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Record W4402555360 · doi:10.1002/jcu.23792

Extravascular lung water assessment by lung ultrasound in infants following pediatric cardiac surgery

2024· article· en· W4402555360 on OpenAlex
Evyatar Hubara, Stéphanie Reynaud, Ashley Gionfriddo, Kyle Runeckles, Brigitte Mueller, Alejandro A. Floh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Ultrasound · 2024
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsTed Rogers Centre for Heart ResearchUniversity of TorontoUniversity Health NetworkSickKids FoundationDalhousie UniversityHospital for Sick Children
Fundersnot available
KeywordsMedicineLungLung ultrasoundUltrasoundCardiac surgeryRadiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Lung edema is a significant factor in prolonged mechanical ventilation and extubation failure after cardiac surgery. This study assessed the predictive capability of point-of-care Lung Ultrasound (LUS) for the duration of mechanical ventilation and extubation failure in infants following cardiac procedures. METHODS: We conducted a prospective observational trial on infants under 1 year, excluding those with pre-existing conditions or requiring extracorporeal membrane oxygenation. LUS was performed upon intensive care unit (ICU) admission and prior to extubation attempts. B-line density was scored by two independent observers. The primary outcomes included the duration of mechanical ventilation and extubation failure, the latter defined as the need for reintubation or non-invasive ventilation within 48 h post-extubation. RESULTS: The study included 42 infants, with findings indicating no correlation between initial LUS scores and extubation timing. Extubation failure occurred in 21% of the patients, with higher LUS scores observed in these cases (p = 0.046). However, interobserver variability was high, impacting the reliability of LUS scores to predict extubation readiness. CONCLUSIONS: LUS was ineffective in determining the length of postoperative ventilation and extubation readiness, highlighting the need for further research and enhanced training in LUS interpretation.

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.

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)0.013
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.003
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 head0.033
GPT teacher head0.407
Teacher spread0.374 · 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