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Record W2944215115 · doi:10.1055/s-0039-1685191

Extracorporeal Strategies in Acute Respiratory Distress Syndrome

2019· review· en· W2944215115 on OpenAlexafffund
Yiorgos Alexandros Cavayas, Aneesh Thakore, Eddy Fan

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2019
Typereview
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineAcute respiratory distressExtracorporealIntensive care medicineRespiratory distressRespiratory diseaseExtracorporeal membrane oxygenationSurgeryInternal medicineLung

Abstract

fetched live from OpenAlex

Abstract Despite the breadth of life-sustaining interventions available, mortality in patients with acute respiratory distress syndrome (ARDS) remains high. A greater appreciation of the potential iatrogenic injury associated with the use of mechanical ventilation has led clinicians and researchers to seek alternatives. Extracorporeal life support (ECLS) may be used to rescue patients with severely impaired gas exchange and provide time for injured lungs to recover while treating the underlying disease. In patients with ARDS, venovenous (VV) ECLS is commonly used, where venous blood is drained into a circuit that passes through a membrane lung, which provides gas exchange, and then returned to the venous system. VV-ECLS can be configured as a system that uses higher blood flows with extracorporeal membrane oxygenation (VV-ECMO) or as one that uses lower blood flows for extracorporeal carbon dioxide removal (VV-ECCO2R). Recent studies support the use of VV-ECMO in patients with severe ARDS who present with refractory gas exchange despite the use of lung-protective mechanical ventilation, positive end-expiratory pressure optimization, neuromuscular blockade, and prone positioning. The optimal management of patients during ECLS (i.e., anticoagulation, transfusions, mechanical ventilation) and the role of ECCO2R in the management of ARDS remain to be determined.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.922
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.050
GPT teacher head0.348
Teacher spread0.299 · 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 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

Citations4
Published2019
Admission routes2
Has abstractyes

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