The Association of Nonmodifiable Patient Factors on Antipsychotic Medication use in the Intensive Care Unit

JOURNAL OF INTENSIVE CARE MEDICINE(2024)

引用 0|浏览3
暂无评分
摘要
Purpose We investigated the association of age, sex, race, and insurance status on antipsychotic medication use among intensive care unit (ICU) patients.Materials and Methods Retrospective study of adults admitted to ICUs at a tertiary academic center. Patient characteristics, hospital course, and medication (olanzapine, quetiapine, and haloperidol) data were collected. Logistic regression models evaluated the independent association of age, sex, race, and insurance status on the use of each antipsychotic, adjusting for prespecified covariates.Results Of 27,137 encounters identified, 6191 (22.8%) received antipsychotics. Age was significantly associated with the odds of receiving olanzapine (P < .001), quetiapine (P = .001), and haloperidol (P = .0046). Male sex and public insurance status were associated with increased odds of receiving antipsychotics olanzapine, quetiapine, and haloperidol (Male vs Female: OR 1.13, 95% CI [1.04, 1.24], P = .0005; OR 1.22, 95% CI [1.10, 1.34], P = .0001; OR 1.28, 95% CI [1.17, 1.40], P < .0001, respectively; public insurance vs private insurance: OR 1.32, 95% CI [1.20, 1.46], P < .0001; OR 1.21, 95% CI [1.09, 1.34], P = .0004; OR 1.15, 95% CI [1.04, 1.27], P = .0058, respectively). Black race was also associated with a decreased odds of receiving all antipsychotics (olanzapine (P = .0177), quetiapine (P = .004), haloperidol (P = .0041)).Conclusions Age, sex, race, and insurance status were associated with the use of all antipsychotic medications investigated, highlighting the importance of investigating the potential impact of these prescribing decisions on patient outcomes across diverse populations. Recognizing how nonmodifiable patient factors have the potential to influence prescribing practices may be considered an important factor toward optimizing medication regimens.
更多
查看译文
关键词
antipsychotic agents,critical illness,delirium,intensive care units,patient discharge
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要