Park C Hyung Keun, Kim Hyeyoung, Kim Bora, Kim Eun Young, Lee Hyun Jeong, Kim Daewook, Ahn Yong Min
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California.
Department of Psychiatry, Pusan National University Yangsan Hospital, Yangsan-si, Gyeongsangnam-do, Republic of Korea.
J Nerv Ment Dis. 2019 Feb;207(2):59-68. doi: 10.1097/NMD.0000000000000921.
Identifying predictors of planned suicide attempts (PSA) is critical because these are associated with grave consequences. Using data of suicide attempters visiting emergency departments, we investigated whether the Columbia-Suicide Severity Rating Scale (C-SSRS) subscales, by retrospectively evaluating ideation before an attempt, could predict the occurrence of PSA versus unplanned suicide attempts using logistic regression analyses. The severity subscale was used as a continuous (model A) and a categorical (model B) variable. In model A, higher scores on each subscale were associated with increased risk of PSA. In model B, the highest score on the severity subscale and a higher intensity subscale score predicted PSA. The severity and intensity subscales had areas under receiver operating curves of 0.712 and 0.688 with optimum cutoff points of 4/5 and 15/16, respectively. In addition, being aged 30 to 49 and 50 to 69 years, being male, interpersonal stress, and depressive and adjustment disorders increased PSA risk. The C-SSRS subscales, along with sociodemographic and clinical risk factors, can predict PSA.
识别有计划自杀未遂(PSA)的预测因素至关重要,因为这些因素会带来严重后果。利用前往急诊科的自杀未遂者的数据,我们通过回顾性评估自杀未遂前的意念,研究哥伦比亚自杀严重程度评定量表(C-SSRS)的分量表是否能够使用逻辑回归分析预测PSA与无计划自杀未遂的发生情况。严重程度分量表被用作连续变量(模型A)和分类变量(模型B)。在模型A中,每个分量表得分越高,PSA风险越高。在模型B中,严重程度分量表的最高分和较高的强度分量表得分可预测PSA。严重程度和强度分量表的受试者工作特征曲线下面积分别为0.712和0.688,最佳临界点分别为4/5和15/16。此外,年龄在30至49岁和50至69岁之间、男性、人际压力以及抑郁和适应障碍会增加PSA风险。C-SSRS分量表以及社会人口学和临床风险因素能够预测PSA。