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Record W299837726

B-type natriuretic peptide and tissue doppler for predicting symptoms on treadmill exercise in apparently asymptomatic aortic stenosis.

2009· article· en· W299837726 on OpenAlexaff
Ronak Rajani, Helen Rimington, John B. Chambers

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineAsymptomaticInternal medicineCardiologyNatriuretic peptideStenosisTreadmillDoppler echocardiographyDoppler imagingHeart failureBlood pressureDiastole
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND AND AIM OF THE STUDY: Exercise-induced symptoms are associated with early changes in left ventricular (LV) function. Blood B-type natriuretic peptide (BNP) and tissue Doppler indices (tDi) also reflect early LV dysfunction, and may therefore predict the development of symptoms. The study aim was to compare BNP levels and tDi for predicting symptoms on treadmill exercise in apparently asymptomatic aortic stenosis (AS). METHODS: A total of 65 patients (mean age 66 years) with an aortic effective orifice area <1.5 cm2 who were asymptomatic on formal questioning, underwent transthoracic echocardiography, measurement of blood BNP level, and exercise testing using a modified Bruce protocol. RESULTS: A blood BNP level >58 pg/ml had a sensitivity of 86% and specificity of 64% (AUC = 0.81) for the development of symptoms on exercise testing. The combined tDi index of peak systolic shortening velocity <8 cm/s and E/Ea >15 had a sensitivity of 52% and specificity of 73%. In patients with no symptoms on exercise, 27% with a blood BNP level >58 pg/ml compared to 7% with a level < or =58 pg/ml developed symptoms during follow up. CONCLUSION: The study results suggested that patients with a blood BNP level < or =58 pg/ml can be seen up to one year, while those with a BNP level >58 pg/ml required exercise testing and a more frequent follow up. The combined tissue Doppler indices gave a similar, but less accurate, stratification.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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 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

Citations14
Published2009
Admission routes1
Has abstractyes

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