Minimally invasive access type related to outcomes of sutureless and rapid deployment valves
Bibliographic record
Abstract
OBJECTIVES: Minimally invasive surgical techniques with optimal outcomes are of paramount importance. Sutureless and rapid deployment aortic valves are increasingly implanted via minimally invasive approaches. We aimed to analyse the procedural outcomes of a full sternotomy (FS) compared with those of minimally invasive cardiac surgery (MICS) and further assess MICS, namely ministernotomy (MS) and anterior right thoracotomy (ART). METHODS: We selected all isolated aortic valve replacements in the Sutureless and Rapid Deployment Aortic Valve Replacement International Registry (SURD-IR, n = 2257) and performed propensity score matching to compare aortic valve replacement through FS or MICS (n = 508/group) as well as through MS and ART accesses (n = 569/group). RESULTS: Postoperative mortality was 1.6% in FS and MICS patients who had a mean logistic EuroSCORE of 11%. Cross-clamp and cardiopulmonary bypass (CPB) times were shorter in the FS group than in the MICS group (mean difference 3.2 and 9.2 min; P < 0.001). Patients undergoing FS had a higher rate of acute kidney injury (5.6% vs 2.8%; P = 0.012). Direct comparison of MS and ART revealed longer mean cross-clamp and CPB times (12 and 16.7 min) in the ART group (P < 0.001). The postoperative outcome revealed a higher stroke rate (3.2% vs 1.2%; P = 0.043) as well as a longer postoperative intensive care unit [2 (1-3) vs 1 (1-3) days; P = 0.009] and hospital stay [11 (8-16) vs 8 (7-12) days; P < 0.001] in the MS group than in the ART group. CONCLUSIONS: According to this non-randomized international registry, FS resulted in a higher rate of acute kidney injury. The ART access showed a lower stroke rate than MS and a shorter hospital stay than all other accesses. All these findings may be related to underlying patient risk factors.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".