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Record W1973370014 · doi:10.1164/rccm.200507-1178oc

Ischemia and Reperfusion Increases Susceptibility to Ventilator-induced Lung Injury in Rats

2006· article· en· W1973370014 on OpenAlexaff
Ettore Crimi, Haibo Zhang, Robin N. N. Han, Lorenzo Del Sorbo, V. Marco Ranieri, Arthur S. Slutsky

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineLungTidal volumeARDSMechanical ventilationAnesthesiaLung volumesKidneyLactate dehydrogenaseInternal medicineRespiratory systemBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: Hemorrhagic shock followed by resuscitation (HSR) commonly triggers an inflammatory response that leads to acute respiratory distress syndrome. HYPOTHESIS: HSR exacerbates mechanical stress-induced lung injury by rendering the lung more susceptible to ventilator-induced lung injury. METHODS: Rats were subjected to HSR, and were randomized into an HSR + high tidal volume and zero positive end-expiratory pressure (PEEP) or a HSR + low tidal volume with 5 cm H(2)O PEEP. A sham-operated rat + high tidal volume and zero PEEP served as a control. RESULTS: HSR increased susceptibility to ventilator-induced lung injury as evidenced by an increase in lung elastance and the wet/dry ratio and a reduction in Pa(O(2)) as compared with the other groups. The lung injury observed in the HSR + high tidal volume group was associated with a higher level of interleukin 6 in the lung and blood, increased epithelial cell apoptosis in the kidney and small intestine villi, and a tendency toward high levels of alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, and creatinine in plasma. CONCLUSIONS: HSR priming renders the lung and kidney more susceptible to mechanical ventilation-induced organ injury.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.014
GPT teacher head0.320
Teacher spread0.307 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations39
Published2006
Admission routes1
Has abstractyes

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