| Literature DB >> 36237586 |
Michael L Williams1,2,3, Bridget Hwang2, Linna Huang2, Ashley Wilson-Smith2,4, John Brookes5, Aditya Eranki6, Tristan D Yan2,7, T Sloane Guy8, Johannes Bonatti9.
Abstract
Background: Robotic-assisted mitral valve surgery (RMVS) is becoming an increasingly performed procedure in cardiac surgery, however, its true safety and efficacy compared to the gold standard conventional sternotomy approach [conventional sternotomy mitral valve surgery (CSMVS)] remains debated. The aim of this meta-analysis was to provide a comprehensive analysis of all available literature comparing RMVS to CSMVS.Entities:
Keywords: Mitral valve disease; conventional sternotomy; mitral valve repair; mitral valve replacement; robotic cardiac surgery; robotic mitral valve surgery
Year: 2022 PMID: 36237586 PMCID: PMC9551372 DOI: 10.21037/acs-2022-rmvs-21
Source DB: PubMed Journal: Ann Cardiothorac Surg ISSN: 2225-319X
Figure 1PRISMA flow-chart summarizing the search strategy for relevant publications. CCRCT, Cochrane Central Register of Controlled Trials; CDSR, Cochrane Database of Systematic Reviews; DARE, Database of Abstracts of Review of Effectiveness; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
Study characteristics
| Primary author | Year | Country | Institution(s) | Study period | Type of study | Robotic (n) | Sternotomy (n) | Follow-up time (months), mean ± SD |
|---|---|---|---|---|---|---|---|---|
| Chemtob | 2020 | USA | Cleveland Clinic, Cleveland, Ohio | 2014–2019 | NR | 605 | 395 | NR |
| Coyan | 2018 | USA | University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania and West Virginia University, Morgantown, West Virgina | 2013–2015 | Retrospective PSM multicenter-center | 91 | 91 | 12 |
| Folliguet | 2006 | France | Institute Mutualiste Montsouris, Paris | 2000–2005 | Retrospective matched single-center | 25 | 25 | 24 |
| Hawkins | 2018 | USA | The Virginia Cardiac Services Quality Initiative (VCSQI) Database | 2011–2016 | Retrospective multi-center* | 372 | 1,352 | NR |
| Kam | 2010 | Australia | Epworth Hospital, Melbourne, Australia | 2005–2008 | Retrospective single-center | 107 | 40 | NR |
| Kesävuori | 2018 | Finland | University Central Hospital, Helsinki | 2011–2015 | Retrospective PSM single-center | 142 | 142 | 35±17 robotic, |
| Mihaljevic | 2011 | USA | Cleveland Clinic, Cleveland, Ohio, USA | 2006–2009 | Retrospective PSM single-center | 106 | 106 | NR |
| Seo | 2019 | USA | University of California, Los Angeles, California | 2008–2016 | Retrospective single-center | 175 | 259 | NR |
| Sicim | 2021 | Turkey | University of Health Sciences, Gulhane Training and Research Hospital, Ankara | 2014–2020 | Retrospective single-center | 64 | 66 | NR |
| Stevens | 2012 | USA | East Carolina University Hospital, Greenville, North Carolina, USA | 1992–2009 | Retrospective single-center | 447 | 377 | 76.8±54 |
| Suri | 2011 | USA | Mayo Clinic, Rochester, Minnesota | 2007–2010 | Retrospective PSM single-center | 95 | 95 | 1 |
| Wang | 2018 | USA | Duke University Medical Center, Durham, North Carolina-The Society of Thoracic Surgeons (STS) database | 2011–2014 | Retrospective PSM multi-center database | 503 | 503 | 21.36 (11.52–30.96)** |
| Woo | 2006 | USA | University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania | 2002–2005 | Retrospective single-center | 25 | 39 | NR |
| Zhao | 2020 | China | General Hospital of PLA, Beijing | 2002–2014 | Retrospective PSM single-center | 47 | 47 | 6 |
*, study also includes PSM cohorts; **, median and interquartile range. n, number of patients; SD, standard deviation; NR, not report; PSM, propensity score matched.
Figure 2Risk of bias assessment of included studies utilising the ROBINS-I tool. ROBINS-I, Risk Of Bias in Non-randomized Studies of Interventions.
Pooled baseline characteristics for all included studies
| Variable | Robotic (n=2,804) | Sternotomy (n=3,537) |
|---|---|---|
| Age (years), mean | 63.5 | 64.6 |
| Male, % | 65.5 | 61.8 |
| BMI (kg/m2), mean | 26.0 | 26.5 |
| Hypertension, % | 43.4 | 46.7 |
| Diabetes, % | 4.6 | 7.8 |
| Cerebrovascular disease, % | 3.0 | 4.8 |
| Respiratory disease, % | 4.6 | 8.2 |
| LVEF, mean | 61.5 | 60.5 |
| Cardiac arrhythmia, % | 13.9 | 18.4 |
| PVD, % | 3.4 | 3.7 |
| NYHA III/IV, % | 19.4 | 26.8 |
| Valve pathology—myxomatous degeneration, % | 94.6 | 90.5 |
BMI, body mass index; LVEF, left ventricular ejection fraction; PVD, peripheral vascular disease; NYHA, New York Heart Association.
Figure 3Forest plot of OR for all-cause mortality (A), CVA (B), and re-operation for bleeding (C) for robotic versus conventional sternotomy mitral valve surgery. M-H, Mantel-Haenszel test; CI, confidence interval; OR, odds ratio; CVA, cerebrovascular accidents.
Figure 4Forrest plot of MD for cross clamp (A), and CPB times (B) for robotic versus conventional sternotomy mitral valve surgery. MD, mean difference; CPB, cardiopulmonary bypass; SD, standard deviation.
Figure 5Forrest plot of MD for ICU stay (hours) (A), and length of hospital stay (days) (B) for robotic versus conventional sternotomy mitral valve surgery. ICU, intensive care unit; MD, mean difference; SD, standard deviation.