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Record W2735761750 · doi:10.5152/tjar.2017.93753

Changing Definitions of Sepsis

2017· review· en· W2735761750 on OpenAlexaff
Fethi Gül, Mustafa Kemal Arslantaş, İsmail Cinel, Anand Kumar

Bibliographic record

VenueTürk anestezi ve reanimasyon dergisi · 2017
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSepsisIntensive care medicineSeptic shockOrgan dysfunctionMedicineSystemic inflammatory response syndromeSOFA scoreResuscitationMultiple organ dysfunction syndromeDiseaseHost responseImmunologyInternal medicineEmergency medicineImmune system

Abstract

fetched live from OpenAlex

Sepsis is one of the main causes of morbidity and mortality in critically ill patients despite the use of modern antibiotics and resuscitation therapies. Outcomes in sepsis have improved overall, probably because of an enhanced focus on early diagnosis and other improvements in supportive care, but mortality rates still remain unacceptably high. The diagnosis and definition of sepsis is a critical problem due to the heterogeneity of this disease process. Although it is apparent that much more needs to be done to advance our understanding, sepsis and related terms remain difficult to define. A 1991 consensus conference developed initial definitions that systemic inflammatory response syndrome (SIRS) to infection would be called sepsis. Definitions of sepsis and septic shock were revised in 2001 to incorporate the threshold values for organ damage. In early 2016, the new definitions of sepsis and septic shock have changed dramatically. Sepsis is now defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. The consensus document describes organ dysfunction as an acute increase in total Sequential Organ Failure Assessment (SOFA) score two points consequently to the infection. A significant change in the new definitions is the elimination of any mention of SIRS. The Sepsis-3 Task Force also introduced a new bedside index, called the qSOFA, to identify outside of critical care units patients with suspected infection who are likely to develop sepsis. Recently updated the consensus definitions improved specificity compared with the previous descriptions.

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)0.007
metaresearch head score (Gemma)0.015
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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.006
Science and technology studies0.0010.006
Scholarly communication0.0030.007
Open science0.0030.003
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0030.002

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 head0.444
GPT teacher head0.453
Teacher spread0.009 · 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

Citations210
Published2017
Admission routes1
Has abstractyes

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