five

Accidental Drug Related Deaths 2012-2023

收藏
data.ct.gov2024-07-01 更新2025-03-25 收录
下载链接:
https://data.ct.gov/Health-and-Human-Services/Accidental-Drug-Related-Deaths-2012-2023/rybz-nyjw
下载链接
链接失效反馈
官方服务:
资源简介:
A listing of each accidental death associated with drug overdose in Connecticut from 2012 to 2023. A "Y" value under the different substance columns indicates that particular substance was detected. Data are derived from an investigation by the Office of the Chief Medical Examiner which includes the toxicity report, death certificate, as well as a scene investigation. The “Morphine (Not Heroin)” values are related to the differences between how Morphine and Heroin are metabolized and therefor detected in the toxicity results. Heroin metabolizes to 6-MAM which then metabolizes to morphine. 6-MAM is unique to heroin, and has a short half-life (as does heroin itself). Thus, in some heroin deaths, the toxicity results will not indicate whether the morphine is from heroin or prescription morphine. In these cases the Medical Examiner may be able to determine the cause based on the scene investigation (such as finding heroin needles). If they find prescription morphine at the scene it is certified as “Morphine (not heroin).” Therefor, the Cause of Death may indicate Morphine, but the Heroin or Morphine (Not Heroin) may not be indicated. “Any Opioid” – If the Medical Examiner cannot conclude whether it’s RX Morphine or heroin based morphine in the toxicity results, that column may be checked

本数据集详尽记录了2012年至2023年间康涅狄格州因药物过量导致的意外死亡案例。不同物质列下的“Y”值表示检测到该特定物质。数据源自首席法医官办公室的调查,包括毒物学报告、死亡证明以及现场调查。其中,“吗啡(非海洛因)”值与吗啡和海洛因在毒物学检测结果中的代谢差异有关。海洛因代谢为6-MAM,随后6-MAM再代谢为吗啡。6-MAM是海洛因特有的代谢产物,其半衰期较短(海洛因本身亦然)。因此,在某些海洛因死亡案例中,毒物学结果可能无法明确吗啡的来源是海洛因还是处方吗啡。在这种情况下,法医官可能根据现场调查(例如发现海洛因针具)来确定死因。如果现场发现处方吗啡,则将其确认为“吗啡(非海洛因)”。因此,死亡原因可能表明为吗啡,但海洛因或吗啡(非海洛因)可能未被明确指出。“任何阿片类药物”一栏,若法医官无法根据毒物学结果确定其为处方吗啡或海洛因代谢而来的吗啡,则该栏可能被勾选。
提供机构:
data.ct.gov
搜集汇总
数据集介绍
main_image_url
以上内容由遇见数据集搜集并总结生成
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作