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Record W3008446876 · doi:10.1097/aln.0000000000003191

Usefulness of Parasternal Intercostal Muscle Ultrasound during Weaning from Mechanical Ventilation

2020· article· en· W3008446876 on OpenAlexaff
Martin Dres, Bruno‐Pierre Dubé, Ewan C. Goligher, Stefannie Vorona, Suela Demiri, Élise Morawiec, Julien Mayaux, Laurent Brochard, Thomas Similowski, Alexandre Demoule

Bibliographic record

VenueAnesthesiology · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsParasternal lineMedicineDiaphragm (acoustics)CardiologyIntercostal muscleMechanical ventilationSpontaneous breathing trialInternal medicineAnesthesiaRespiratory system

Abstract

fetched live from OpenAlex

BACKGROUND: The assessment of diaphragm function with diaphragm ultrasound seems to bring important clinical information to describe diaphragm work and weakness. When the diaphragm is weak, extradiaphragmatic muscles may play an important role, but whether ultrasound can also assess their activity and function is unknown. This study aimed to (1) evaluate the feasibility of measuring the thickening of the parasternal intercostal and investigate the responsiveness of this muscle to assisted ventilation; and (2) evaluate whether a combined evaluation of the parasternal and the diaphragm could predict failure of a spontaneous breathing trial. METHODS: First, an exploratory evaluation of the parasternal in 23 healthy subjects. Second, the responsiveness of parasternal to several pressure support levels were studied in 16 patients. Last, parasternal activity was compared in presence or absence of diaphragm dysfunction (assessed by magnetic stimulation of the phrenic nerves and ultrasound) and in case of success/failure of a spontaneous breathing trial in 54 patients. RESULTS: The parasternal was easily accessible in all patients. The interobserver reproducibility was good (intraclass correlation coefficient, 0.77 (95% CI, 0.53 to 0.89). There was a progressive decrease in parasternal muscle thickening fraction with increasing levels of pressure support (Spearman ρ = -0.61 [95% CI, -0.74 to -0.44]; P < 0.0001) and an inverse correlation between parasternal muscle thickening fraction and the pressure generating capacity of the diaphragm (Spearman ρ = -0.79 [95% CI, -0.87 to -0.66]; P < 0.0001). The parasternal muscle thickening fraction was higher in patients with diaphragm dysfunction: 17% (10 to 25) versus 5% (3 to 8), P < 0.0001. The pressure generating capacity of the diaphragm, the diaphragm thickening fraction and the parasternal thickening fraction similarly predicted failure or the spontaneous breathing trial. CONCLUSIONS: Ultrasound assessment of the parasternal intercostal muscle is feasible in the intensive care unit and provides novel information regarding the respiratory capacity load balance.

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)0.007
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.257
Teacher spread0.216 · 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

Citations146
Published2020
Admission routes1
Has abstractyes

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