Patient selection for minimally invasive aortic valve implantation
Bibliographic record
Abstract
We have read with great interest the two original articles in the January issue of the Journal that report early experiences with transapical aortic valve replacement [1,2]. These studies show that beating-heart transapical aortic valve implantation has acceptable early results in patients deemed to be at too high a risk to allow for a safe valve replacement by conventional surgery. The authors of both studies should be celebrated as innovators and congratulated for their pioneering efforts using these novel technologies. In these studies, transapical procedures were reserved for patients with preoperative risk profiles that were deemed to be prohibitive for traditional valve replacement such that a successful outcome following conventional surgery was considered unlikely. However, precise inclusion criteria and a definition of inoperability were not provided in these papers. The lack of a transparent patient selection process makes these studies difficult to interpret and compromises the reader’s ability to get a sense of the role of these interventions in the management of severe aortic stenosis. Furthermore, we are concerned that much of the preoperative risk stratification in these studies relied on the logistic EuroSCORE. Predictive models including the EuroSCORE have previously been shown to lose discriminatory capability at the extremes of risk [3,4]. To illustrate our point, we have reviewed all consecutive patients undergoing aortic valve replacement at our institution over a 10-year period (1995–2005). The population evaluated included a total of 1879 consecutive patients. During that time period, there were 325 patients, with a logistic EuroSCORE of greater than 20%, who underwent conventional aortic valve surgery. The average predicted mortality for that group was 39.4% by logistic EuroSCORE. In contrast, we have found in this high-risk group of patients that the observed in-hospital mortality was only 15.1%, which was significantly lower than what was predicted. Therefore, relying on the EuroSCORE to predict preoperative mortality risk may inappropriately classify patients as high-risk patients and unsuitable for conventional aortic valve replacement. Taken further, this may mean that some patients with high EuroSCORE could be denied an intervention that can potentially benefit them. These studies [1,2] are early feasibility studies and are not randomized controlled trials evaluating two potentially equivalent and equally acceptable interventions. The investigators should interpret their results accordingly and not overstate their conclusions by reporting that this technology is a ‘viable alternative’ to conventional surgical aortic valve replacement [2]. The issue here is one of good science and not the reluctance to accept an emerging technique.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".