Microbial traits have minimal power for predicting death from bloodstream infection

Abstract

Bloodstream infection (BSI) is a life-threatening condition where the risk of dying is affected by both patient-and pathogen-related factors. Certain microbial traits (e.g., virulence genes) are thought to affect survival rates from BSIs, but the magnitude of their impact on human mortality remains unclear. To address this, we analyzed the microbial genomes, quantitative proteomes, and electronic medical records (EMRs) from 35,746 BSIs from Calgary, Canada (2006-2022). We show that EMR-based machine learning models accurately predict 30-day mortality (AUC=0.83), but surprisingly, integrating >70,000 microbial genes/proteins does not improve this performance. We demonstrate that microbial factors co-segregate with specific patient cohorts and are therefore not independent predictors of risk. We conclude that microbial virulence factors have minimal impact on mortality rates from BSIs.

One-Sentence SummaryMicrobial genes and protein abundance levels have minimal power for predicting 30-day mortality in bloodstream infections.

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BibTeX RIS

BibTeX

@misc{gilliland2026microbial,
  title = {{Microbial traits have minimal power for predicting death from bloodstream infection}},
  author = {R. Gilliland and M. E. Valdes-Tresanco and A. Plakhotnyk and A. Westlund and J. T. Smith and T. M. Pham and T. D. Mortimer and B. J. Walker and A. M. Earl and Y. H. Grad and M. E. MacDonald and I. A. Lewis and PRIME Consortium},
  howpublished = {medRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.08.26365081},
  url = {https://www.medrxiv.org/content/10.64898/2026.10.08.26365081v1},
  note = {CC BY-NC},
}

RIS

TY  - UNPB
TI  - Microbial traits have minimal power for predicting death from bloodstream infection
AU  - R. Gilliland
AU  - M. E. Valdes-Tresanco
AU  - A. Plakhotnyk
AU  - A. Westlund
AU  - J. T. Smith
AU  - T. M. Pham
AU  - T. D. Mortimer
AU  - B. J. Walker
AU  - A. M. Earl
AU  - Y. H. Grad
AU  - M. E. MacDonald
AU  - I. A. Lewis
AU  - PRIME Consortium
PY  - 2026
DA  - 2026/10/08
PB  - medRxiv
DO  - 10.64898/2026.10.08.26365081
UR  - https://www.medrxiv.org/content/10.64898/2026.10.08.26365081v1
AB  - Bloodstream infection (BSI) is a life-threatening condition where the risk of dying is affected by both patient-and pathogen-related factors. Certain microbial traits (e.g., virulence genes) are thought to affect survival rates from BSIs, but the magnitude of their impact on human mortality remains unclear. To address this, we analyzed the microbial genomes, quantitative proteomes, and electronic medical records (EMRs) from 35,746 BSIs from Calgary, Canada (2006-2022). We show that EMR-based machine learning models accurately predict 30-day mortality (AUC=0.83), but surprisingly, integrating >70,000 microbial genes/proteins does not improve this performance. We demonstrate that microbial factors co-segregate with specific patient cohorts and are therefore not independent predictors of risk. We conclude that microbial virulence factors have minimal impact on mortality rates from BSIs.  One-Sentence SummaryMicrobial genes and protein abundance levels have minimal power for predicting 30-day mortality in bloodstream infections.
ER  -

Abstract

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