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Record W2913730011 · doi:10.1002/ejhf.1379

Lung Ultrasound Integrated with Clinical Assessment for the Diagnosis of Acute Decompensated Heart Failure in the Emergency Department: A Randomized Controlled Trial

2019· article· en· W2913730011 on OpenAlex

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

VenueEuropean Journal of Heart Failure · 2019
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineEmergency departmentAcute decompensated heart failureHeart failureRandomized controlled trialIntensive care medicineLung ultrasoundEmergency medicineUltrasoundCardiologyLungInternal medicineRadiology

Abstract

fetched live from OpenAlex

AIMS: Although acute decompensated heart failure (ADHF) is a common cause of dyspnoea, its diagnosis still represents a challenge. Lung ultrasound (LUS) is an emerging point-of-care diagnostic tool, but its diagnostic performance for ADHF has not been evaluated in randomized studies. We evaluated, in patients with acute dyspnoea, accuracy and clinical usefulness of combining LUS with clinical assessment compared to the use of chest radiography (CXR) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in conjunction with clinical evaluation. METHODS AND RESULTS: This was a randomized trial conducted in two emergency departments. After initial clinical evaluation, patients with acute dyspnoea were classified by the treating physician according to presumptive aetiology (ADHF or non-ADHF). Patients were subsequently randomized to continue with either LUS or CXR/NT-proBNP. A new diagnosis, integrating the results of both initial assessment and the newly obtained findings, was then recorded. Diagnostic accuracy and clinical usefulness of LUS and CXR/NT-proBNP approaches were calculated. A total of 518 patients were randomized. Addition of LUS had higher accuracy [area under the receiver operating characteristic curve (AUC) 0.95] than clinical evaluation alone (AUC 0.88) in identifying ADHF (P < 0.01). In contrast, use of CXR/NT-proBNP did not significantly increase the accuracy of clinical evaluation alone (AUC 0.87 and 0.85, respectively; P > 0.05). The diagnostic accuracy of the LUS-integrated approach was higher then that of the CXR/Nt-proBNP-integrated approach (AUC 0.95 vs. 0.87, p < 0.01). Combining LUS with the clinical evaluation reduced diagnostic errors by 7.98 cases/100 patients, as compared to 2.42 cases/100 patients in the CXR/Nt-proBNP group. CONCLUSION: Integration of LUS with clinical assessment for the diagnosis of ADHF in the emergency department seems to be more accurate than the current diagnostic approach based on CXR and NT-proBNP.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized trialhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.363
Teacher spread0.339 · 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