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Record W2036283470 · doi:10.1097/aco.0b013e3283440185

Diaphragmatic dysfunction in mechanical ventilation

2011· review· en· W2036283470 on OpenAlexaff
Jack J. Haitsma

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2011
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineDiaphragm (acoustics)Mechanical ventilationDiaphragmatic breathingVentilation (architecture)Diaphragm muscleRespiratory failureWeaknessAnesthesiaSurgeryPathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: It has become clear from experimental data that prolonged mechanical ventilation can induce diaphragm dysfunction, also known as ventilator-induced diaphragm dysfunction. In this article we will discuss most recent understanding on ventilator-induced diaphragm dysfunction and data on diaphragm dysfunction in patients. RECENT FINDINGS: Over the last year several studies confirmed the existence of diaphragm dysfunction in patients. Known atrophy pathways are activated in patients undergoing prolonged conventional ventilation resulting in muscle proteolysis and a decrease in myofiber content. The loss of diaphragm force is time-dependent, but current data do not distinguish between the role played by other factors involved in diaphragm dysfunction. SUMMARY: Diaphragm dysfunction occurs in patients, especially when ventilated with controlled modes of ventilation that minimize diaphragm activity. Time on the ventilator seems to be one of the biggest risk factors resulting in difficulties in weaning patients and prolonging time on the ventilator. Future trials should investigate whether improved patient-ventilator synchrony can reduce ventilator-induced diaphragm dysfunction and decrease weaning failure.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.185
GPT teacher head0.408
Teacher spread0.223 · 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 designOther design
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

Citations18
Published2011
Admission routes1
Has abstractyes

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