Abstract:
:Trauma-induced critical illness is driven by acute inflammation, and elevated systemic interleukin-6 (IL-6) after trauma is a biomarker of adverse outcomes. We constructed a multicompartment, ordinary differential equation model that represents a virtual trauma patient. Individual-specific variants of this model reproduced both systemic inflammation and outcomes of 33 blunt trauma survivors, from which a cohort of 10,000 virtual trauma patients was generated. Model-predicted length of stay in the intensive care unit, degree of multiple organ dysfunction, and IL-6 area under the curve as a function of injury severity were in concordance with the results from a validation cohort of 147 blunt trauma patients. In a subcohort of 98 trauma patients, those with high-IL-6 single-nucleotide polymorphisms (SNPs) exhibited higher plasma IL-6 levels than those with low IL-6 SNPs, matching model predictions. Although IL-6 could drive mortality in individual virtual patients, simulated outcomes in the overall cohort were independent of the propensity to produce IL-6, a prediction verified in the 98-patient subcohort. In silico randomized clinical trials suggested a small survival benefit of IL-6 inhibition, little benefit of IL-1β inhibition, and worse survival after tumor necrosis factor-α inhibition. This study demonstrates the limitations of extrapolating from reductionist mechanisms to outcomes in individuals and populations and demonstrates the use of mechanistic simulation in complex diseases.
journal_name
Sci Transl Medjournal_title
Science translational medicineauthors
Brown D,Namas RA,Almahmoud K,Zaaqoq A,Sarkar J,Barclay DA,Yin J,Ghuma A,Abboud A,Constantine G,Nieman G,Zamora R,Chang SC,Billiar TR,Vodovotz Ydoi
10.1126/scitranslmed.aaa3636subject
Has Abstractpub_date
2015-04-29 00:00:00pages
285ra61issue
285eissn
1946-6234issn
1946-6242pii
7/285/285ra61journal_volume
7pub_type
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