Nikolaos Pandis

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Articles (11)

Year:

2023

Year:

2023

Meta‐analyses may provide imprecise estimates when important meta‐analysis parameters are not considered during the synthesis. The aim of this case study was to highlight the influence of meta‐analysis parameters that can affect reported estimates using as an example pre‐existing meta‐analyses on the association between implant survival and sinus membrane perforation. PubMed was searched on 7 July 2021 for meta‐analyses comparing implant failure in perforated and non‐perforated sinus membranes. Primary studies identified in these meta‐analyses were combined in a new random‐effects model with odds ratios (ORs), confidence intervals (CIs), and prediction intervals reported. Using this new meta‐analysis, further meta‐analyses were then undertaken considering the clinical, methodological, and statistical heterogeneity of the primary studies, publication bias, and clustering effects. The meta‐analyses with the greatest number and more homogeneous studies provided lower odds of implant failure in non‐perforated sites (OR 0.49, 95 % CI = [0.26, 0.92]). However, when considering heterogeneity, publication bias, and clustering (number of implants), the confidence in these results was reduced. Interpretation of estimates reported in systematic reviews can vary depending on the assumptions made in the meta‐analysis. Users of these analyses need to carefully consider the impact of heterogeneity, publication bias, and clustering, which can affect the size, direction, and interpretation of the reported estimates.

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2021

Year:

2020

Year:

2020

Collaborators (7)

Bjorn Klinge

Karolinska Institutet

SWEDEN
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Georgios Tsakos

University College London

UNITED KINGDOM
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Johan Burisch

-

DENMARK
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Michail Tsagris

University of Crete

GREECE
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Jadbinder Seehra

King’s College London

UNITED KINGDOM
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Andreas Stavropoulos

-

SWEDEN
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Kristina Bertl

-

AUSTRIA
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