探索分析后错误的程度,重点是转录错误 - - 在VIPVIZA研究中进行的干预
Malin Mickelsson1, Kim Ekblom1,2, Kristina Stefansson1
1Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden.
Clinical chemistry and laboratory medicine
|February 28, 2025
概括
在VIPVIZA研究中发生了脂质变量的转录错误. 教育干预减少了这些错误,但有些错误仍然影响了心血管疾病风险预测.
科学领域:
- 医学研究 医学研究
- 临床数据管理 临床数据管理
- 心血管疾病风险评估心血管疾病风险评估
背景情况:
- 该 VIPVIZA 研究涉及转录脂质参数 (总胆固醇,甘油三,高密度胆固醇,低密度胆固醇) 进入研究数据库.
- 在数据输入过程中可能会出现转录错误,这可能会影响下游分析和临床决策.
研究的目的:
- 在VIPVIZA研究中量化脂质变量中的转录错误.
- 评估教育干预措施在减少这些转录错误方面的有效性.
- 评估转录错误对SCORE2心血管疾病风险预测算法的影响.
主要方法:
- 脂质参数由研究护士转录.
- 通过重新计算LDL胆固醇来确定转录错误;差异>0.15表示存在错误.
- 对SCORE2风险类别进行了比较,使用不正确和正确的脂质值来评估错误分类.
主要成果:
- 转录错误频率在2019年为0.55%,在教育干预后在2023年降至0.25%.
- 在总胆固醇或高密度胆固醇转录错误的个体中,15%的人被分配了一个不正确的SCORE2风险类别.
结论:
- 尽管有数字化努力,临床数据的转录错误仍然存在.
- 尽量减少实验室外的手工转录对于数据准确性至关重要.
- 准确的脂质值对于可靠的心血管风险预测算法,如SCORE2.2,至关重要.
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