ArticleInternational journal of critical illness and injury science
A Bayesian genomic-enhanced precision critical care early warning model for septic shock outcomes.
Article in International journal of critical illness and injury science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- What's new in critical illness and injury science? Bayesian genomics and the next frontier of early sepsis prediction: Promise, pitfalls, and the path forward.International journal of critical illness and injury scienceArticle
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Septic shock remains a significant contributor to mortality, with high patient variability in treatment response. Precision medicine offers promise in addressing this complexity. This study aimed to develop a Bayesian genomic-enhanced precision critical care clinical decision/probability model to predict outcomes in septic shock patients. Methods: Utilizing Bayesian modeling, we integrated clinical scoring systems (e.g., the Miami sepsis score and point of care lactate) with genomic data. Sensitivity and specificity from prior studies were incorporated into the model. The effectiveness of a genomic-based approach versus a Bayesian model was evaluated using paired Results: The mean difference between the GENOMIC and Bayesian groups was -19.8900, with a 95% confidence interval ranging from -39.7944 to 0.0144. The combined Bayesian model, integrating clinical, lactate, and genomic data outperformed standalone genomic models. Mean score for the Bayesian model was 92.75 (standard deviation [SD] = 5.1881), significantly higher than the genomic model's 72.86 (SD = 15.4196) ( Conclusion: A Bayesian genomic-enhanced model offers a promising pathway for improving septic shock outcomes. Future studies with larger datasets and further model refinement are warranted to validate its potential and explore its broader application in critical care.
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