Abstract
Background Antipsychotic polypharmacy (APP) occurs commonly but it is unclear whether it is associated with an increased risk of adverse drug reactions (ADRs). Electronic health records (EHRs) offer an opportunity to examine APP using real-world data. In this study, we use EHR data to identify periods when patients were prescribed 2 + antipsychotics and compare these with periods of antipsychotic monotherapy. To determine the relationship between APP and subsequent instances of ADRs: QT interval prolongation, hyperprolactinaemia, and increased body weight [body mass index (BMI) >25]. Methods We extracted anonymised EHR data. Patients aged 16 + receiving antipsychotic medication at Camden & Islington NHS Foundation Trust between 1 January 2008 and 31 December 2018 were included. Multilevel mixed-effects logistic regression models were used to elucidate the relationship between APP and the subsequent presence of QT interval prolongation, hyperprolactinaemia, and/or increased BMI following a period of APP within 7, 30, or 180 days respectively. Results We identified 35 409 observations of antipsychotic prescribing among 13 391 patients. Compared with antipsychotic monotherapy, APP was associated with a subsequent increased risk of hyperprolactinaemia (adjusted odds ratio 2.46; 95% CI 1.87-3.24) and of registering a BMI > 25 (adjusted odds ratio 1.75; 95% CI 1.33-2.31) in the period following the APP prescribing. Conclusions Our observations suggest that APP should be carefully managed with attention to hyperprolactinaemia and obesity.
| Original language | English |
|---|---|
| Pages (from-to) | 4220-4227 |
| Number of pages | 8 |
| Journal | Psychological Medicine |
| Volume | 53 |
| Issue number | 9 |
| Early online date | 29 Apr 2022 |
| DOIs | |
| State | Published - 29 Jul 2023 |
Bibliographical note
Publisher Copyright:Copyright © The Author(s), 2022. Published by Cambridge University Press.
Funding
This work was supported by the Medical Research Council (MC_PC_17216 and MR/W014386/1). David P.J. Osborn is also supported by the University College London Hospitals NIHR Biomedical Research Centre and the NIHR North Thames Applied Research Collaboration. Joseph F. Hayes is supported by UKRI grant MR/V023373/1, the University College London Hospitals NIHR Biomedical Research Centre and the NIHR North Thames Applied Research Collaboration. This funder had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The views expressed in this article are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care.
| Funders | Funder number |
|---|---|
| NIHR North Thames Applied Research Collaboration | |
| UK Research and Innovation | MR/V023373/1 |
| Medical Research Council | MC_PC_17216, MR/W014386/1 |
| University College London Hospitals Biomedical Research Centre |
Keywords
- antipsychotic polypharmacy
- antipsychotics
- electronic health records
- natural language processing
