emergency department visits. Results Four percent of Marion County residents had at least 1 toxicology result. Test positivity rates ranged from 3% to 19% across ZIP codes. Males were underrepresented in the data set. Age distribution resembled that of Marion County. Alerts for opioid toxicology results were not correlated with opioid overdose–related emergency department visits. Conclusions Analyzing toxicology results at scale was impeded by varying data formats, completeness, and representativeness; changes in data feeds; and patient matching difficulties. In this study, toxicology results did not predict spikes in opioid overdoses. Larger, more rigorous and well-controlled studies are needed to assess the utility of toxicology tests in predicting opioid overdose spikes.
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