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Record W1525114205 · doi:10.1111/nyas.12444

Barriers to the effective treatment of sepsis: antimicrobial agents, sepsis definitions, and host‐directed therapies

2014· review· en· W1525114205 on OpenAlexafffund
Ngan H. Lyle, Olga M. Pena, John H. Boyd, Robert E. W. Hancock

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2014
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchAssociation of Medical Microbiology and Infectious Disease Canada
KeywordsSepsisHost responseIntensive care medicineAntimicrobialMedicineHost (biology)Clinical trialImmune systemImmunologyDiseaseBiologyMicrobiologyInternal medicine

Abstract

fetched live from OpenAlex

Sepsis is a complex clinical syndrome involving both infection and a deleterious host immune response. Antimicrobial agents are key elements of sepsis treatment, yet despite great strides in antimicrobial development in the last decades, sepsis continues to be associated with unacceptably high mortality (~30%). This is the result, on one hand, of the rise of antimicrobial resistant organisms and, on the other hand, of the dearth of effective host-directed immune therapies. A major obstacle to the development of good host-directed therapies is the lack of understanding of the host immune response. The problem is exacerbated by poor nonspecific clinical definitions of disease. Poor definitions have had a profound impact on sepsis research, from epidemiologic studies to the failed clinical trials of host-directed therapies. Therefore, better definitions must be developed to enable advancement in the field.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.220
GPT teacher head0.415
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations60
Published2014
Admission routes2
Has abstractyes

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