Northern Centre for Mood Disorders, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.
Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust, Newcastle upon Tyne, UK.
J Psychopharmacol. 2022 May;36(5):545-556. doi: 10.1177/02698811221090628. Epub 2022 May 4.
Major depressive disorder (MDD) is common and often has sub-optimal response to treatment. Difficult-to-treat depression (DTD) is a new concept that describes 'depression that continues to cause significant burden despite usual treatment efforts'.
To identify patients with likely DTD in UK secondary care and examine demographic, disease and treatment data as compared with 'non-DTD' MDD patients.
Anonymised electronic health records (EHRs) of five specialist mental health National Health Service (NHS) Trusts in the United Kingdom were analysed using a natural language processing model. Data on disease characteristics, comorbidities and treatment histories were extracted from structured fields and using natural language algorithms from unstructured fields. Patients with MDD aged ⩾18 years were included in the analysis; those with presumed DTD were identified on the basis of MDD history (duration and recurrence) and number of treatments prescribed.
In a sample of 28,184 patients with MDD, 19% met criteria for DTD. Compared to the non-DTD group, patients with DTD were more likely to have severe depression, suicidal ideation, and comorbid psychiatric and/or physical illness, as well as higher rates of hospitalisation. They were also more likely to be in receipt of unemployment and sickness/disability benefits. More intensive treatment strategies were used in the DTD group, including higher rates of combination therapy, augmentation, psychotherapy and electroconvulsive therapy.
This study demonstrates the feasibility of identifying patients with probable DTD from EHRs and highlights the increased burden associated with MDD in these patients.
重度抑郁症（MDD）较为常见，且通常对治疗的反应欠佳。治疗困难的抑郁症（DTD）是一个新概念，用于描述“尽管进行了常规治疗，但仍持续存在且严重影响生活的抑郁症”。
在英国二级保健中识别可能患有 DTD 的患者，并与“非 DTD MDD”患者比较其人口统计学、疾病和治疗数据。
使用自然语言处理模型对英国五家专科精神卫生国民保健服务（NHS）信托机构的匿名电子健康记录（EHR）进行分析。从结构化字段中提取疾病特征、合并症和治疗史数据，并使用自然语言算法从非结构化字段中提取数据。分析年龄 ⩾18 岁的 MDD 患者；根据 MDD 病史（持续时间和复发）和开具的治疗方案数量，确定 DTD 患者。
在 28184 例 MDD 患者中，19%符合 DTD 标准。与非 DTD 组相比，DTD 患者更有可能患有重度抑郁症、自杀意念以及合并的精神和/或躯体疾病，住院率也更高。他们也更有可能享受失业和疾病/残疾津贴。DTD 组使用了更强化的治疗策略，包括更高的联合治疗、增效治疗、心理治疗和电惊厥治疗的比例。
本研究从 EHR 中识别出可能患有 DTD 的患者，证明了这一方法具有可行性，并强调了这些患者中 MDD 相关的负担加重。
