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儿童抑郁症药物治疗算法的可行性研究:德克萨斯儿童药物治疗算法项目(CMAP)。

A feasibility study of the childhood depression medication algorithm: the Texas Children's Medication Algorithm Project (CMAP).

作者信息

Emslie Graham J, Hughes Carroll W, Crismon M Lynn, Lopez Molly, Pliszka Steve, Toprac Marcia G, Boemer Christine

机构信息

University of Texas Southwestern Medical Center-Dallas, TX 75390-8589, USA.

出版信息

J Am Acad Child Adolesc Psychiatry. 2004 May;43(5):519-27. doi: 10.1097/00004583-200405000-00005.

Abstract

OBJECTIVE

To evaluate the feasibility and impact on clinical response and function associated with the use of an algorithm-driven disease management program (ALGO) for children and adolescents treated for depression with or without attention-deficit/hyperactivity disorder (ADHD) in community mental health centers.

METHOD

Interventions included (1). medication algorithms, (2). clinical and technical support for the physician, (3). uniform chart documentation of outcomes, and (4). a patient/family psychoeducation program. Children eligible for entry into the study were referred to the child psychiatrist for initiation or change in medicine. Outcomes of treatment with the ALGO for up to 4 months are presented. Measures of change included clinical symptoms, functioning, and global improvement (Clinical Global Impression Scale). A historical chart cohort from the same clinics was used as a quasi-control.

RESULTS

Thirty-nine individuals (depression = 24; comorbid depression with ADHD = 15) were enrolled for treatment with ALGO. One hundred fourteen children were in the control cohort (74 depressed, 40 comorbid). For the ALGO groups, Children's Depression Rating Scale-Revised depression severity scores decreased from 48.2 to 32.5 and Child Adolescent Functioning Assessment Scale function scores improved from 70.3 to 40.9 (all p < or =.0005). Clinical Global Impression Scale severity scores decreased from 5.7 to 3.7 in ALGO compared to only 5.8 to 4.8 in the control (p <.003).

CONCLUSIONS

There was clear improvement in clinical symptoms, functioning, and global response with ALGO treatment. The magnitude of the improvement was greater in children and adolescents treated with the ALGO program compared with a historical cohort. These data support the need for controlled studies in larger populations examining the effects of algorithm-driven disease management programs on the clinical outcomes of children with mental illness.

摘要

目的

评估在社区心理健康中心使用算法驱动的疾病管理项目(ALGO)对患有或未患有注意力缺陷多动障碍(ADHD)的抑郁症儿童和青少年的可行性及其对临床反应和功能的影响。

方法

干预措施包括(1)药物治疗算法,(2)为医生提供临床和技术支持,(3)统一记录结果的图表,以及(4)患者/家庭心理教育项目。符合研究纳入标准的儿童被转介给儿童精神科医生以开始或改变药物治疗。呈现了使用ALGO治疗长达4个月的结果。变化的测量指标包括临床症状、功能以及整体改善情况(临床总体印象量表)。来自同一诊所的历史图表队列用作准对照。

结果

39名个体(抑郁症患者24名;合并抑郁症和ADHD患者15名)登记接受ALGO治疗。114名儿童在对照队列中(74名抑郁症患者,40名合并症患者)。对于ALGO组,儿童抑郁评定量表修订版的抑郁严重程度评分从48.2降至32.5,儿童青少年功能评估量表的功能评分从70.3提高到40.9(所有p<或=0.0005)。与对照组仅从5.8降至4.8相比,ALGO组的临床总体印象量表严重程度评分从5.7降至3.7(p<0.003)。

结论

ALGO治疗在临床症状、功能和整体反应方面有明显改善。与历史队列相比,接受ALGO项目治疗的儿童和青少年的改善程度更大。这些数据支持需要在更大规模人群中进行对照研究,以检验算法驱动的疾病管理项目对患有精神疾病儿童临床结局的影响。

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