Perspective on the treatment of functional mitral regurgitation using the Cardioband System
Bibliographic record
Abstract
This commentary refers to ‘Transcatheter mitral valve repair for functional mitral regurgitation using the Cardioband system: 1 year outcomes’, by D. Messika-Zeitoun et al., 2019;40:466–472. We read with interest Dr Shapira’s editorial regarding our manuscript entitled ‘Transcatheter mitral valve repair for functional mitral regurgitation using the Cardioband system: 1 year outcomes’.1 The comment that ‘these rather optimistic results are obviously misleading’ contradicts the transparency evidenced by the detailed data and discussion provided in the manuscript. We presented data both as paired comparisons and in the overall population taking into account loss to follow-up, deaths, and reintervention, approach uncommon in the medical literature. The comment ‘Cardioband system is far from being perfect’ misconstrues our intent for reporting early results of an innovative therapy (first 60 patients implanted since the first-in-human experience in 2013) that encompass a mix of learning curve and technical improvements, including anchor disengagements which were concentrated in the first half of our experience. To view these results as the final potential of the device, and to compare these preliminary results to those obtained in surgery in different populations, is inaccurate. As with any novel procedure, improvements in both procedural length and success rates are expected as teams gain experience. Assessment of MR severity is questioned. Like all transcatheter/surgical therapies, this procedure is performed under general anaesthesia which is known to affect MR severity. Haemodynamic stimulation could easily be implemented in the future. More importantly, the degree of MR was re-evaluated before discharge using transthoracic echocardiography. The criticism that the implant is ‘not a full ring’ and that ‘the more stringent mitral valve academic research consortium definition of “optimal” residual MR should have been considered and would have yielded results inferior to those achievable by a surgical undersized ring implantation’ should be addressed. Comparing studies is difficult at best; however, if one wish to do so, assessment of surgical outcomes should come from one of the few randomized studies2 which reported a 32.6% rate of moderate or severe—not mild—MR recurrence at 1 year, with a complete ring. The opinion that the Cardioband is equivalent to surgical examples of ‘not a full ring’ is based on historical preconceptions and the assumption that all things are equal between transcatheter and surgical therapies other than access. The capability to perform real-time echo assessment and size adjustment on a beating heart is unique compared to the need to define a leaflet coaptation criteria during surgical intervention in arrested heart context. The suggestion that we treated patients that should not have been treated citing the current ESC/EACTS guidelines is incorrect.3 Level of evidence is weak, and management of these patients still debated.4 Finally, it is stated that the device is “not suitable for a considerable number of patients” citing a reference reporting 11.7% prevalence of mitral annular calcification in patients with MR’. Not all valve anatomies are suitable for the Cardioband device and patients with MAC or extreme tethering were excluded as mentioned in our manuscript. In our experience, the Cardioband system is applicable in a fair proportion of functional MR patients. We do hope that our response will help the reader having a better understanding of current achievements and prospects of the Cardioband system. Conflict of interest: D.M.-Z. is a consultant for Edwards Lifesciences, Mardil and Cardiawave and receives research grants from Edwards Lifesciences and Abbott vascular. A.V. is consultant for Edwards Lifesciences, Abbott vascular and Mitraltech. P.V. is an Edwards Lifesciences employee. F.M. is consultant Edwards Lifesciences and has financial interest in Valtechcardio and Edwards Lifesciences. The authors of ehz613 were invited to submit a response to Discussion Forum contribution ehy424, but opted not to.
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 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.030 | 0.029 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".