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PreprintCC BY-NC-NDmedRxiv

Parametric Models for Predicting Gram-negative Antibiotic Susceptibility Phenotype: A Brief Report

  • A. Garg
  • C. Graham
  • N. Daneman
  • D. MacFadden1
  1. 1Ottawa Hospital Research Institute
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Abstract

Predicted probabilities of antibiotic susceptibility to known or suspected pathogens can be used to support antibiotic selection. Patient demographic, clinical, and prior microbiologic history can be used to generate location-specific prediction models. For three Canadian tertiary care institutions we fit and evaluated models for predicting Gram-negative antibiotic susceptibilities to common antimicrobial agents based on previously established model structures. A web-based application was developed to permit visualization of antibiotic susceptibility predictions and support antibiotic decision-making.

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Cite

BibTeXRIS
BibTeX
@misc{garg2026parametric,
  title = {{Parametric Models for Predicting Gram-negative Antibiotic Susceptibility Phenotype: A Brief Report}},
  author = {A. Garg and C. Graham and N. Daneman and D. MacFadden},
  howpublished = {medRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.01.26363073},
  url = {https://www.medrxiv.org/content/10.64898/2026.10.01.26363073v1},
  note = {CC BY-NC-ND},
}
RIS
TY  - UNPB
TI  - Parametric Models for Predicting Gram-negative Antibiotic Susceptibility Phenotype: A Brief Report
AU  - A. Garg
AU  - C. Graham
AU  - N. Daneman
AU  - D. MacFadden
PY  - 2026
DA  - 2026/10/01
PB  - medRxiv
DO  - 10.64898/2026.10.01.26363073
UR  - https://www.medrxiv.org/content/10.64898/2026.10.01.26363073v1
AB  - Predicted probabilities of antibiotic susceptibility to known or suspected pathogens can be used to support antibiotic selection. Patient demographic, clinical, and prior microbiologic history can be used to generate location-specific prediction models. For three Canadian tertiary care institutions we fit and evaluated models for predicting Gram-negative antibiotic susceptibilities to common antimicrobial agents based on previously established model structures. A web-based application was developed to permit visualization of antibiotic susceptibility predictions and support antibiotic decision-making.
ER  -