Midterm Echocardiographic Follow-Up After Ross Operation
Bibliographic record
Abstract
Background —The pulmonary autograft (Ross) operation is an attractive treatment for aortic valve disease, but hemodynamic follow-up is not well defined. Methods and Results —One hundred thirty-two consecutive patients (62% male, mean age 40±11 years) were followed up to 5 years after the Ross operation. Echocardiography was performed early (within 30 days), 3 to 6 months, and yearly after surgery. The valve effective orifice area (EOA) and mean transvalvular gradient of both aortic and pulmonary valves were measured, and transvalvular regurgitation was assessed by using color Doppler echocardiography. EOA was indexed for body surface area. The hemodynamic performance was excellent for both the aortic and pulmonary valves early after surgery (gradient, 3±4 and 3±4 mm Hg, respectively). It remained stable thereafter for the aortic valve, whereas there was a significant deterioration of the EOA (−0.74±0.82 cm 2 ) and gradient (+6±8 mm Hg) for the pulmonary valve, which occurred mostly during the first 6 months after surgery. This hemodynamic deterioration resulted in suboptimal (defined as an EOA index <0.85 cm 2 /m 2 ) hemodynamics in 19.3% of the patients, to the extent that 3 (2%) of the 132 patients eventually had to be subjected to further surgery for severe pulmonary valve stenosis. Conclusions —The pulmonary autograft provides continued excellent hemodynamics in the aortic position, whereas moderately high gradients can be found across the pulmonary homograft in some patients. Further studies are necessary to identify the factors responsible for the deterioration of the hemodynamic performance of the homograft in the pulmonary position and to determine its impact on right ventricular function and clinical status.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".