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Effects of PEEP levels following repeated recruitment maneuvers on ventilator‐induced lung injury

2008· article· en· W1902245422 on OpenAlexafffund
S.‐C. KO, H. ZHANG, Jack J. Haitsma, Kuo-Chen Cheng, Chien‐Feng Li, Arthur S. Slutsky

Bibliographic record

VenueActa Anaesthesiologica Scandinavica · 2008
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicinePositive end-expiratory pressureOxygenationAnesthesiaLungPulmonary complianceMechanical ventilationTidal volumeRespiratory physiologyVentilation (architecture)Respiratory systemInternal medicinePhysics

Abstract

fetched live from OpenAlex

BACKGROUND: Different levels of positive end-expiratory pressure (PEEP) with and without a recruitment maneuver (RM) may have a significant impact on ventilator-induced lung injury but this issue has not been well addressed. METHODS: Anesthetized rats received hydrochloric acid (HCl, pH 1.5) aspiration, followed by mechanical ventilation with a tidal volume of 6 ml/kg. The animals were randomized into four groups of 10 each: (1) high PEEP at 6 cm H(2)O with an RM by applying peak airway pressure at 30 cm H(2)O for 10 s every 15 min; (2) low PEEP at 2 cm H(2)O with RM; (3) high PEEP alone; and (4) low PEEP alone. RESULTS: The mean arterial pressure and the amounts of fluid infused were similar in the four groups. Application of the higher PEEP improved oxygenation compared with the lower PEEP groups (P<0.05). The lung compliance was better reserved, and the systemic cytokine responses and lung wet to dry ratio were lower in the high PEEP than in the low PEEP group for a given RM (P<0.05). CONCLUSIONS: The use of a combination of periodic RM and the higher PEEP had an additive effect in improving oxygenation and pulmonary mechanics and attenuation of inflammation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.308
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.070
GPT teacher head0.318
Teacher spread0.248 · 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 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

Citations32
Published2008
Admission routes2
Has abstractyes

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