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Multiple organ dysfunction syndrome: Exploring the paradigm of complex nonlinear systems

2000· review· en· W2028553295 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Care Medicine · 2000
Typereview
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsNonlinear systemMedicineSystemic inflammatory response syndromeIntensive care medicineComputer scienceComplex systemOrgan dysfunctionRelevance (law)SepsisInterdependenceMultiple organ dysfunction syndromeData scienceMachine learningRisk analysis (engineering)Artificial intelligenceImmunology

Abstract

fetched live from OpenAlex

OBJECTIVES: The objectives of this article are to introduce and explore a novel paradigm based on complex nonlinear systems, and to evaluate its application to critical care research regarding the systemic host response and multiple organ dysfunction syndrome (MODS). DATA SOURCES: Published original work, review articles, scientific abstracts and books, as well as our personal files. STUDY SELECTION: Studies were selected for their relevance to the applications of nonlinear complex systems, to critical care medicine, and to the concepts presented. DATA EXTRACTION: We extracted all applicable data. DATA SYNTHESIS: Following a brief review of MODS, an introduction to complex nonlinear systems is presented, including clear concepts, definitions, and properties. By examining the multiple, nonlinear, interrelated, and variable interactions between the metabolic, neural, endocrine, immune, and inflammatory systems; data regarding interconnected antibody networks; and the redundant, nonlinear, interdependent nature of the inflammatory response, we present the hypothesis that the systemic host response to trauma, shock, or sepsis must be evaluated as a complex nonlinear system. This model provides a new explanation for the failure of trials using various antimediator therapies in the treatment of patients with sepsis and MODS. Understanding the host response as a complex nonlinear system offers innovative means of studying critical care patients, specifically by suggesting a greater focus on systemic properties. We hypothesize that analysis of variability and connectivity of individual variables offer a novel means of evaluating and differentiating the systemic properties of a complex nonlinear system. Current applications of evaluating variability and connectivity are discussed, and insights regarding future research are offered. CONCLUSION: The paradigm offered by the study of complex nonlinear systems suggests new insights to pursue research to evaluate, monitor, and treat patients with MODS.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.137
GPT teacher head0.355
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it