title: Impact of patients' preexisting metabolic risk factors on the choice of antipsychotics by office-based physicians.
abstract: OBJECTIVE
  This study examined the association between patients' preexisting metabolic risk factors and the physician's choice of antipsychotic agent based on its propensity to cause metabolic side effects.
  
  
  METHODS
  Data were from the 2005-2007 National Ambulatory Medical Care Survey (NAMCS); 1,898 office-based visits were identified during which prescriptions of antipsychotics were mentioned. Antipsychotics were classified as having high, medium, or low risk based on their propensity to cause metabolic abnormalities; a separate category for antipsychotic polypharmacy was specified for visits during which multiple antipsychotics were mentioned. Patients' preexisting metabolic risk was assessed by the presence of diabetes, hyperlipidemia, obesity, or hypertension. With controls for other patient and physician characteristics, multinomial logit regression models were applied to examine the association between the level of metabolic risk of the prescribed antipsychotic agents and the patient's baseline metabolic risk.
  
  
  RESULTS
  Compared with patients of normal weight or who were underweight according to body mass index, obese patients were less likely to receive antipsychotics with high risk (relative risk ratio [RRR]=.14, 95% confidence interval [CI]=.05-.37) or medium risk (RRR=.39, CI=.19-.78) of causing metabolic abnormalities. However, having preexisting metabolic conditions, such as diabetes, hyperlipidemia, or hypertension, had little effect on physicians' choice of antipsychotics with regard to metabolic risk properties.
  
  
  CONCLUSIONS
  Patients' weight appeared to be the key consideration in providers' decision to order or continue antipsychotics according to the associated metabolic risk. Further studies are warranted to understand the factors that determine the choice of antipsychotics for patients with preexisting metabolic conditions, such as diabetes, hyperlipidemia, or hypertension.
authors.affiliation: University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. cli@uams.edu
authors.forename: Chenghui
authors.initials: C
authors.lastname: Li
authors.forename: Dinesh
authors.initials: D
authors.lastname: Mittal
authors.forename: Richard R
authors.initials: RR
authors.lastname: Owen
mesh_terms: D000293:Adolescent; D000328:Adult; D000553:Ambulatory Care; D014150:Antipsychotic Agents / Q000009:adverse effects / Q000145:classification / Q000627:therapeutic use*; D002648:Child; D002675:Child, Preschool; D002755:Choice Behavior; D015897:Comorbidity; D003920:Diabetes Mellitus / Q000453:epidemiology; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D057915:Drug Substitution; D004359:Drug Therapy, Combination; D005260:Female; D019538:Health Care Surveys; D006801:Humans; D006949:Hyperlipidemias / Q000453:epidemiology; D006973:Hypertension / Q000453:epidemiology; D007223:Infant; D001523:Mental Disorders / Q000188:drug therapy* / Q000453:epidemiology; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology*; D009819:Office Visits / Q000706:statistics & numerical data; D019338:Polypharmacy; D010818:Practice Patterns, Physicians'; D012044:Regression Analysis; D012307:Risk Factors; D015430:Weight Gain; D055815:Young Adult
chemical_list: D014150:Antipsychotic Agents