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The Texas Children's Medication Algorithm Project: Report of the Texas Consensus Conference Panel on Medication Treatment of Childhood Major Depressive Disorder

Overview
Publisher Elsevier
Specialties Pediatrics
Psychiatry
Date 1999 Nov 24
PMID 10560232
Citations 18
Authors
Affiliations
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Abstract

Objectives: To develop consensus guidelines for medication treatment algorithms for childhood major depressive disorder (MDD) based on scientific evidence and clinical opinion when science is lacking. The ultimate goal of this approach is to synthesize research and clinical experience for the practitioner and to increase the uniformity of preferred treatment for childhood MDD. A final goal is to develop an approach that can be tested as to whether it improves clinical outcomes for children and adolescents with MDD.

Method: A consensus conference was held. Participants included academic clinicians and researchers, practicing clinicians, administrators, consumers, and families. The focus was to review and use clinical evidence to recommend specific pharmacological approaches for treatment of MDD in children and adolescents. After a series of presentations of current research evidence and panel discussion, the consensus panel met, agreed on assumptions, and drafted the algorithms. The process initially addressed strategies of treatment and then tactics to implement the strategies.

Results: Consensually agreed-upon algorithms for major depressions (with and without psychosis) and comorbid attention deficit disorders were developed. Treatment strategies emphasized the use of selective serotonin reuptake inhibitors. The algorithm consists of systematic strategies for treatment interventions and recommended tactics for implementation of the strategies, including medication augmentation and medication combinations. Participants recommended prospective evaluation of the algorithms in various public sector settings, and many volunteered as sites for such an evaluation.

Conclusions: Using scientific and clinical experience, consensus-derived algorithms for children and adolescents with MDD can be developed.

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