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首页> 外文期刊>The British journal of psychiatry : >Using machine learning to predict suicide in the 30 days after discharge from psychiatric hospital in Denmark
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Using machine learning to predict suicide in the 30 days after discharge from psychiatric hospital in Denmark

机译：使用机器学习预测丹麦精神病院出院后 30 天内的自杀

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Background Suicide risk is high in the 30 days after discharge from psychiatric hospital, but knowledge of the profiles of high-risk patients remains limited. Aims To examine sex-specific risk profiles for suicide in the 30 days after discharge from psychiatric hospital, using machine learning and Danish registry data. Method We conducted a case-cohort study capturing all suicide cases occurring in the 30 days after psychiatric hospital discharge in Denmark from 1 January 1995 to 31 December 2015 (n = 1205). The comparison subcohort was a 5 random sample of all persons born or residing in Denmark on 1 January 1995, and who had a first psychiatric hospital admission between 1995 and 2015 (n = 24 559). Predictors included diagnoses, surgeries, prescribed medications and demographic information. The outcome was suicide death recorded in the Danish Cause of Death Registry. Results For men, prescriptions for anxiolytics and drugs used in addictive disorders interacted with other characteristics in the risk profiles (e.g. alcohol-related disorders, hypnotics and sedatives) that led to higher risk of postdischarge suicide. In women, there was interaction between recurrent major depression and other characteristics (e.g. poisoning, low income) that led to increased risk of suicide. Random forests identified important suicide predictors: alcohol-related disorders and nicotine dependence in men and poisoning in women. Conclusions Our findings suggest that accurate prediction of suicide during the high-risk period immediately after psychiatric hospital discharge may require a complex evaluation of multiple factors for men and women.
机译：背景 从精神病院出院后 30 天内自杀风险很高，但对高危患者概况的了解仍然有限。目的 使用机器学习和丹麦登记数据检查从精神病院出院后 30 天内的特定性别自杀风险概况。方法 我们进行了一项病例队列研究，收集了 1995 年 1 月 1 日至 2015 年 12 月 31 日期间丹麦精神病院出院后 30 天内发生的所有自杀病例 （n = 1205）。比较亚队列是 1995 年 1 月 1 日在丹麦出生或居住的所有人在 1995 年至 2015 年期间首次入院的 5% 随机样本 （n = 24 559）。预测因素包括诊断、手术、处方药和人口统计信息。结果是丹麦死因登记处记录的自杀死亡。结果 对于男性来说，用于成瘾性疾病的抗焦虑药和药物的处方与风险概况中的其他特征（例如酒精相关疾病、催眠药和镇静剂）相互作用，导致出院后自杀风险更高。在女性中，复发性重度抑郁症与其他特征（例如中毒、低收入）之间存在相互作用，导致自杀风险增加。随机森林确定了重要的自杀预测因素：男性的酒精相关疾病和尼古丁依赖以及女性的中毒。结论 我们的研究结果表明，准确预测精神病院出院后高危时期的自杀可能需要对男性和女性的多种因素进行复杂的评估。

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