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Record W4379093637 · doi:10.1159/000527708

Adsorption of Endotoxin and Mitigation of Sepsis

2023· review· en· W4379093637 on OpenAlexaff
John A. Kellum, Hisataka Shoji, Debra Foster, Paul M. Walker

Bibliographic record

VenueContributions to nephrology · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsIridian Spectral Technologies (Canada)
Fundersnot available
KeywordsHemoperfusionMedicineSepsisSeptic shockPolymyxinPolymyxin BResuscitationExtracorporealIntensive care medicinePharmacologyAdverse effectImmunologyAntibioticsInternal medicineMicrobiologyAnesthesiaBiology

Abstract

fetched live from OpenAlex

In the fields of sepsis and systemic inflammation, endotoxin might be the most studied molecule since the term was coined by Richard Pfeiffer in 1892. Paradoxically measuring endotoxin in humans and finding an effective treatment for endotoxemia have remained challenging. While advances have been made in understanding the mechanisms of how this simple molecule can trigger an intense immune cascade, there is an ever growing need to develop better treatments. Studies measuring endotoxin levels in patients with septic shock have consistently demonstrated that there is a dose-response relationship between endotoxin levels and adverse outcomes. A rapid assay to measure endotoxin activity has been available for more than a decade, but few studies have synergized the assay with a therapeutic. Polymyxin B hemoperfusion (PMX-HP) leverages a molecule with high affinity for endotoxin with a technique to eliminate exposure. Polymyxin is bound and immobilized to fibers within a cartridge and administered as an extracorporeal therapy via veno-venous hemoperfusion. Clinical evidence of its use is plentiful yet inconsistent in studies based on an outcome for mortality at 28 days. Herein, we describe targeted patient selection using the endotoxin activity assay and clinical phenotyping followed by adsorption of endotoxin using the PMX-HP for endotoxemic sepsis.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.022
GPT teacher head0.324
Teacher spread0.302 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2023
Admission routes1
Has abstractyes

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