首页> 外文期刊>The journal of clinical psychiatry >Texas Medication Algorithm Project, phase 3 (TMAP-3): clinical results for patients with a history of mania.
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Texas Medication Algorithm Project, phase 3 (TMAP-3): clinical results for patients with a history of mania.

机译:德州药物治疗算法项目,第3阶段(TMAP-3):具有躁狂病史的患者的临床结果。

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BACKGROUND: The Texas Medication Algorithm Project (TMAP) assessed the clinical and economic impact of algorithm-driven treatment (ALGO) as compared with treatment-as-usual (TAU) in patients served in public mental health centers. This report presents clinical outcomes in patients with a history of mania (BD), including bipolar I and schizoaffective disorder, bipolar type, during 12 months of treatment beginning March 1998 and ending with the final active patient visit in April 2000. METHOD: Patients were diagnosed with bipolar I disorder or schizoaffective disorder, bipolar type, according to DSM-IV criteria. ALGO was comprised of a medication algorithm and manual to guide treatment decisions. Physicians and clinical coordinators received training and expert consultation throughout the project. ALGO also provided a disorder-specific patient and family education package. TAU clinics had no exposure to the medication algorithms. Quarterly outcome evaluations were obtained by independent raters. Hierarchical linear modeling, based on a declining effects model, was used to assess clinical outcome of ALGO versus TAU. RESULTS: ALGO and TAU patients showed significant initial decreases in symptoms (p =.03 and p <.001, respectively) measured by the 24-item Brief Psychiatric Rating Scale (BPRS-24) at the 3-month assessment interval, with significantly greater effects for the ALGO group. Limited catch-up by TAU was observed over the remaining 3 quarters. Differences were also observed in measures of mania and psychosis but not in depression, side-effect burden, or functioning. CONCLUSION: For patients with a history of mania, relative to TAU, the ALGO intervention package was associated with greater initial and sustained improvement on the primary clinical outcome measure, the BPRS-24, and the secondary outcome measure, the Clinician-Administered Rating Scale for Mania (CARS-M). Further research is planned to clarify which elements of the ALGO package contributed to this between-group difference.
机译:背景:与公共治疗中心的常规治疗(TAU)相比,德州药物治疗算法项目(TMAP)评估了算法驱动治疗(ALGO)的临床和经济影响。本报告介绍了1998年3月至2000年4月最后一次活动患者就诊的12个月内有躁狂症(BD)病史的患者的临床结局,包括双相性I和躁郁症(双相型)。根据DSM-IV标准诊断为双相I型躁郁症或双情感型躁郁症。 ALGO由药物治疗算法和指导治疗决策的手册组成。在整个项目过程中,医师和临床协调员都接受了培训和专家咨询。 ALGO还提供了针对特定疾病的患者和家庭教育套餐。 TAU诊所没有接触过药物治疗算法。季度结果评估由独立评估者获得。基于递减效应模型的分层线性建模用于评估ALGO与TAU的临床结局。结果:ALGO和TAU患者在3个月的评估时间间隔内,通过24项简短精神病评定量表(BPRS-24)测得的症状出现了明显的初始减轻(分别为p = .03和p <.001)。对ALGO小组的影响更大。在剩下的三个季度中,观察到的TAU追赶次数有限。在躁狂和精神病的测量上也观察到差异,但在抑郁,副作用负担或功能上没有差异。结论:相对于TAU,对于有躁狂病史的患者,ALGO干预措施与主要临床结局指标BPRS-24和次要结局指标(临床医师管理的评分量表)的初步和持续改善相关疯狂(CARS-M)。计划进行进一步研究,以弄清ALGO软件包中的哪些因素导致了群体之间的差异。

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