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Record W2935899654 · doi:10.1186/s13613-019-0511-1

Narrative review: clinical assessment of peripheral tissue perfusion in septic shock

2019· review· en· W2935899654 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

VenueAnnals of Intensive Care · 2019
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCapillary refillSeptic shockMedicineResuscitationPerfusionSepsisHemodynamicsAnesthesiologyShock (circulatory)Intensive careSurviving Sepsis CampaignPeripheralIntensive care medicineCentral venous pressureCardiologyBlood pressureAnesthesiaInternal medicineHeart rate

Abstract

fetched live from OpenAlex

Sepsis is one of the main reasons for intensive care unit admission and is responsible for high morbidity and mortality. The usual hemodynamic targets for resuscitation of patients with septic shock use macro-hemodynamic parameters (hearth rate, mean arterial pressure, central venous pressure). However, persistent alterations of microcirculatory blood flow despite restoration of macro-hemodynamic parameters can lead to organ failure. This dissociation between macro- and microcirculatory compartments brings a need to assess end organs tissue perfusion in patients with septic shock. Traditional markers of tissue perfusion may not be readily available (lactate) or may take time to assess (urine output). The skin, an easily accessible organ, allows clinicians to quickly evaluate the peripheral tissue perfusion with noninvasive bedside parameters such as the skin temperatures gradient, the capillary refill time, the extent of mottling and the peripheral perfusion index.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.698
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.382
GPT teacher head0.580
Teacher spread0.197 · 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