在南非,通过计算机编码的口头尸检方法来确定死亡原因,以及医生对口头尸检采访进行编码之间的协议
Pam Groenewald1, Jason Thomas2, Samuel J Clark2
1Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa.
Global health action
|December 1, 2023
概括
计算机编码口语解剖 (CCVA) 在识别南非艾滋病毒/艾滋病等主要死亡原因方面表现有前途,但需要改进算法才能准确地确定死亡原因 (COD).
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 南非国家死亡原因验证 (NCODV 2017/18) 项目利用口头尸检 (VA) 来确定死亡原因 (COD).
- 医生编码的VA (PCVA) 和计算机编码的VA (CCVA) 方法用于在全国样本中分配COD.
研究的目的:
- 为了评估三个CCVA算法 (InterVA-5,InSilicoVA,Tariff 2.0) 与医生编码的VA (PCVA) 参考标准的性能.
- 评估不同的人口分组在个人和人口层面上对COD分配的协议.
主要方法:
- 分析了5386个口头尸检记录,使用了7个绩效指标.
- 对个人级别协议 (PPV,灵敏度等) 的CCVA算法与PCVA进行比较. 和人口层面的协议 (CSMF准确度,斯皮尔曼等级相关性).
主要成果:
- 所有CCVA方法都将艾滋病毒/艾滋病确定为主要的死亡原因,与PCVA一致.
- 对于大多数病因,CCVA的性能与PCVA相似,但例外包括艾滋病毒/艾滋病,结核病和某些伤害.
- 虽然CCVA显示个人层面的协议较弱至中度,但它们在特定死因分数 (CSMF) 准确性方面取得了中度至强度的协议,特别是在特定子组中.
结论:
- 计算机编码口语解剖 (CCVA) 可以识别主要的死亡原因,如艾滋病毒/艾滋病,与南非的医生编码相比.
- 建议进一步完善CCVA算法,以提高南非背景下死亡原因分配的准确性和可靠性.
相关概念视频
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