Aortic Valve Replacement: Is Minimally Invasive Really Better? A Contemporary Systematic Review and Meta-Analysis
Bibliographic record
Abstract
In recent years, minimally invasive cardiac surgery has increased in prevalence. There has been significant debate regarding the optimal approach to isolated aortic valve replacement between conventional midline sternotomy and minimally invasive approaches. We performed a systematic review of the contemporary literature comparing minimally invasive to full sternotomy aortic valve replacement. PubMed and Embase were systematically searched for articles published from 2010-2021. A total of 1215 studies were screened and 45 studies (148,606 patients total) met the inclusion criteria. This study found rates of in-hospital mortality were higher with full sternotomy than ministernotomy ( P = 0.02). 30-day mortality was higher with full sternotomy compared to right anterior thoracotomy ( P = 0.006). Renal complications were more common with full sternotomy versus ministernotomy ( P < 0.00001) and right anterior thoracotomy ( P < 0.0001). Rates of wound infections were greater with full sternotomy than ministernotomy ( P = 0.02) and right anterior thoracotomy ( P < 0.00001). Intensive care unit length of stay ( P = 0.0001) and hospital length of stay ( P < 0.0001) were shorter with ministernotomy compared to full sternotomy. This review found that minimally invasive approaches to isolated aortic valve replacement result in reduced early mortality and select measures of postoperative morbidity; however, long-term mortality is not significantly different based on surgical approach. An analysis of mortality alone is not sufficient for the selection of the optimal approach to isolated aortic valve replacement. Surgeon experience, individual patient characteristics, and preference require thorough consideration, and additional studies investigating quality of life measures will be imperative in identifying the optimal approach to isolated aortic valve replacement.
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 | 0.014 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".