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Record W2754147990 · doi:10.1164/rccm.201703-0536oc

Mechanical Ventilation–induced Diaphragm Atrophy Strongly Impacts Clinical Outcomes

2017· article· en· W2754147990 on OpenAlexaff
Ewan C. Goligher, Martin Dres, Eddy Fan, Gordon D. Rubenfeld, Damon C. Scales, Margaret S. Herridge, Stefannie Vorona, Michael C. Sklar, Nuttapol Rittayamai, Ashley Lanys, Alistair Murray, Deborah Brace, Cristian Urrea, W. Darlene Reid, George Tomlinson, Arthur S. Slutsky, Brian P. Kavanagh, Laurent Brochard, Niall D. Ferguson

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoUniversity Health NetworkToronto General HospitalSt. Michael's HospitalSunnybrook Health Science CentreMount Sinai Hospital
Fundersnot available
KeywordsMedicineMechanical ventilationInterquartile rangeVentilation (architecture)Spontaneous breathing trialOdds ratioDiaphragm (acoustics)AnesthesiaConfidence intervalHazard ratioInternal medicine

Abstract

fetched live from OpenAlex

RATIONALE: Diaphragm dysfunction worsens outcomes in mechanically ventilated patients, but the clinical impact of potentially preventable changes in diaphragm structure and function caused by mechanical ventilation is unknown. OBJECTIVES: To determine whether diaphragm atrophy developing during mechanical ventilation leads to prolonged ventilation. METHODS: Diaphragm thickness was measured daily by ultrasound in adults requiring invasive mechanical ventilation; inspiratory effort was assessed by thickening fraction. The primary outcome was time to liberation from ventilation. Secondary outcomes included complications (reintubation, tracheostomy, prolonged ventilation, or death). Associations were adjusted for age, severity of illness, sepsis, sedation, neuromuscular blockade, and comorbidity. MEASUREMENTS AND MAIN RESULTS: Of 211 patients enrolled, 191 had two or more diaphragm thickness measurements. Thickness decreased more than 10% in 78 patients (41%) by median Day 4 (interquartile range, 3-5). Development of decreased thickness was associated with a lower daily probability of liberation from ventilation (adjusted hazard ratio, 0.69; 95% confidence interval [CI], 0.54-0.87; per 10% decrease), prolonged ICU admission (adjusted duration ratio, 1.71; 95% CI, 1.29-2.27), and a higher risk of complications (adjusted odds ratio, 3.00; 95% CI, 1.34-6.72). Development of increased thickness (n = 47; 24%) also predicted prolonged ventilation (adjusted duration ratio, 1.38; 95% CI, 1.00-1.90). Decreasing thickness was related to abnormally low inspiratory effort; increasing thickness was related to excessive effort. Patients with thickening fraction between 15% and 30% (similar to breathing at rest) during the first 3 days had the shortest duration of ventilation. CONCLUSIONS: Diaphragm atrophy developing during mechanical ventilation strongly impacts clinical outcomes. Targeting an inspiratory effort level similar to that of healthy subjects at rest might accelerate liberation from ventilation.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.061
GPT teacher head0.411
Teacher spread0.349 · 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 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

Citations832
Published2017
Admission routes1
Has abstractyes

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