title: Second-generation antipsychotics in a tertiary care hospital: prescribing patterns, metabolic profiles, and drug interactions.
abstract: We carried out an observational study that analyzed population characteristics, metabolic profiles, potentially interacting pharmacotherapy, and related adverse events in second-generation antipsychotics (SGAs) users of a tertiary care hospital. Within our pharmacoepidemiological database derived from electronic medical records of 82,358 hospitalizations, we identified 1136 hospitalizations contributing 9165 patient-days with exposure to SGA. Blood pressure, blood glucose, lipids, and BMI had been documented in 97.7, 75.7, 24.6, and 77.4% of hospitalizations, respectively. Among these, the prevalence of hypertension, hyperglycemia, dyslipidemia, and BMI 30 kg/m or more was 36.9, 22.6, 61.1, and 23.1%, respectively. A total of 63.4, 70.8, and 37.1% of SGA users with hyperglycemia, dyslipidemia, and hypertension, respectively, received no pharmacotherapy for these conditions. We identified 614 patient-days with SGA plus formally contraindicated comedication and another 1066 patient-days with other high-risk combinations for QTc prolongation. Among those there was one case with associated neutropenia and four cases with abnormal QTc interval. However, specific monitoring for such adverse events was not documented in 45.5% of hospitalizations with contraindicated and 89.8% with high-risk QTc-prolonging combinations. Our study identified targets for improved monitoring and management in SGA users. These may be implemented as automated alerts into electronic prescribing systems and thereby efficiently support safer pharmacotherapy in clinical practice.
authors.affiliation: aDepartment of Clinical Pharmacology and Toxicology bDepartment of Medical Informatics, University Hospital Zurich cSwiss Federal Institute of Technology Zurich (ETHZ) dZurich Center for Integrative Human Physiology (ZIHP), Zurich eDrugsafety.ch, Küsnacht, Switzerland fDepartment of Psychiatry, Ludwig-Maximilian University, Munich, Germany.
authors.forename: David F
authors.initials: DF
authors.lastname: Niedrig
authors.forename: Carmen
authors.initials: C
authors.lastname: Gött
authors.forename: Anja
authors.initials: A
authors.lastname: Fischer
authors.forename: Sabrina T
authors.initials: ST
authors.lastname: Müller
authors.forename: Waldemar
authors.initials: W
authors.lastname: Greil
authors.forename: Guido
authors.initials: G
authors.lastname: Bucklar
authors.forename: Stefan
authors.initials: S
authors.lastname: Russmann
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014150:Antipsychotic Agents / Q000009:adverse effects / Q000627:therapeutic use*; D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism; D001794:Blood Pressure / Q000187:drug effects; D015992:Body Mass Index; D000075202:Contraindications; D016208:Databases, Factual; D004347:Drug Interactions; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D004363:Drug Utilization; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008055:Lipids / Q000097:blood; D008297:Male; D008660:Metabolism / Q000187:drug effects; D008875:Middle Aged; D017891:Pharmacoepidemiology; D062606:Tertiary Care Centers; D055815:Young Adult
chemical_list: D014150:Antipsychotic Agents; D001786:Blood Glucose; D008055:Lipids