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Record W3157030168 · doi:10.1097/mcc.0000000000000827

Driving pressure monitoring during acute respiratory failure in 2020

2021· review· en· W3157030168 on OpenAlexaff
Lü Chen, Annemijn H. Jonkman, Sérgio M. Pereira, Cong Lü, Laurent Brochard

Bibliographic record

VenueCurrent Opinion in Critical Care · 2021
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsARDSMedicineMechanical ventilationAcute respiratory distressAcute respiratory failureIntensive care medicineVentilation (architecture)Pressure support ventilationCoronavirus disease 2019 (COVID-19)Respiratory failureEmergency medicineAnesthesiaLungDiseaseInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Assess the most recent studies using driving pressure (DP) as a monitoring technique under mechanical ventilation and describe the technical challenges associated with its measurement. RECENT FINDINGS: DP is consistently associated with survival in acute respiratory failure and acute respiratory distress syndrome (ARDS) and can detect patients at higher risk of ventilator-induced lung injury. Its measurement can be challenged by leaks and ventilator dyssynchrony, but is also feasible under pressure support ventilation. Interestingly, an aggregated summary of published results suggests that its level is on average slightly lower in patients with coronavirus disease-19 induced ARDS than in classical ARDS. SUMMARY: The DP is easy to obtain and should be incorporated as a minimal monitoring technique under mechanical 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)0.004
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.190
GPT teacher head0.485
Teacher spread0.295 · 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

Citations21
Published2021
Admission routes1
Has abstractyes

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