MétaCan
Menu
Back to cohort
Record W2159859679 · doi:10.1155/2013/384210

Interest of Monitoring Diaphragmatic Electrical Activity in the Pediatric Intensive Care Unit

2013· article· en· W2159859679 on OpenAlexaff
Laurence Ducharme‐Crevier, Geneviève Du Pont‐Thibodeau, Guillaume Émériaud

Bibliographic record

VenueCritical Care Research and Practice · 2013
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineDiaphragmatic breathingIntensive care medicineVentilation (architecture)Diaphragm (acoustics)Intensive care unitMechanical ventilationInternal medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

The monitoring of electrical activity of the diaphragm (EAdi) is a new minimally invasive bedside technology that was developed for the neurally adjusted ventilatory assist (NAVA) mode of ventilation. In addition to its role in NAVA ventilation, this technology provides the clinician with previously unavailable and essential information on diaphragm activity. In this paper, we review the clinical interests of EAdi in the pediatric intensive care setting. Firstly, the monitoring of EAdi allows the clinician to tailor the ventilatory settings on an individual basis, avoiding frequent overassistance leading potentially to diaphragmatic atrophy. Increased inspiratory EAdi levels can also suggest insufficient support, while a strong tonic activity may reflect the patient efforts to increase its lung volume. EAdi monitoring also allows detection of patient-ventilator asynchrony. It can play a role in evaluation of extubation readiness. Finally, EAdi monitoring provides the clinician with better understanding of the ventilatory capacity of patients with acute neuromuscular disease. Further studies are warranted to evaluate the clinical impact of these potential benefits.

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)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.247
GPT teacher head0.493
Teacher spread0.247 · 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 designQualitative
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

Citations33
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCritical Care Research and PracticeSame topicRespiratory Support and MechanismsFrench-language works237,207