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136 Gp auscultation for diagnosing valvular heart disease

2017· article· en· W2735030853 on OpenAlexaff
Saul Myerson, Bernard Prendergast, Syed K M Gardezi, Anthony Prothero, Andrew Kennedy, Joanna Wilson

Bibliographic record

VenueHeart · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineAuscultationHeart Auscultationvalvular heart diseaseCardiologyHeart murmurInternal medicineHeart soundsHeart diseaseElectrocardiography

Abstract

fetched live from OpenAlex

Introduction Cardiac auscultation is an important clinical skill used by physicians in assessing and diagnosing valvular heart disease (VHD). The widespread use of echocardiography in the last three decades has coincided with a perceived decline in the utility of auscultation, particularly by general physicians. The ability of generalists to identify VHD in an unselected population has not been well characterised, so we aimed to determine the accuracy of auscultation in primary care for diagnosing VHD. Methods 251 participants aged 65 and over who were participating in the OxValve population cohort study were included. They were recruited from two participating GP surgeries and had no previous diagnosis of VHD. The participants underwent cardiac auscultation during the OxValve study visit by two experienced General Practitioners (GPs), neither of whom had a specialist interest in cardiology. A 5-point Likert scale was used to rate the ability to hear heart sounds (1=not at all; 5=perfectly) in addition to the presence or absence of a murmur, type of murmur and the ability to make a diagnosis based upon the auscultation findings. This was compared to transthoracic echocardiography performed at the same visit, but GPs were blind to the echocardiogram result, which was performed after auscultation. VHD was categorised as mild (either mild regurgitation [excluding trace/physiological] or aortic sclerosis) or significant (moderate/severe regurgitation or at least mild stenosis). Standard measures of diagnostic accuracy were calculated. Results 82 murmurs were heard by the GPs (80 systolic; 2 diastolic). Echocardiography identified mild VHD in 174 (69%) of the 251 participants, with more significant VHD present in 37 (15%). The ability to hear a murmur on auscultation was not related to age, BMI or heart rate (table 1). Auscultation had a sensitivity of 32% and specificity of 67% for diagnosing mild VHD, which improved slightly for significant VHD to a sensitivity of 43%, and specificity of 69% (table 2). The area under the curve on receiver operating characteristics (ROC) analysis was 0.50 for mild VHD and 0.56 for significant VHD (Figure-1) suggesting limited discriminatory ability. Conclusion GP auscultation has only moderate accuracy for diagnosing valvular heart disease in an unselected population, and the presence of an isolated murmur would not be a reliable indicator of valve disease. This study did not include patients with cardiovascular symptoms however, in whom the presence of a murmur may be more significant, and for whom echocardiography might be more appropriate. Abstract 136 Table 2 The accuracy of cardiac auscultation in diagnosing significant VHD Abstract 136 Figure 1 ROC curve for significant VHD Area under the curve = 0.56 (95% CI 0.46 – 0.66) Abstract 136 Table 1 The likelihood of hearing of murmur on auscultation and its relationship with age, BMI & heart rate

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)0.000
metaresearch head score (Gemma)0.000
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 score0.013
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.416
Teacher spread0.382 · 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".

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Citations8
Published2017
Admission routes1
Has abstractyes

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