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Comparison of a basic lung scanning protocol against formally reported chest x‐ray in the diagnosis of pulmonary oedema

2013· article· en· W2564340285 on OpenAlexaff
Kylie Baker, Geoffrey Mitchell, Angus Thompson, Geoffrey Stieler

Bibliographic record

VenueAustralasian Journal of Ultrasound in Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsSt. Paul's Hospital
FundersSpoedeisende Geneeskunde Onderzoeksfonds
KeywordsMedicineEmergency departmentRadiologyLungDiagnostic accuracyInterimPulmonary oedemaPresentation (obstetrics)Internal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction : Brief lung scan protocols have been recommended as a useful adjunct to identify pulmonary oedema in the breathless elderly patient. Some papers quote diagnostic accuracies above that of chest x‐ray. Method : We recruited a prospective convenience sample of patients over sixty years of age reporting any breathlessness on presentation to the emergency department. Those who received both bedside lung scan and chest x‐ray later had their case notes audited by an expert cardiologist for the cause of their breathlessness at presentation. Admission diagnosis was also extracted. Results : 204 comparative data sets were collected. Compared with cardiologist chart review, delayed expert radiology report had a diagnostic accuracy of 92.2% (95%CI 87.6 to 95.1). Bedside interpretation of lung scan protocol had a diagnostic accuracy of 85.3% (95%CI 79.8 to 89.5). The difference of 6.9% between the two accuracy measures was significant (95%CI 0.69 to 13.1). Admission diagnosis accuracy, which encompasses inexpert x‐ray interpretation was 70.2%(95%CI 62.9 to 76.6), significantly less than either lung scan or expert chest x‐ray report. Conclusion : For identifying heart failure in breathless patients, urgent chest x‐ray with delayed formal report has not been shown to be redundant. Basic lung scan protocols should not yet replace chest x‐ray, but may be more reliable in the interim than inexpert clinician interpretation of chest x‐rays.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.067
GPT teacher head0.401
Teacher spread0.334 · 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.

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

Citations11
Published2013
Admission routes1
Has abstractyes

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