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Record W2552432157 · doi:10.1097/mcc.0000000000000377

Should we use driving pressure to set tidal volume?

2016· review· en· W2552432157 on OpenAlexaff
Domenico Luca Grieco, Lü Chen, Martin Dres, Laurent Brochard

Bibliographic record

VenueCurrent Opinion in Critical Care · 2016
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineTidal volumeIntensive care medicineProne positionMechanical ventilationVentilation (architecture)Acute respiratory distressAnesthesiaLungRespiratory systemInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Ventilator-induced lung injury (VILI) can occur despite use of tidal volume (VT) limited to 6 ml/kg of predicted body weight, especially in patients with a smaller aerated compartment (i.e. the baby lung) in which, indeed, tidal ventilation takes place. Because respiratory system static compliance (CRS) is mostly affected by the volume of the baby lung, the ratio VT/CRS (i.e. the driving pressure, ΔP) may potentially help tailoring interventions on VT setting. RECENT FINDINGS: Driving pressure is the ventilatory variable most strongly associated with changes in survival and has been shown to be the key mediator of the effects of mechanical ventilation on outcome in the acute respiratory distress syndrome. Observational data suggest an increased risk of death for patients with ΔP more than 14 cmH2O, but a well tolerated threshold for this parameter has yet to be identified. Prone position along with simple ventilatory adjustments to facilitate CO2 clearance may help reduce ΔP in isocapnic conditions. The safety and feasibility of low-flow extracorporeal CO2 removal in enhancing further reduction in VT and ΔP are currently being investigated. SUMMARY: Driving pressure is a bedside available parameter that may help identify patients prone to develop VILI and at increased risk of death. No study had prospectively evaluated whether interventions on ΔP may provide a relevant clinical benefit, but it appears physiologically sound to try titrating VT to minimize ΔP, especially when it is higher than 14 cmH2O and when it has minimal costs in terms of CO2 clearance.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.892
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.417
GPT teacher head0.522
Teacher spread0.105 · 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

Citations54
Published2016
Admission routes1
Has abstractyes

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