Trajectories and predictors of suicidal ideation in clinical characteristics and pharmacological treatments for major depressive disorder: a study based on a national multi-centered prospective cohort.
Ruoxi Ding, Xuequan Zhu, Lei Feng, Le Xiao, Ling Zhang, Ping He, Gang Wang
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引用次数: 0
Abstract
Suicidal ideation (SI) is a significant precursor and risk marker for suicide behaviors in major depressive disorder (MDD). Exploration of SI trajectory from a longitudinal framework are essential for treatment guidelines and clinical management of suicide risk. This study sought to explore SI trajectories and its associated clinical, sociodemographic characteristics, and initial treatment among patients with MDD. We used data from a non-interventional, national multi-centered prospective cohort study. 1 461 patients with MDD were included in the growth mixture modeling using SI at baseline, 2 weeks, 4 weeks, 8 weeks, 12 weeks, and 6 months, 9 months, and 12 months as the indicator. A multinomial regression was employed with SI trajectory as the outcome and anhedonia, depressive symptoms, atypical depressive symptoms, pharmacological treatments, and other covariates as the predictors. Four distinct SI trajectories were identified: a consistently low SI trajectory(50.7%), a persistently mild SI trajectory(20.6%), a fast declined SI trajectory(8.9%), and a slowly declined trajectory(19.8%). Compared to those with a consistently low SI trajectory, a higher score of anhedonia was associated with an increased risk of experiencing persistently mild (RRR = 1.20, 95%CI: 1.05, 1.38) and slowly declined SI (1.54, 95%CI: 1.32, 1.80). Severity of depressive symptom was also positively associated with the risk of experiencing persistently mild (1.15, 95%CI: 1.13, 1.18) and slowly declined SI (1.17, 95%CI: 1.14, 1.21). And the risk of experiencing slowly declined SI was higher for those use SSRI(1.49, 95%CI: 1.02, 2.31), and for those use antidepressant and antipsychotic/mood stabilizer combined therapy (3.78, 95%CI: 1.48, 9.61). The findings of this study are potentially useful for clinical practice as critical indicators of profiles and interventions for prognosis among patients with MDD. Further research is warranted to explore potential modifiable factors and the association between SI trajectories and suicide behavior.
自杀意念(SI)是重度抑郁障碍(MDD)患者自杀行为的重要前兆和风险标志。从纵向框架中探索自杀意念的轨迹对于自杀风险的治疗指南和临床管理至关重要。本研究旨在探索 SI 轨迹及其相关的临床、社会人口学特征以及 MDD 患者的初始治疗。我们使用了一项非干预性、全国性多中心前瞻性队列研究的数据。以基线、2 周、4 周、8 周、12 周、6 个月、9 个月和 12 个月时的 SI 为指标,对 1 461 名 MDD 患者进行了生长混合建模。以 SI 轨迹为结果,以失乐症、抑郁症状、非典型抑郁症状、药物治疗和其他协变量为预测因素,采用多项式回归。结果发现了四种不同的 SI 轨迹:持续低 SI 轨迹(50.7%)、持续轻度 SI 轨迹(20.6%)、快速下降 SI 轨迹(8.9%)和缓慢下降 SI 轨迹(19.8%)。与持续低 SI 轨迹的患者相比,失乐症得分越高,出现持续轻度 SI(RRR = 1.20,95%CI:1.05, 1.38)和缓慢 SI(1.54,95%CI:1.32, 1.80)的风险越高。抑郁症状的严重程度也与出现持续轻度(1.15,95%CI:1.13,1.18)和缓慢下降的 SI(1.17,95%CI:1.14,1.21)的风险呈正相关。而使用 SSRI(1.49,95%CI:1.02,2.31)和抗抑郁药与抗精神病药/情绪稳定剂联合疗法(3.78,95%CI:1.48,9.61)的患者出现 SI 缓慢下降的风险更高。这项研究的结果可能对临床实践很有帮助,因为它是预测 MDD 患者预后的概况和干预措施的关键指标。我们有必要开展进一步研究,探索潜在的可改变因素以及 SI 轨迹与自杀行为之间的关联。
期刊介绍:
Psychiatry has suffered tremendously by the limited translational pipeline. Nobel laureate Julius Axelrod''s discovery in 1961 of monoamine reuptake by pre-synaptic neurons still forms the basis of contemporary antidepressant treatment. There is a grievous gap between the explosion of knowledge in neuroscience and conceptually novel treatments for our patients. Translational Psychiatry bridges this gap by fostering and highlighting the pathway from discovery to clinical applications, healthcare and global health. We view translation broadly as the full spectrum of work that marks the pathway from discovery to global health, inclusive. The steps of translation that are within the scope of Translational Psychiatry include (i) fundamental discovery, (ii) bench to bedside, (iii) bedside to clinical applications (clinical trials), (iv) translation to policy and health care guidelines, (v) assessment of health policy and usage, and (vi) global health. All areas of medical research, including — but not restricted to — molecular biology, genetics, pharmacology, imaging and epidemiology are welcome as they contribute to enhance the field of translational psychiatry.