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Distinct patterns of vital sign and inflammatory marker responses in adults with suspected bloodstream infection

Abstract:

Objectives: To identify patterns in inflammatory marker and vital sign responses in adult with suspected bloodstream infection (BSI) and define expected trends in normal recovery.

Methods: We included patients ≥16 y from Oxford University Hospitals with a blood culture taken between 1-January-2016 and 28-June-2021. We used linear and latent class mixed models to estimate trajectories in C-reactive protein (CRP), white blood count, heart rate, respiratory rate and temperature and identify CRP response subgroups. Centile charts for expected CRP responses were constructed via the lambda-mu-sigma method.

Results: In 88,348 suspected BSI episodes; 6908 (7.8%) were culture-positive with a probable pathogen, 4309 (4.9%) contained potential contaminants, and 77,131(87.3%) were culture-negative. CRP levels generally peaked 1–2 days after blood culture collection, with varying responses for different pathogens and infection sources (p < 0.0001). We identified five CRP trajectory subgroups: peak on day 1 (36,091; 46.3%) or 2 (4529; 5.8%), slow recovery (10,666; 13.7%), peak on day 6 (743; 1.0%), and low response (25,928; 33.3%). Centile reference charts tracking normal responses were constructed from those peaking on day 1/2.

Conclusions: CRP and other infection response markers rise and recover differently depending on clinical syndrome and pathogen involved. However, centile reference charts, that account for these differences, can be used to track if patients are recovering as expected and to help personalise infection treatment.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jinf.2024.106156

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Big Data Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Big Data Institute
Role:
Author


Publisher:
Elsevier
Journal:
Journal of Infection More from this journal
Volume:
88
Issue:
5
Article number:
106156
Publication date:
2024-04-08
Acceptance date:
2024-04-04
DOI:
EISSN:
1532-2742
ISSN:
0163-4453


Language:
English
Keywords:
Pubs id:
1987863
Local pid:
pubs:1987863
Deposit date:
2024-04-04

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