| Literature DB >> 35028981 |
Mohammad Yousuf Salmasi1,2, Sruthi Ramaraju1, Iqraa Haq1, Ryan A B Mohamed2, Taimoor Khan2, Faruk Oezalp2, George Asimakopoulos2, Shahzad G Raja2.
Abstract
OBJECTIVES: Despite the benefits of rapid deployment aortic valve prostheses (RDAVR), conventional sutured valves (cAVR) are more commonly used in the treatment for aortic stenosis. Given the paucity of randomized studies, this study aimed to synthesize available data to compare both treatment options.Entities:
Keywords: aortic valve replacement; rapid deployment valves; sutureless valves
Mesh:
Year: 2022 PMID: 35028981 PMCID: PMC9305745 DOI: 10.1111/jocs.16223
Source DB: PubMed Journal: J Card Surg ISSN: 0886-0440 Impact factor: 1.778
Figure 1(A) PRISMA flowchart of included studies at each stage of screening. (B) Funnel plot for included studies. PRISMA, Prescribed Reported Items for Systematic Reviews and Meta‐analysis
Characteristics of included studies
| Author | Year | Study design | Total no. of participants | No. RDAVR | No. cAVR | Mean follow‐up (years) | Follow‐up, years (RDAVR) | Follow‐up, years (cAVR) | Mean age (RDAVR) | Mean age (cAVR) |
|---|---|---|---|---|---|---|---|---|---|---|
| Andreas | 2016 | Parallel cohort | 248 | 116 | 132 | 2 | 2.9 | 75 | 70 | |
| Beckmann | 2016 | Comparative, retrospective | 128 | 92 | 36 | 2.9 ± 1.6 | 4.4 ± 2.8 | 62 | 79 | |
| Belluschi | 2017 | Observational, retrospective | 124 | 62 | 62 | 79 | 79 | |||
| Bening | 2017 | Retrospective | 68 | 43 | 25 | 74.1 | 74.2 | |||
| Casha | 2018 | Retrospective, single‐center, risk‐matched cohort. | 40 | 20 | 20 | 76.95 | 78.29 | |||
| Chiariello | 2019 | Retrospective, nonrandomized trial | 76 | 52 | 24 | 2.9 ± 0.5 | 78.5 | 77 | ||
| D'Onofrio | 2013 | Propensity‐ matched analysis | 286 | 31 | 112 | 0.083 | 73.5 | 73.5 | ||
| Dalen | 2015 | Observational, retrospective | 565 | 182 | 383 | 3.2 ± 2.1 | 77.5 | 73.8 | ||
| Dedeilias | 2016 | Prospective, randomized | 50 | 25 | 25 | 0.67 ± 0.13 | 0.67 ± 0.15 | 80 | 79 | |
| Ensminger | 2018 | Observational, propensity‐matched, prospective study, multicentre study (~22,000 patients) | 2042 | 1021 | 1021 | 75 | 75 | |||
| Ferrari | 2017 | Retrospective, non‐randomized trial | 64 | 32 | 32 | 1 | 1 | 1 | 78 | 72.5 |
| Forcillo | 2016 | Retrospective | 395 | 76 | 319 | 83 | 83 | |||
| Ghoneim | 2016 | Retrospective, single‐center study | 351 | 49 | 259 | 78 | 74.7 | |||
| Gilmanov | 2014 | Retrospective, observational, cohort | 266 | 133 | 133 | 1.28 ± 0.67 | 4.47 ± 2.42 | 75.3 | 73.6 | |
| Gotzmann | 2019 | Retrospective, propensity score matched single‐center study | 108 | 54 | 54 | 0.77 | 73.2 | 72.9 | ||
| Hanedan | 2018 | Retrospective, non‐randomized study | 70 | 38 | 32 | 2.19 ± 1.76 | 1.41 ± 0.97 | 3.12 ± 2.03 | 71.2 | 69.5 |
| Ilhan | 2020 | Prospective, cohort study | 140 | 48 | 92 | 0.5 | 0.5 | 76.3 | 73.6 | |
| Konertz | 2017 | Retrospective, cohort study | 79 | 16 | 63 | 73 | 67.5 | |||
| Mujtaba | 2018 | Retrospective, observational, cohort | 763 | 139 | 624 | 74.3 | 71.74 | |||
| Muneretto | 2015 | Retrospective, propensity matched, cohort | 408 | 204 | 204 | 2 | 2 | 2 | 80 | 79 |
| Muneretto | 2014 | Prospective, cohort study | 108 | 53 | 55 | 2 | 2 | 2 | 79 | 79 |
| Nguyen | 2017 | Retrospective, observational | 236 | 59 | 177 | 1 | 1 | 1 | 70 | 69 |
| Pollari | 2014 | Retrospective | 164 | 82 | 82 | 1.08 ± 0.5 | 75.5 | 74.5 | ||
| Rahmanian | 2018 | Nonrandomized, retrospective analysis | 326 | 163 | 163 | 75.8 | 75.8 | |||
| Sainte | 2017 | Retrospective, single‐center, matched case‐control | 104 | 52 | 52 | 1 | 79.1 | 78.5 | ||
| Santarpino | 2013 | Multicenter study | 100 | 50 | 50 | 77.5 | 71.7 | |||
| Shalabi | 2016 | Prospective, cohort study | 44 | 22 | 22 | 1.17 ± 0.92 | 3.75 ± 1.83 | 77 | 79 | |
| Shreshta | 2013 | Retrospective, multicentre, nonrandomized | 120 | 50 | 70 | 2.73 ± 1.29 | 79.8 | |||
| Smith | 2017 | Retrospective, propensity‐matched cohort study | 82 | 41 | 41 | 0.14 ± 0.11 | 76.5 | |||
| Stanger | 2017 | Retrospective, observational | 1388 | 82 | 1306 | 76.9 | 72.6 | |||
| Stegmeier (Labcor) | 2020 | Retrospective | 87 | 25 | 62 | 79 | 74.4 | |||
| Thitivaraporn | 2018 | Retrospective | 20 | 10 | 10 | 1 | 81.5 | 81.1 | ||
| Villa | 2019 | Retrospective | 231 | 113 | 118 | 80.1 | 75.5 | |||
| Vola | 2015 | Retrospective, single‐center | 83 | 41 | 42 | 2.13 ± 1.08 | 1.59 ± 0.42 | 2.59 ± 1.12 | 75.7 | 75.3 |
| Wahlers | 2018 | Retrospective, multicentre, nonrandomized, propensity‐matched cohort | 545 | 287 | 258 | 3 | 2.7 ± 0.8 | 3 | 75.3 | 68.5 |
Abbreviations: cAVR, conventional aortic valve replacement; RDAVR, rapid deployment aortic valve replacement.
Figure 2(A) Forest plot demonstrating the operative mortality following RDAVR versus cAVR. Subgroup analysis is shown based on the RDAVR prosthesis used in each study. (B) Forest plot demonstrating the risk of stroke following RDAVR compared with cAVR. Subgroup analysis is shown based on the RDAVR prosthesis used in each study. cAVR, conventional aortic valve replacement; RDAVR, rapid deployment aortic valve replacement
Figure 3Forest plot demonstrating the risk of pacemaker insertion following RDAVR compared with cAVR. Subgroup analysis is shown based on (A) the RDAVR prosthesis used in each study, and (B) the study design. cAVR, conventional aortic valve replacement; RDAVR, rapid deployment aortic valve replacement
Figure 4Forest plot demonstrating the ITU stay following RDAVR compared with cAVR. Subgroup analysis is shown based on (A) the RDAVR prosthesis used in each study, and (B) the surgical approach. cAVR, conventional aortic valve replacement; RDAVR, rapid deployment aortic valve replacement
Figure 5Echocardiographic outcomes, comparison of RDAVR with cAVR, including (A) paravalvular leak, (B) indexed effective orifice area, and (C) mean gradient across valve. cAVR, conventional aortic valve replacement; RDAVR, rapid deployment aortic valve replacement
Results of meta‐regression demonstrating the influence of covariates on four outcomes of interest: mortality, stroke, pacemaker rate, paravalvular leak (PVL)
| Covariate | Coef | Standard error | 95% CI |
|
|---|---|---|---|---|
| Influence of covariates on operative mortality | ||||
| Age | 0.035 | 0.052 | −0.052 to 0.122 | .419 |
| BMI | 0.009 | 0.151 | −0.306 to 0.323 | .953 |
| LVEF | 0.0042 | 0.033 | −0.065 to 0.074 | .899 |
| Euroscore | 0.0057 | 0.044 | −0.092 to 0.103 | .898 |
| Influence of covariates on stroke | ||||
| Age | −0.067 | 0.065 | −0.204 to 0.069 | .314 |
| BMI | −0.117 | 0.250 | −0.654 to 0.420 | .649 |
| LVEF | −0.039 | 0.018 | −0.042 to 0.037 | .892 |
| Euroscore | −0.081 | 0.054 | −0.208 to 0.045 | .172 |
| Influence of covariates on pacemaker rate | ||||
| Age | −0.004 | 0.037 | −0.083 to 0.075 | .916 |
| BMI | 0.020 | 0.126 | −0.247 to 0.285 | .878 |
| LVEF | 0.077 | 0.186 | −0.724 to 0.880 | .717 |
| Euroscore | −0.002 | 0.064 | −0.180 to 0.179 | .997 |
| Valve size | 0.005 | 0.005 | −0.009 to 0.020 | .361 |
| Influence of covariates on PVL rate | ||||
| Age | 0.124 | 0.162 | −0.575 to 0.822 | .526 |
| BMI | −0.635 | 0.567 | −2.023 to 0.753 | .306 |
| LVEF | −0.0049 | 0.029 | −0.097 to 0.088 | .877 |
| Euroscore | 0.138 | 0.133 | −0.435 to 0.711 | .409 |
| Valve size | −0.014 | 0.011 | −0.048 to 0.020 | .276 |
Abbreviation: BMI, body mass index. LVEF, left ventricular ejection fraction.