Impact of blood pressure on the Doppler echocardiographic assessment of severity of aortic stenosis
Bibliographic record
Abstract
OBJECTIVE: To investigate the impact of blood pressure (BP) on the Doppler echocardiographic (Doppler-echo) evaluation of severity of aortic stenosis (AS). METHODS: Handgrip exercise or phenylephrine infusion was used to increase BP in 22 patients with AS. Indices of AS severity (mean pressure gradient (DeltaP(mean)), aortic valve area (AVA), valve resistance, percentage left ventricular stroke work loss (% LVSW loss) and the energy loss coefficient (ELCo)) were measured at baseline, peak BP intervention and recovery. RESULTS: From baseline to peak intervention, mean (SD) BP increased (99 (8) vs 121 (10) mm Hg, p<0.001), systemic vascular resistance (SVR) increased (1294 (264) vs 1552 (372) dynexs/cm(5), p<0.001) and mean (SD) transvalvular flow rate (Q(mean)) decreased (323 (67) vs 306 (66) ml/s, p = 0.02). There was no change in DeltaP(mean) (36 (13) vs 36 (14) mm Hg, p = NS). However, there was a decrease in AVA (1.15 (0.32) vs 1.09 (0.33) cm(2), p = 0.02) and ELCo (1.32 (0.40) vs 1.24 (0.42) cm(2), p = 0.04), and an increase in valve resistance (153 (63) vs 164 (74) dynexs/cm(5), p = 0.02), suggesting a more severe valve stenosis. In contrast, % LVSW loss decreased (19.8 (6) vs 16.5 (6)%, p<0.001), suggesting a less severe valve stenosis. There was an inverse relationship between the change in mean BP and AVA (r = -0.34, p = 0.02); however, only the change in Q(mean) was an independent predictor of the change in AVA (r = 0.81, p<0.001). CONCLUSIONS: Acute BP elevation due to increased SVR can affect the Doppler-echo evaluation of AS severity. However, the impact of BP on the assessment of AS severity depends primarily on the associated change in Q(mean), rather than on an independent effect of SVR or arterial compliance, and can result in a valve appearing either more or less stenotic depending on the direction and magnitude of the change in Q(mean).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".