Patient Heterogeneity and the J-Curve Relationship Between Time-to-Antibiotics and the Outcomes of Patients Admitted With Bacterial Infection

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Abstract

OBJECTIVES: Sepsis remains a leading and preventable cause of hospital utilization and mortality in the United States. Despite updated guidelines, the optimal definition of sepsis as well as optimal timing of bundled treatment remain uncertain. Identifying patients with infection who benefit from early treatment is a necessary step for tailored interventions. In this study, we aimed to illustrate clinical predictors of time-to-antibiotics among patients with severe bacterial infection and model the effect of delay on risk-adjusted outcomes across different sepsis definitions.

DESIGN: A multicenter retrospective observational study.

SETTING: A seven-hospital network including academic tertiary care center.

PATIENTS: Eighteen-thousand three-hundred fifteen patients admitted with severe bacterial illness with or without sepsis by either acute organ dysfunction (AOD) or systemic inflammatory response syndrome positivity.

MEASUREMENTS AND MAIN RESULTS: The primary exposure was time to antibiotics. We identified patient predictors of time-to-antibiotics including demographics, chronic diagnoses, vitals, and laboratory results and determined the impact of delay on a composite of inhospital death or length of stay over 10 days. Distribution of time-to-antibiotics was similar across patients with and without sepsis. For all patients, a J-curve relationship between time-to-antibiotics and outcomes was observed, primarily driven by length of stay among patients without AOD. Patient characteristics provided good to excellent prediction of time-to-antibiotics irrespective of the presence of sepsis. Reduced time-to-antibiotics was associated with improved outcomes for all time points beyond 2.5 hours from presentation across sepsis definitions.

CONCLUSIONS: Antibiotic timing is a function of patient factors regardless of sepsis criteria. Similarly, we show that early administration of antibiotics is associated with improved outcomes in all patients with severe bacterial illness. Our findings suggest identifying infection is a rate-limiting and actionable step that can improve outcomes in septic and nonseptic patients.

Original languageEnglish (US)
Pages (from-to)799-809
Number of pages11
JournalCritical care medicine
Volume50
Issue number5
Early online dateDec 31 2021
DOIs
StatePublished - May 1 2022

Bibliographical note

Funding Information:
Dr. Usher, Tourani, Dr. Pruinelli, and Dr. Simon received support for article research from the National Institutes of Health (NIH). Dr. Melton’s institution received funding from the NIH and the Agency for Healthcare Quality and Research (AHRQ); she received funding from the American Medical Informatics Association, the American College of Medical Informatics, the AHRQ, the American Board of Preventative Medicine, and St. Jude (Abbott) Medical. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Funding Information:
Supported, in part, by grant from the National Institute of Health (R01 GM120079, to Dr. Simon).

Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.

PubMed: MeSH publication types

  • Journal Article
  • Multicenter Study
  • Observational Study
  • Research Support, N.I.H., Extramural

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