Stanford Sleep Epidemiology Research Center (SSERC), Division of Public Mental Health and Population Sciences, School of Medicine, Stanford, CA, USA.
Takeda Pharmaceuticals U.S.A., Inc., Lexington, MA, USA.
J Affect Disord. 2023 Jan 15;321:272-278. doi: 10.1016/j.jad.2022.10.034. Epub 2022 Oct 21.
Major depressive disorder (MDD) is largely managed in primary care, but physicians vary widely in their understanding of symptoms and treatments. This study aims to better understand the evolution of depression from initial diagnosis over a 3-year period.
This was a noninterventional, retrospective, longitudinal study, with 2 waves of participant interviews approximately 3 years apart. Phone interviews were conducted using the hybrid artificial intelligence (AI) Sleep-EVAL system, an AI-driven diagnostic deep learning tool. Participants were noninstitutionalized adults representative of the general population in 8 US states. Diagnosis was confirmed according to the DSM-5 using the Sleep-EVAL System.
10,931 participants completed Wave 1 and 2 (W1, W2) interviews. The prevalence of MDD, including partial and complete remission, was 13.4 % and 19.6 % in W1 and W2, respectively. About 42 % of MDD participants at W1 continued to report depressive symptoms at W2. Approximately half of antidepressant (AD) users in W1 were moderately to completely dissatisfied with their treatment; 29.6 % changed their AD for a different one, with 16.4 % switching from one SSRI to another between W1 and W2. Primary care physicians were the top AD prescribers, both in W1 (45.7 %) and W2 (59%), respectively.
Data collected relied on self-reporting by participants. As such, the interpretation of the data may be limited.
Depression affects a sizeable portion of the US population. Dissatisfaction with treatment, frequent switching of ADs, and changing care providers are associated with low rates of remission. Residual symptoms remain a challenge that future research must address.
重度抑郁症（MDD）主要在初级保健中进行管理，但医生对症状和治疗方法的理解差异很大。本研究旨在更好地了解抑郁在 3 年内从初始诊断到后期的演变过程。
这是一项非干预性、回顾性、纵向研究，参与者有两次访谈，大约相隔 3 年。使用混合人工智能（AI）Sleep-EVAL 系统进行电话访谈，这是一种人工智能驱动的诊断深度学习工具。参与者是非住院的成年人，代表美国 8 个州的一般人群。根据 DSM-5 使用 Sleep-EVAL 系统确认诊断。
10931 名参与者完成了第 1 波和第 2 波（W1、W2）访谈。在 W1 和 W2，MDD 的患病率（包括部分和完全缓解）分别为 13.4%和 19.6%。约 42%的 MDD 参与者在 W1 时继续在 W2 报告抑郁症状。大约一半的 W1 抗抑郁药（AD）使用者对其治疗中度至完全不满意；50%的人更换了不同的 AD，其中 29.6%的人在 W1 和 W2 之间从一种 SSRI 换成另一种，16.4%的人从一种 SSRI 换成另一种。初级保健医生是 AD 的主要处方者，W1 和 W2 分别为 45.7%和 59%。
收集的数据依赖于参与者的自我报告。因此，对数据的解释可能有限。
抑郁症影响了相当一部分美国人口。对治疗的不满、频繁更换 AD 和改变治疗提供者与缓解率低有关。残留症状仍然是一个挑战，未来的研究必须解决。
