ReviewCritical care medicine2013
In silico modeling: methods and applications to trauma and sepsis.
Review in Critical care medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.
- Interleukin-17 as a spatiotemporal bridge from acute to chronic inflammation: Novel insights from computational modeling.WIREs mechanisms of diseasePooled it
- Digital twin mathematical models suggest individualized hemorrhagic shock resuscitation strategies.Communications medicine · 2024Article
- What's next for computational systems biology?Frontiers in systems biology · 2023Review
- The critical role of neutrophil-endothelial cell interactions in sepsis: new synergistic approaches employing organ-on-chip, omics, immune cell phenotyping andFrontiers in cellular and infection microbiology · 2023Review
- The Use of Multiplexing to Identify Cytokine and Chemokine Networks in the Immune-Inflammatory Response to Trauma.Antioxidants & redox signaling · 2021Review
- Article
- An Early Stage Researcher's Primer on Systems Medicine Terminology.Network and systems medicine · 2021Review
- SARS-CoV-2/COVID-19: Evolving Reality, Global Response, Knowledge Gaps, and Opportunities.Shock (Augusta, Ga.) · 2020Review
- Computational Analysis Supports IL-17A as a Central Driver of Neutrophil Extracellular Trap-Mediated Injury in Liver Ischemia Reperfusion.Journal of immunology (Baltimore, Md. : 1950) · 2019Article
- A computational analysis of dynamic, multi-organ inflammatory crosstalk induced by endotoxin in mice.PLoS computational biology · 2018Article
- Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology.Immunological reviews · 2018Review
- Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.Biomedical engineering online · 2018Review
- Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model.Journal of theoretical biology · 2017Article
- The role of NIGMS P50 sponsored team science in our understanding of multiple organ failure.The journal of trauma and acute care surgery · 2017Article
- Data-Driven Modeling for Precision Medicine in Pediatric Acute Liver Failure.Molecular medicine (Cambridge, Mass.) · 2017Article
- Systems Medicine-Complexity Within, Simplicity Without.Journal of healthcare informatics research · 2017Article
- Individual-specific principal component analysis of circulating inflammatory mediators predicts early organ dysfunction in trauma patients.Journal of critical care · 2016Article
- From static to dynamic: a sepsis-specific dynamic model from clinical criteria in polytrauma patients.Annals of translational medicine · 2016Article
- Computational Analysis Supports an Early, Type 17 Cell-Associated Divergence of Blunt Trauma Survival and Mortality.Critical care medicine · 2016Article
- Machine Perfusion of Porcine Livers with Oxygen-Carrying Solution Results in Reprogramming of Dynamic Inflammation Networks.Frontiers in pharmacology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesTo familiarize clinicians with advances in computational disease modeling applied to trauma and sepsis. DATA SOURCES: PubMed search and review of relevant medical literature. SUMMARY: Definitions, key methods, and applications of computational modeling to trauma and sepsis are reviewed.
conclusionsComputational modeling of inflammation and organ dysfunction at the cellular, organ, whole-organism, and population levels has suggested a positive feedback cycle of inflammation → damage → inflammation that manifests via organ-specific inflammatory switching networks. This structure may manifest as multicompartment "tipping points" that drive multiple organ dysfunction. This process may be amenable to rational inflammation reprogramming.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.