Management of Antipsychotic Medication Associated Obesity
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 122
- 试验地点
- 2
- 主要终点
- Mean Weight
研究概览
简要总结
This program aims to help Veterans who take antipsychotic medications lose weight. The investigators use a program based on the American Diabetes Association's "Diabetes Prevention Program," and the investigators have modified it to fit the lifestyles of people with mental illness. All participants are educated about nutrition and cutting down fat intake, how and when to exercise, and the causes of diabetes and how to prevent it. Participants must be Veterans who live within one hour of the West Los Angeles VA hospital.
详细描述
Rationale: The focus of this project is to develop a strategy to combat medication associated weight gain, the most problematic side effect of the newer antipsychotic medications. Improvements in long-term health outcomes might then be expected to change quality of life, promote treatment adherence, rehabilitative potential, and decrease resource utilization.
Procedures:
Half of the patients will randomized to the behavioral weight loss program (Lifestyle Balance Program) and do the following: Meet with their psychiatrist and a nutritionist who will go over diet recommendations with the patient Given a 7% weight loss goal Assisted in obtaining a 500 calorie reduction per day Asked to exercise for at least 30 min/day, at least 5 days a week Maintain weekly food and exercise diaries Be quizzed on their knowledge of healthy eating habits and nutrition
The other half of the patients will be randomized to "Usual Care" and will:
Receive pamphlets about Lifestyle Balance, starting exercise, and general nutritional information regarding food pyramids and the amount of calories in fast foods.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Crossover
- 主要目的
- Treatment
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 70 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Must be a Veteran
- •Diagnosis of psychotic disorders, schizophrenia, schizoaffective disorder and bipolar illness
- •Age 18-70
- •Clinically determined to require ongoing treatment with Second Generation Antipsychotics (SGA) such as olanzapine, risperidone, quetiapine, ziprasidone, aripiprazole, clozapine
- •Experienced weight gain since treatment with SGA's
- •Inpatient or outpatient at the West Los Angeles VA
- •Competent to sign informed consent
排除标准
- •Have recently been diagnosed with schizophrenia (less than 1 year)
- •Are pregnant or breast feeding a baby
- •Have a medically unstable condition
结局指标
主要结局
Mean Weight
时间窗: Weekly/Monthly, up to 1 year
Average weight of subjects attending each of the first 8 weekly visits and the 10 monthly visits which followed, per study group.
Change in Predicted Trajectory of Mean Body Fat Percentage Per GLMM Analysis
时间窗: 12 months
Computed as % body fat at 12 month - % body fat at baseline. General Linear Mixed Model (GLMM) is a full information maximum likelihood approach that permits inclusion of all available data and provides unbiased parameter estimates even if there are missing data under the condition that data are missing at random. The GLMM approach assumes that every patient is on a specific trajectory over time and that both the slope and the shape of this trajectory are a potential function of group membership or other person-level covariates. Using a likelihood ratio test, we found a linear model, assuming the same rate of change throughout the study, provided a good fit to the data compared to other models. We used a linear model of the average rate of change over time (slope) for all comparisons. To illustrate the magnitude of difference between slopes for major outcomes, we report the estimated difference at 12 months between two hypothetical participants with identical baseline characteristics.
Change in Predicted Trajectory of Mean BMI Per GLMM Analysis
时间窗: 12 months
General Linear Mixed Model (GLMM) is a full information maximum likelihood approach that permits inclusion of all available data and provides unbiased parameter estimates even if there are missing data under the condition that data are missing at random. The GLMM approach assumes that every patient is on a specific trajectory over time and that both the slope and the shape of this trajectory are a potential function of group membership or other person-level covariates. Using a likelihood ratio test, we compared different options to model these trajectories and found a linear model, which assumes that the same rate of change is maintained over the whole study, provided a good fit to the data. We used a linear model of the average rate of change over time (slope) for all comparisons. To illustrate the magnitude of difference between slopes for major outcomes, we report the estimated difference at 12 months between two hypothetical participants with identical baseline characteristics.
次要结局
未报告次要终点