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Record W2109114042 · doi:10.1186/cc11867

Clinical review: Acute respiratory distress syndrome - clinical ventilator management and adjunct therapy

2013· review· en· W2109114042 on OpenAlexafffund
Jonathan A. Silversides, Niall D. Ferguson

Bibliographic record

VenueCritical Care · 2013
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsMount Sinai HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineARDSIntensive care medicinePlateau pressureMechanical ventilationContinuous positive airway pressureProne positionVentilation (architecture)LungAnesthesiaInternal medicineObstructive sleep apnea

Abstract

fetched live from OpenAlex

Acute respiratory distress syndrome (ARDS) is a potentially devastating form of acute inflammatory lung injury with a high short-term mortality rate and significant long-term consequences among survivors. Supportive care, principally with mechanical ventilation, remains the cornerstone of therapy - although the goals of this support have changed in recent years - from maintaining normal physiological parameters to avoiding ventilator-induced lung injury while providing adequate gas exchange. In this article we discuss the current evidence base for ventilatory support and adjunctive therapies in patients with ARDS. Key components of such a strategy include avoiding lung overdistension by limiting tidal volumes and airway pressures, and the use of positive end-expiratory pressure with or without lung recruitment manoeuvres in patients with severe ARDS. Adjunctive therapies discussed include pharmacologic techniques (for example, vasodilators, diuretics, neuromuscular blockade) and nonpharmacologic techniques (for example, prone position, alternative modes of ventilation).

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)0.001
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.003

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 head0.189
GPT teacher head0.499
Teacher spread0.309 · 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

Citations61
Published2013
Admission routes2
Has abstractyes

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