No CrossRef data available.
Article contents
The identification of treatment-resistant depression patients in electronic health records, a retrospective cohort study in China
Published online by Cambridge University Press: 01 September 2022
Abstract
Previous Electronic Health Records (EHR) based studies adopted various definitions in identifying Treatment-Resistant Depression (TRD) patients. There is a lack of similar attempts among Chinese population which limits the understanding of TRD in China.
Assess TRD identification using EHR from a major psychiatric hospital in China.
This study utilized a retrospective Major Depressive Disorder (MDD) cohort of patients who newly initiated pharmaceutical treatment (2010-2018); follow-up was ended upon 1-year or treatment discontinuation (≥120d without treatment). TRD was first identified based on common clinical definition of two prior regimen failures (change of regimen) with 4-week as regimen adequacy threshold (Def1). Alternative adequacy thresholds of 2-week and 6-week were applied. Based on Def1 (4-week), at least 3 distinctive regimens were additionally required in TRD identification (Def2). Further, a data-driven definition (Def3) based on drug count as having ≥3 antidepressants or ≥1 antipsychotic within 1 year was considered (Cepeda et al., 2018).
From 12257 MDD patients included in the cohort, Def1 identified 633 (5.2%) TRD cases, whereas regimen adequacy thresholds of 2-week and 6-week identified 1772 (14.5%) and 61 (0.5%) cases, respectively. Further, Def2 identified 261 (2.4%) TRD cases. Finally, Def3 yielded 2449 (20.0%) TRD cases, including 1966 exclusive cases that were not identified by Def1.
This study showed different definitions for TRD identification had considerable impact on the number of patients identified among Chinese population, obscuring the comparability among EHR-based TRD studies. As first step, we found the criteria of regimen adequacy as major contributor to the observed variability in China.
No significant relationships.
- Type
- Abstract
- Information
- European Psychiatry , Volume 65 , Special Issue S1: Abstracts of the 30th European Congress of Psychiatry , June 2022 , pp. S268
- Creative Commons
- This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Copyright
- © The Author(s), 2022. Published by Cambridge University Press on behalf of the European Psychiatric Association
Comments
No Comments have been published for this article.