Obesity Clinical Trial
— MAMAOOfficial title:
Management of Antipsychotic Medication Associated Obesity
| Verified date | May 2015 |
| Source | VA Office of Research and Development |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | United States: Federal Government |
| Study type | Interventional |
This program aims to help veterans who take antipsychotic medications lose weight. We use a program based on the American Diabetes Association's "Diabetes Prevention Program," and we 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.
| Status | Completed |
| Enrollment | 122 |
| Est. completion date | September 2009 |
| Est. primary completion date | September 2009 |
| Accepts healthy volunteers | No |
| Gender | Both |
| Age group | 18 Years to 70 Years |
| Eligibility |
Inclusion Criteria: - 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 Exclusion Criteria: - Have recently been diagnosed with schizophrenia (less than 1 year) - Are pregnant or breast feeding a baby - Have a medically unstable condition |
Allocation: Randomized, Endpoint Classification: Efficacy Study, Intervention Model: Crossover Assignment, Masking: Open Label, Primary Purpose: Treatment
| Country | Name | City | State |
|---|---|---|---|
| United States | VA Greater Los Angeles Healthcare System, West LA | West Los Angeles | California |
| Lead Sponsor | Collaborator |
|---|---|
| VA Office of Research and Development |
United States,
Guzik LH, Wirshing DA. Behavioral weight loss classes for patients with severe mental illness. Psychiatr Serv. 2007 Nov;58(11):1498. — View Citation
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Mean Weight | Average weight of subjects attending each of the first 8 weekly visits and the 10 monthly visits which followed, per study group. | Weekly/Monthly, up to 1 year | No |
| Primary | Change in Predicted Trajectory of Mean BMI Per GLMM Analysis | 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. | 12 months | No |
| Primary | Change in Predicted Trajectory of Mean Body Fat Percentage Per GLMM Analysis | 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. | 12 months | No |
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