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Consultants: Jillian Lyon and Mary Ehlers The Impact of Atypical Antipsychotic Use on Obstructive Sleep Apnea.

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Presentation on theme: "Consultants: Jillian Lyon and Mary Ehlers The Impact of Atypical Antipsychotic Use on Obstructive Sleep Apnea."— Presentation transcript:

1 Consultants: Jillian Lyon and Mary Ehlers The Impact of Atypical Antipsychotic Use on Obstructive Sleep Apnea

2 Background The main focus of this study was to see if atypical antipsychotic medication was linked with sleep apnea. To investigate this, the client used information from the U of I sleep laboratories from 2005-2009. The client included many covariates widely accepted to be predictors of sleep apnea. To test the hypothesis, one treatment group and two control groups were used.

3 Three Groups Atypical Antipsychotics Group: Patients using atypical antipsychotics, regardless of other psychiatric issues (84 subjects) Depressive Disorder Group: Patients with a clinical diagnosis of depression using other psychiatric medication, but not using atypical antipsychotics (200 subjects) Mentally Healthy Group: Mentally healthy controls not taking antipsychotics (331 subjects)

4 Variables Measured Continuous Variables: Age BMI (Body Mass Index) Neck Circumference AHI (Apnea-Hypopnea Index): Number of episodes divided by the total number of sleep hours SpO2: measures oxygen saturation level Categorical Variables: Group (Listed on previous slide) Gender

5 Variables Measured (Continued) Binary Variables: OSA (Obstructive Sleep Apnea): classified as “yes” if AHI was greater than or equal to 5. DM (Diabetes Mellitus) CAD (Coronary Artery Disease) COPD (Chronic Obstructive Pulmonary Disease) HTN (Hypertension): high blood pressure Hypothyroid: disease caused by insufficient production of thyroid hormone AD (Antidepressant Use) Benzodiazepine Use: antipsychotic used for anxiety

6 Consultants’ Objectives 1. Ensure that the models were correctly fit and the significance of variables was reported accurately. 2. Verify statistical claims made in the paper as well as investigate some possible problems with correlation between categorical variables. 3. Advise client as to which tables and graphics to include in the paper.

7 Model 1: Diagnosis of OSA Logistic regression with OSA as the response variable. All of the variables measured were included in the model with the exception of AHI and SpO2. Significant predictors: Age, BMI, Sex, and NC Note: We also fit the saturated model using specific individual drugs rather than just grouping them all into “antidepressant use” and came to the same conclusions (i.e. the individual drugs were not significant)

8 Model 2: OSA Severity Regular linear regression with AHI as the response. All of the variables measured were included in the model with the exception of OSA and SpO2. However, this model was fit using only the information from subjects that were diagnosed as having OSA, i.e. those with AHI greater than or equal to 5 Significant predictors: BMI, NC, and Hypothyroid

9 Model 2 (Continued) Regular linear regression with AHI as the response and all subjects included, regardless of OSA diagnosis. Significant predictors: Sex, Age, BMI, NC, DM, Hypothyroid, and Benzo The client did not fit this model, but after verifying that the residuals did not behave differently from the model with just OSA positive subjects, we recommended this model be used instead of the one the client fit.

10 Model 3: Oxygen Deprivation Regular linear regression with SpO2 as the response. All of the variables measured were included in the model with the exception of OSA and AHI. However, this model was fit using only the information from subjects that were diagnosed as having OSA, i.e. those with AHI greater than or equal to 5 Significant predictors: Age and BMI

11 Model 3 (Continued) Regular linear regression with SpO2 as the response and all subjects included, regardless of OSA diagnosis. Significant predictors: Sex, Age, BMI, NC, and Hypothyroid The client did not fit this model, but after verifying that the residuals did not behave differently from the model with just OSA positive subjects, we recommended this model be used instead of the one the client fit.

12 Conclusions 1. The client incorrectly fit the models, treating every variable as continuous. This had an effect on what was significant. However, Group was never shown to be significant, so there was no evidence to support the claim of a relationship between Atypical Antipsychotic Drugs and Sleep Apnea.

13 Conclusions (Continued) 2. Determined that the issue of correlation between categorical explanatory variables was not relevant since we were not using the models to predict OSA in future subjects. 3. Recommended the inclusion of one particular table as many of the magazines we examined did not include many tables, especially ones of regression coefficient estimates.


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