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Modeling the Two-Hit Hypothesis for Evaluating Strategies to Prevent Organ Injury after Shock/Resuscitation

2003· review· en· W2396492514 on OpenAlexaff
Ori D. Rotstein

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2003
Typereview
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsUniversity Health NetworkToronto General Hospital
Fundersnot available
KeywordsResuscitationHypertonic salineMedicineIntensive care medicineShock (circulatory)PopulationOrgan dysfunctionSepsisAnesthesiaImmunologyInternal medicine

Abstract

fetched live from OpenAlex

The major cause of late death in patients sustaining major trauma relates to the development of progressive organ failure. Recent studies suggest that trauma victims are rendered susceptible to the development of organ failure because antecedent shock/resuscitation renders them susceptible to an exaggerated immune response to late inflammatory stimuli, the so-called two-hit hypothesis. In this article, the rationale underlying the use of a "two-hit" model in trauma research is reviewed and a specific example is cited. Importantly, these models permit investigation aimed at understanding the cellular and molecular mechanisms of disease after shock/resuscitation. Interventions such as antioxidant therapy and hypertonic saline resuscitation have a rational basis for use and have been shown to be effective in a rodent two-hit lung injury model. These studies suggest potential use in the critically ill trauma patient population.

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.

How this classification was reachedexpand

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.420
Teacher spread0.335 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations108
Published2003
Admission routes1
Has abstractyes

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