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Record W2539163585 · doi:10.1097/ccm.0000000000002082

The Open Lung Approach Improves Pulmonary Vascular Mechanics in an Experimental Model of Acute Respiratory Distress Syndrome

2016· article· en· W2539163585 on OpenAlexaff
Arnoldo Santos, Luca Lucchetta, Manuel Ignacio Monge García, João Batista Borges, Gerardo Tusman, Göran Hedenstierna, Anders Larsson, Fernando Suárez-Sipmann

Bibliographic record

VenueCritical Care Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsMedicinePulmonary complianceRespiratory physiologyMechanical ventilationPositive end-expiratory pressureLungPulmonary arteryCardiologyCompliance (psychology)Respiratory distressAnesthesiaVascular resistanceRespiratory systemInternal medicineHemodynamics

Abstract

fetched live from OpenAlex

OBJECTIVE: To test whether positive end-expiratory pressure consistent with an open lung approach improves pulmonary vascular mechanics compared with higher or lower positive end-expiratory pressures in experimental acute respiratory distress syndrome. DESIGN: Experimental study. SETTING: Animal research laboratory. SUBJECTS: Ten pigs, 35 ± 5.2 kg. INTERVENTIONS: Acute respiratory distress syndrome was induced combining saline lung lavages with injurious mechanical ventilation. The positive end-expiratory pressure level resulting in highest compliance during a decremental positive end-expiratory pressure trial after lung recruitment was determined. Thereafter, three positive end-expiratory pressure levels were applied in a random order: hyperinflation, 6 cm H2O above; open lung approach, 2 cm H2O above; and collapse, 6 cm H2O below the highest compliance level. High fidelity pressure and flow sensors were placed at the main pulmonary artery for measuring pulmonary artery resistance (Z0), effective arterial elastance, compliance, and reflected pressure waves. MEASUREMENTS AND MAIN RESULTS: After inducing acute respiratory distress syndrome, Z0 and effective arterial elastance increased (from 218 ± 94 to 444 ± 115 dyn.s.cm and from 0.27 ± 0.14 to 0.62 ± 0.22 mm Hg/mL, respectively; p < 0.001), vascular compliance decreased (from 2.76 ± 0.86 to 1.48 ± 0.32 mL/mm Hg; p = 0.003), and reflected waves arrived earlier (0.23 ± 0.07 vs 0.14 ± 0.05, arbitrary unit; p = 0.002) compared with baseline. Comparing the three positive end-expiratory pressure levels, open lung approach resulted in the lowest: 1) Z0 (297 ± 83 vs 378 ± 79 dyn.s.cm, p = 0.033, and vs 450 ± 119 dyn.s.cm, p = 0.002); 2) effective arterial elastance (0.37 ± 0.08 vs 0.50 ± 0.15 mm Hg/mL, p = 0.04, and vs 0.61 ± 0.12 mm Hg/mL, p < 0.001), and 3) reflection coefficient (0.35 ± 0.17 vs 0.48 ± 0.10, p = 0.024, and vs 0.53 ± 0.19, p = 0.005), comparisons with hyperinflation and collapse, respectively. CONCLUSIONS: In this experimental setting, positive end-expiratory pressure consistent with the open lung approach resulted in the best pulmonary vascular mechanics compared with higher or lower positive end-expiratory pressure settings.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.344
Teacher spread0.303 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations18
Published2016
Admission routes1
Has abstractyes

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