使用电子病历评估药物与致命性脑出血之间的因果关系：疾病特异性方法与传统方法的比较评价

Causality Assessment Between Drugs and Fatal Cerebral Haemorrhage Using Electronic Medical Records: Comparative Evaluation of Disease-Specific and Conventional Methods.

作者信息

Ohta Miki, Miyawaki Satoru, Yokota Shinichiroh, Yoshimoto Makoto, Maruyama Tatsuya, Koide Daisuke, Moritoyo Takashi, Saito Nobuhito

机构信息

Clinical Research Promotion Centre, The University of Tokyo Hospital, Tokyo, Japan.

Department of Neurosurgery, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.

出版信息

Drugs Real World Outcomes. 2024 Jun;11(2):221-229. doi: 10.1007/s40801-023-00413-y. Epub 2024 Feb 6.

DOI:10.1007/s40801-023-00413-y

PMID:38321346

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11176114/

Abstract

INTRODUCTION

A new algorithm for causality assessment of drugs and fatal cerebral haemorrhage (ACAD-FCH) was published in 2021. However, its use in clinical practice has not been verified.

OBJECTIVES

This study aimed to explore the practical value of the ACAD-FCH when applying information available in clinical practice.

METHODS

The medical records of patients who died at the University of Tokyo Hospital in 2020 were reviewed, and cases with intracranial haemorrhage were selected. Two evaluators independently assessed these cases using three methods (the ACAD-FCH, Naranjo algorithm, and WHO-UMC scale). The number of 'Yes', 'No', and 'No information/Do not know' responses to each question by both evaluators were summed and compared. Inter-rater reliability was evaluated for each method using agreement rates and kappa coefficients with 95% confidence intervals (CI).

RESULTS

Among 316 deaths, 24 cases with intracranial haemorrhage were evaluated. The proportion of ‛No information/Do not know' responses for each question was 35.6% (95% CI 31.4-40.6%) for the ACAD-FCH and 66.9% (95% CI 62.5-71.1%) for the Naranjo algorithm. The respective agreement rates and kappa coefficients were 0.917 (0.798-1.00) and 0.867 (0.675-1.00) for the ACAD-FCH, 0.708 (0.512-0.904) and 0.139 (-0.236 to 0.513) for the Naranjo algorithm, and 0.50 (0.284-0.716) and 0.326 (0.110-0.541) for the WHO-UMC scale, respectively.

CONCLUSION

Our findings suggest the utility of the ACAD-FCH when assessing death cases with intracranial haemorrhage. However, larger studies including intra-rater assessments are warranted for further validation of this algorithm.

摘要

引言

一种用于药物与致命性脑溢血因果关系评估的新算法（ACAD-FCH）于2021年发布。然而，其在临床实践中的应用尚未得到验证。

目的

本研究旨在探讨在应用临床实践中可得信息时ACAD-FCH的实用价值。

方法

回顾了2020年在东京大学医院死亡患者的病历，并选取了颅内出血病例。两名评估者使用三种方法（ACAD-FCH、Naranjo算法和WHO-UMC量表）对这些病例进行独立评估。汇总并比较两名评估者对每个问题的“是”“否”及“无信息/不知道”回答的数量。使用一致性率和95%置信区间（CI）的kappa系数对每种方法的评估者间信度进行评估。

结果

在316例死亡病例中，对24例颅内出血病例进行了评估。ACAD-FCH每个问题的“无信息/不知道”回答比例为35.6%（95%CI 31.4 - 40.6%），Naranjo算法为66.9%（95%CI 62.5 - 71.1%）。ACAD-FCH的一致性率和kappa系数分别为0.917（0.798 - 1.00）和0.867（0.675 - 1.00），Naranjo算法分别为0.708（0.512 - 0.904）和0.139（-0.236至0.513），WHO-UMC量表分别为0.50（0.284 - 0.716）和0.326（0.110 - 0.541）。