Despite strong evidence of efficacy of electroconvulsive therapy (ECT) in the treatment of depression, no sensitive and specific predictors of ECT response have been identified. Previous meta-analyses have suggested some pre-treatment associations with response at a population level.

Using 10 years (2009–2018) of routinely collected Scottish data of people with moderate to severe depression (n = 2074) receiving ECT we tested two hypotheses: (a) that there were significant group-level associations between post-ECT clinical outcomes and pre-ECT clinical variables and (b) that it was possible to develop a method for predicting illness remission for individual patients using machine learning.

Data were analysed on a group level using descriptive statistics and association analyses as well as using individual patient prediction with machine learning methodologies, including cross-validation.

ECT is highly effective for moderate to severe depression, with a response rate of 73% and remission rate of 51%. ECT response is associated with older age, psychotic symptoms, necessity for urgent intervention, severe distress, psychomotor retardation, previous good response, lack of medication resistance, and consent status. Remission has the same associations except for necessity for urgent intervention and, in addition, history of recurrent depression and low suicide risk. It is possible to predict remission with ECT with an accuracy of 61%.

Pre-ECT clinical variables are associated with both response and remission and can help predict individual response to ECT. This predictive tool could inform shared decision-making, prevent the unnecessary use of ECT when it is unlikely to be beneficial and ensure prompt use of ECT when it is likely to be effective.

尽管有强有力的证据表明电休克疗法 (ECT) 在治疗抑郁症方面有效，但尚未确定 ECT 反应的敏感且特异的预测因子。之前的荟萃分析表明，治疗前与人群水平的反应存在一些关联。

使用 10 年（2009-2018 年）定期收集的苏格兰中度至重度抑郁症患者（ n = 2074）接受 ECT 的数据，我们测试了两个假设：（a）ECT 后临床结果与ECT 前的临床变量；(b) 可以开发一种使用机器学习预测个体患者疾病缓解的方法。

使用描述性统计和关联分析以及使用机器学习方法（包括交叉验证）对个体患者进行预测来对数据进行群体层面的分析。

ECT 对中重度抑郁症非常有效，有效率达 73%，缓解率达 51%。 ECT 反应与年龄较大、精神病症状、紧急干预的必要性、严重痛苦、精神运动迟缓、以前的良好反应、缺乏药物抵抗力和同意状态有关。除了需要紧急干预以及复发性抑郁症病史和低自杀风险之外，缓解具有相同的关联。通过 ECT 可以预测缓解，准确度为 61%。

ECT 前的临床变量与反应和缓解相关，可以帮助预测个体对 ECT 的反应。这种预测工具可以为共同决策提供信息，防止在 ECT 不太可能有益时不必要地使用它，并确保在 ECT 可能有效时立即使用它。