Efficacy of Acellular Dermal Matrix in Soft Tissue Augmentation Around Dental Implants: A Systematic Review and Meta-Analysis

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Abstract

This study was done to perform a systematic review and meta-analysis of the studies on the efficacy of acellular dermal matrix (ADM) in increasing the soft tissue thickness (STT) and keratinized mucosal width (KMW) around dental implants. The PubMed, Scopus, Cochrane, Web of Science, and ProQuest databases were searched by July 2020 to retrieve relevant studies. Depending upon the heterogeneity of included studies, the weighted mean difference (WMD) with 95% CI was calculated using either fixed or random-effects model. Based on the meta-analysis of 6 studies, the effect of ADM on STT and KMW was significant (WMD: 1.07 [95% CI: 0.34–1.79], P = .004, and WMD: 1.99 [95% CI: 0.88–3.09], P < .001, respectively). Further, a comparison between the efficacy of the ADM and the control group, which included the autogenous soft tissue augmentation techniques, showed no statistically significant differences between groups (STT: WMD: 0.24 [95% CI: −0.26 to 0.74], P = .161 and KMW: WMD: −0.23 [95% CI: −0.68 to 0.22], P = .324). The subgroup analysis showed that simultaneous augmentation and implant placement were increased by 0.23 mm in the KMW, and the placement of ADM around loaded implants caused 0.5 mm decrease in the KMW, which was not statistically significant. Accordingly, it is possible to substitute ADM for soft tissue augmentation around dental implants.

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Most cited references 64

Record: found
Abstract: not found
Article: not found

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

David Moher, Alessandro Liberati, Jennifer Tetzlaff … (2009)

0 comments Cited 7593 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

Bias in meta-analysis detected by a simple, graphical test

Jos I. M. Egger, G D Smith, M. Schneider … (1997)

0 comments Cited 7122 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Quantifying heterogeneity in a meta-analysis.

Julian P T Higgins, Simon G Thompson (2002)

The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.