ReviewJournal of critical care2014
From data patterns to mechanistic models in acute critical illness.
Review in Journal of critical care, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed, 35 citations in OpenAlex.
- Intertwined roles for GDF-15, HMGB1, and MIG/CXCL9 in Pediatric Acute Liver Failure.Frontiers in systems biology · 2024Article
- Clinical Phenotypes of Sepsis in a Cohort of Hospitalized Patients According to Infection Site.Critical care explorations · 2023Article
- Article
- System dynamics modeling for traumatic brain injury: Mini-review of applications.Frontiers in bioengineering and biotechnology · 2022Review
- A machine learning model to predict critical care outcomes in patient with chest pain visiting the emergency department.BMC emergency medicine · 2021Article
- Closed-Loop Control for Fluid Resuscitation: Recent Advances and Future Challenges.Frontiers in veterinary science · 2021Review
- Prognostic and predictive enrichment in sepsis.Nature reviews. Nephrology · 2020Review
- A computational analysis of dynamic, multi-organ inflammatory crosstalk induced by endotoxin in mice.PLoS computational biology · 2018Article
- The coming era of precision medicine for intensive care.Critical care (London, England) · 2017Review
- Perpetual and Virtual Patients for Cardiorespiratory Physiological Studies.Journal of pediatric intensive care · 2016Review
- Dynamic Profiling: Modeling the Dynamics of Inflammation and Predicting Outcomes in Traumatic Brain Injury Patients.Frontiers in pharmacology · 2016Article
- In vivo and systems biology studies implicate IL-18 as a central mediator in chronic pain.Journal of neuroimmunology · 2015Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
Abstract
The complexity of the physiologic and inflammatory response in acute critical illness has stymied the accurate diagnosis and development of therapies. The Society for Complex Acute Illness was formed a decade ago with the goal of leveraging multiple complex systems approaches to address this unmet need. Two main paths of development have characterized the society's approach: (i) data pattern analysis, either defining the diagnostic/prognostic utility of complexity metrics of physiologic signals or multivariate analyses of molecular and genetic data and (ii) mechanistic mathematical and computational modeling, all being performed with an explicit translational goal. Here, we summarize the progress to date on each of these approaches, along with pitfalls inherent in the use of each approach alone. We suggest that the next decade holds the potential to merge these approaches, connecting patient diagnosis to treatment via mechanism-based dynamical system modeling and feedback control and allowing extrapolation from physiologic signals to biomarkers to novel drug candidates. As a predicate example, we focus on the role of data-driven and mechanistic models in neuroscience and the impact that merging these modeling approaches can have on general anesthesia.
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.