Ejection dynamics in native aortic valve stenosis using echocardiography: can it be helpful?
Bibliographic record
Abstract
Abstract Background The assessment of aortic stenosis (AS) severity has a major impact on the management of affected patients. Ejection dynamics, including acceleration time (AT), ejection time (ET), and acceleration time/ejection time ratio (AT/ET) measured using doppler echocardiography are established in the evaluation of prosthetic aortic valve stenosis with high sensitivity and specificity. However, their clinical utility in native AS has not been well described. Purpose The aim of this systematic review was to evaluate the diagnostic accuracy of ejection dynamics to identify severe AS and to assess whether ejection dynamics can differentiate low flow, low gradient severe AS from pseudo-severe AS. Methods We conducted a systematic review of Medline, Embase, and Web of Science from database inception until January 2021. We included observational studies and randomized controlled trials (RCTs) in which the diagnostic accuracy of ejection dynamics by doppler echocardiography for severe AS was compared with standard echocardiographic diagnostic criteria including peak velocity, mean pressure gradient, aortic valve area, and dimensionless index. Studies were eligible if they included AS of at least mild severity. Two authors independently screened and extracted data. Results We included 12 studies in the review (RCT=1, observational=11) with a total of 5182 participants. There was significant inconsistency in outcome measurement and reporting of results therefore a meta-analysis was not suitable. We used narrative synthesis to report our results. All included studies used standard echocardiographic criteria to ascertain the presence of severe AS. Mean age was 72 years and 53% of the participants were male. 1983 participants (38.3%) were classified as having severe AS. AT >94–109ms had sensitivity of 74–92% and specificity of 72–89% at identifying severe AS. AT/ET >0.34–0.35 showed sensitivity of 67–77% and specificity of 68–100%. Only one study compared low-flow, low-gradient AS with pseudo-severe AS, showing that an AT >100ms had sensitivity 62%, specificity 76%; and AT/ET >0.33, sensitivity 65%, specificity 84%. Data for ET showed insufficient consistency and diagnostic accuracy. Conclusions AT and AT/ET may be useful to corroborate the presence of severe AS. However, more research is needed to understand whether these parameters add incremental prognostic value to standard echocardiographic measures of AS severity. Funding Acknowledgement Type of funding sources: None. Summary of evidence search and selection
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".