Minimally invasive mitral valve surgery versus conventional sternotomy mitral valve surgery: A systematic review and meta‐analysis of 119 studies
Bibliographic record
Abstract
Abstract Background and Aim of the Study Whether minimally invasive mitral valve surgery (MMVS) leads to better outcomes remains unclear. We conducted a systematic review and meta‐analysis comparing various MMVS approaches with conventional sternotomy. Methods We searched Cochrane CENTRAL, MEDLINE, EMBASE, ClinicalTrials. gov, and the ISRCTN Register for studies comparing minimally invasive approach (thoracotomy, port access, partial sternotomy, or robotic) with median sternotomy for mitral valve surgery. We performed title and abstract, full‐text screening, and data extraction independently and in duplicate. We pooled data using random effect models. Quality assessment was performed using validated tools. Certainty of evidence was established using the GRADE framework. Results One hundred and nineteen studies ( n = 38,106) met eligibility criteria: eight randomized controlled trials (RCTs) and 111 observational studies. MMVS was associated with fewer days in hospital (RCT: MD: −2.2 days, 95% CI, [−3.7 to −0.8]; observational: MD: −2.4 days, 95% CI, [−2.7 to −2.1]). Observational studies suggested that MMVS reduced transfusion requirements with fewer units transfused per patient (MD: −1.2; 95% CI, [−1.6 to −0.9]) and fewer patients transfused (RR, 0.7; 95% CI, [0.6−0.7]). Observational data also suggested lower mortality with MMVS (RR, 0.6; 95% CI, [0.5−0.7], p < .001, I 2 = 0%), but this was not corroborated by RCT data. The risk of postoperative mitral regurgitation (≥2+ or requiring re‐intervention) did not differ between the two groups. Conclusions MMVS may be associated with shorter length of hospital stay with no significant difference in short‐term morbidity and mortality. There is a paucity of high‐quality data on the long‐term outcomes of MMVS when compared with conventional sternotomy.
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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.039 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".