Salvo Lilian, Saldivia Sandra, Parra Carlos, Cifuentes Manuel, Bustos Claudio, Acevedo Paola, Díaz Marcela, Ormazabal Mitza, Guerra Ivonne, Navarrete Nicol, Bravo Verónica, Castro Andrea
Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepción, Chile.
Departamento de Psiquiatría y Salud Mental, Facultad de Medicina, Universidad de Concepción, Concepción, Chile.
Rev Med Chil. 2017 Dec;145(12):1514-1524. doi: 10.4067/s0034-98872017001201514.
Background The knowledge of predictive factors in depression should help to deal with the disease. Aim To assess potential predictors of remission of major depressive disorders (MDD) in secondary care and to propose a predictive model. Material and Methods A 12 month follow-up study was conducted in a sample of 112 outpatients at three psychiatric care centers of Chile, with baseline and quarterly assessments. Demographic, psychosocial, clinical and treatment factors as potential predictors, were assessed. A clinical interview with the checklist of DSM-IV diagnostic criteria, the Hamilton Depression Scale and the List of Threatening Experiences and Multidimensional Scale of Perceived Social Support were applied. Results The number of stressful events, perceived social support, baseline depression scores, melancholic features, time prior to beginning treatment at the secondary level and psychotherapeutic sessions were included in the model as predictors of remission. Sex, age, number of previous depressive episodes, psychiatric comorbidity and medical comorbidity were not significantly related with remission. Conclusions This model allows to predict depression score at six months with 70% of accuracy and the score at 12 months with 72% of accuracy.
背景 了解抑郁症的预测因素应有助于应对该疾病。目的 评估二级护理中重度抑郁症（MDD）缓解的潜在预测因素，并提出一个预测模型。材料与方法 对智利三个精神科护理中心的112名门诊患者进行了为期12个月的随访研究，进行了基线和季度评估。评估了人口统计学、心理社会、临床和治疗因素作为潜在预测因素。应用了符合《精神疾病诊断与统计手册》第四版诊断标准清单的临床访谈、汉密尔顿抑郁量表、威胁性经历清单和感知社会支持多维量表。结果 应激事件数量、感知社会支持、基线抑郁评分、抑郁特征、二级护理开始治疗前的时间以及心理治疗次数被纳入模型作为缓解的预测因素。性别、年龄、既往抑郁发作次数、精神科合并症和内科合并症与缓解无显著相关性。结论 该模型能够以70%的准确率预测六个月时的抑郁评分，以72%的准确率预测12个月时的评分。
