JOURNAL ARTICLE

The impact of palliative care consultation on reducing antibiotic overuse in hospitalized patients with terminal cancer at the end of life: a propensity score-weighting study.

  • Published In: Journal of Antimicrobial Chemotherapy (JAC), 2023, v. 78, n. 1. P. 302 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kim, Jeong Han; Yoo, Shin Hye; Keam, Bhumsuk; Heo, Dae Seog 3 of 3

Abstract

This article examines the impact of palliative care consultation on antibiotic use in hospitalized patients with terminal metastatic solid cancer during the end-of-life phase at a tertiary medical center in Seoul, Republic of Korea. The study found that patients who received palliative care consultation more than three days before death were significantly less likely to receive antibiotics—including broad-spectrum agents such as carbapenems, glycopeptides, and quinolones—within three days before death compared to those without such consultation. Multivariable analysis indicated that palliative care consultation independently reduced antibiotic use near death, suggesting that goals-of-care discussions and improved communication facilitated by palliative teams may influence antibiotic prescribing decisions. The study highlights the complexity of antibiotic use at the end of life, influenced by ethical considerations and cultural factors, and calls for further prospective research to clarify appropriate antibiotic use in this context.

Additional Information

  • Source:Journal of Antimicrobial Chemotherapy (JAC). 2023/01, Vol. 78, Issue 1, p302
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:0305-7453
  • DOI:10.1093/jac/dkac405
  • Accession Number:160965881
  • Copyright Statement:Copyright of Journal of Antimicrobial Chemotherapy (JAC) is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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