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Record W2125163509 · doi:10.1164/ajrccm.162.1.9903120

Biologically Variable or Naturally Noisy Mechanical Ventilation Recruits Atelectatic Lung

2000· article· en· W2125163509 on OpenAlexaff
W. Alan C. Mutch, Stefan Harms, M. Ruth Graham, Stephen Kowalski, Linda Girling, Gerald R. Lefevre

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAtelectasisMedicineLungTidal volumeMechanical ventilationVentilation (architecture)Lung volumesRespiratory systemAnesthesiaPulmonary complianceInternal medicinePhysicsThermodynamics

Abstract

fetched live from OpenAlex

Biologically variable mechanical ventilation (Vbv)-using a computer-controller to mimic the normal variability in spontaneous breathing-improves gas exchange in a model of severe lung injury (Lefevre, G. R., S. E. Kowalski, L. G. Girling, D. B. Thiessen, W. A. C. Mutch. Am. J. Respir. Crit. Care Med. 1996;154:1567-1572). Improved oxygenation with Vbv, in the face of alveolar collapse, is thought to be due to net volume recruitment secondary to the variability or increased noise in the peak inspiratory airway pressures (Ppaw). Biologically variable noise can be modeled as an inverse power law frequency distribution (y approximately 1/f(a)) (West, B. J., M. Shlesinger. Am. Sci. 1990;78:40-45). In a porcine model of atelectasis-right lung collapse with one-lung ventilation-we studied if Vbv (n = 7) better reinflates the collapsed lung compared with conventional monotonously regular control mode ventilation (Vc; n = 7) over a 5-h period. We also investigated the influence of sigh breaths with Vc (Vs; n = 8) with this model. Reinflation of the collapsed lung was significantly enhanced with Vbv-greater Pa(O(2)) (502 +/- 40 mm Hg with Vbv versus 381 +/- 40 mm Hg with Vc at 5 h; and 309 +/- 79 mm Hg with Vs; mean +/- SD), lower Pa(CO(2)) (35 +/- 4 mm Hg versus 48 +/- 8 mm Hg and 50 +/- 8 mm Hg), lower shunt fraction (9.7 +/- 2.7% versus 14.6 +/- 2.0% and 22.9 +/- 6.0%), and higher respiratory system compliance (Crs) (1.15 +/- 0.15 ml/cm H(2)O/kg versus 0.79 +/- 0.19 ml/cm H(2)O/kg and 0.77 +/- 0.13 ml/cm H(2)O/kg)-at lower mean Ppaw (15.7 +/- 1.4 cm H(2)O versus 18.8 +/- 2.3 cm H(2)O and 18.9 +/- 2.8 cm H(2)O). Vbv resulted in an 11% increase in measured tidal volume (VT(m)) over that seen with Vc by 5 h (14.7 +/- 1.2 ml/kg versus 13. 2 ml/kg). The respiratory rate variability programmed for Vbv demonstrated an inverse power law frequency distribution ( y approximately 1/f(a)) with a = 1.6 +/- 0.3. These findings provide strong support for the theoretical model of noisy end-inspiratory pressure better recruiting atelectatic lung. Our results suggest that using natural biologically variable noise has enhanced the performance of a mechanical ventilator in control mode.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.326
Teacher spread0.308 · 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 designOther design
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

Citations124
Published2000
Admission routes1
Has abstractyes

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