| Literature DB >> 26455332 |
Sulin Zhang1,2, Yangming Leng1,2, Bo Liu1,2, Hao Shi3, Meixia Lu3, Weijia Kong1,2,4.
Abstract
In this study, we evaluated the clinical diagnostic value of vestibular evoked myogenic potentials (VEMPs) for endolymphatic hydrops (EH) by systematic review and Meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under summary receiver operating characteristic curves (AUC) were calculated. Subgroup analysis and publication bias assessment were also conducted. The pooled sensitivity and the specificity were 49% (95% CI: 46% to 51%) and 95% (95% CI: 94% to 96%), respectively. The pooled positive likelihood ratio was 18.01 (95% CI: 9.45 to 34.29) and the pooled negative likelihood ratio was 0.54 (95% CI: 0.47 to 0.61). AUC was 0.78 and the pooled diagnostic odds ratio of VEMPs was 39.89 (95% CI: 20.13 to 79.03). In conclusion, our present meta-analysis has demonstrated that VEMPs test alone is not sufficient for Meniere's disease or delayed endolymphatic hydrops diagnosis, but that it might be an important component of a test battery for diagnosing Meniere's disease or delayed endolymphatic hydrops. Moreover, VEMPs, due to its high specificity and non-invasive nature, might be used as a screening tool for EH.Entities:
Mesh:
Year: 2015 PMID: 26455332 PMCID: PMC4601069 DOI: 10.1038/srep14951
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Flowchart for the selection procedure for eligible studies.
Characteristics of included eligible studies.
| Author | Country | Study design | Case N | Control N | TP | FN | FP | TN | Funding |
|---|---|---|---|---|---|---|---|---|---|
| 2003 Yi-Ho Young | Taiwan | prospective | 40 | 40 | 16 | 24 | 0 | 40 | Government |
| 2008 Seok Min Hong | Korea | prospective | 29 | 29 | 20 | 9 | 0 | 29 | No funding |
| 1999 catherine de waele | France | retrospective | 59 | 37 | 27 | 32 | 4 | 33 | No funding |
| 2012 CHI-HSUAN HUANG 1 | Taiwan | prospective | 50 | 50 | 22 | 28 | 0 | 50 | No funding |
| 2012 CHI-HSUAN HUANG 2 | Taiwan | prospective | 50 | 50 | 19 | 31 | 0 | 50 | No funding |
| 2011 Stephanie M Winters 1 | Netherlands | prospective | 31 | 55 | 14 | 17 | 1 | 54 | No funding |
| 2011 Stephanie M Winters 2 | Netherlands | prospective | 37 | 55 | 27 | 10 | 1 | 54 | No funding |
| 2008 Giuseppe Magliulo 1 | Italy | prospective | 22 | 22 | 8 | 14 | 0 | 22 | No funding |
| 2008 Giuseppe Magliulo 2 | Italy | prospective | 22 | 22 | 7 | 15 | 0 | 22 | No funding |
| 2008 Giuseppe Magliulo 3 | Italy | prospective | 22 | 22 | 7 | 15 | 0 | 22 | No funding |
| 2006 Gu¨ zin Akkuzu | Turkey | prospective | 20 | 34 | 10 | 10 | 2 | 32 | No funding |
| 2005 Shih-Wei Kuo 1 | Taiwan | prospective | 12 | 12 | 8 | 4 | 0 | 12 | No funding |
| 2005 Shih-Wei Kuo 2 | Taiwan | prospective | 12 | 12 | 4 | 8 | 0 | 12 | No funding |
| 2012 M. Geraldine Zuniga 1 | USA | prospective | 20 | 56 | 4 | 16 | 0 | 56 | Government |
| 2012 M. Geraldine Zuniga 2 | USA | prospective | 20 | 56 | 10 | 10 | 2 | 54 | Government |
| 2012 M. Geraldine Zuniga 3 | USA | prospective | 20 | 56 | 2 | 18 | 2 | 54 | Government |
| 2006 Ming-Yee Lin 1 | Netherlands | prospective | 17 | 24 | 17 | 0 | 0 | 24 | Government |
| 2006 Ming-Yee Lin 2 | Netherlands | prospective | 6 | 24 | 5 | 1 | 0 | 24 | Government |
| 2012 ANA PAULA SERRA | Brazil | prospective | 12 | 66 | 6 | 6 | 0 | 66 | Government |
| 2012 Jaswinder S. Sandhu | UK | prospective | 12 | 16 | 12 | 0 | 0 | 16 | No funding |
| 2012 HSUN-MO WANG | Taiwan | retrospective | 79 | 60 | 30 | 49 | 0 | 60 | No funding |
| 2011 TOSHIHISA MUROFUSHI 1 | Japan | prospective | 20 | 14 | 11 | 9 | 0 | 14 | No funding |
| 2011 TOSHIHISA MUROFUSHI 2 | Japan | prospective | 20 | 14 | 9 | 11 | 0 | 14 | No funding |
| 2002 Yi-Ho Young | Taiwan | prospective | 10 | 16 | 3 | 7 | 0 | 16 | No funding |
| 2007 V OSEI-LAH 1 | UK | prospective | 11 | 36 | 2 | 9 | 0 | 36 | Government |
| 2007 V OSEI-LAH 2 | UK | prospective | 9 | 36 | 5 | 4 | 0 | 36 | Government |
| 2007 V OSEI-LAH 3 | UK | prospective | 20 | 36 | 5 | 15 | 0 | 36 | Government |
| 2013 Min-Beom Kim | Korea | prospective | 41 | 66 | 14 | 27 | 0 | 66 | No funding |
| 2013 Chuan-Yi Lin 1 | Taiwan | prospective | 50 | 32 | 31 | 19 | 0 | 32 | No funding |
| 2013 Chuan-Yi Lin 2 | Taiwan | prospective | 50 | 32 | 40 | 10 | 0 | 32 | No funding |
| 2006 CHUN-NAN CHEN | Taiwan | prospective | 14 | 14 | 10 | 4 | 0 | 14 | Government |
| 2009 T Murofushi | Japan | prospective | 11 | 16 | 5 | 6 | 0 | 16 | No funding |
| 2009 Chen-Han Chou1 | Taiwan | prospective | 7 | 40 | 3 | 4 | 0 | 40 | Government |
| 2009 Chen-Han Chou2 | Taiwan | prospective | 7 | 40 | 4 | 3 | 0 | 40 | Government |
| 2010 Naoya Egami 1 | Japan | retrospective | 26 | 26 | 19 | 7 | 19 | 7 | Government |
| 2010 Naoya Egami 2 | Japan | retrospective | 7 | 7 | 4 | 3 | 4 | 3 | Government |
| 2011 Chi-Hsuan Huang 1 | Taiwan | prospective | 20 | 20 | 13 | 7 | 8 | 12 | Government |
| 2011 Chi-Hsuan Huang 2 | Taiwan | prospective | 20 | 20 | 5 | 15 | 0 | 20 | Government |
| 2011 Chi-Hsuan Huang 3 | Taiwan | prospective | 20 | 20 | 9 | 11 | 3 | 17 | Government |
| 2011 Chi-Hsuan Huang 4 | Taiwan | prospective | 20 | 20 | 5 | 15 | 0 | 20 | Government |
| 2013 Naoya Egami 1 | Japan | prospective | 114 | 94 | 57 | 57 | 22 | 72 | Government |
| 2013 Naoya Egami 2 | Japan | prospective | 22 | 94 | 21 | 1 | 22 | 74 | Government |
| 2012 Mei-Chun Lin 1 | Taiwan | prospective | 20 | 20 | 14 | 6 | 11 | 9 | No funding |
| 2012 Mei-Chun Lin 2 | Taiwan | prospective | 20 | 20 | 9 | 11 | 6 | 14 | No funding |
| 2011 Rachael L. Taylor 1 | Australia | prospective | 60 | 70 | 30 | 30 | 0 | 70 | Government |
| 2011 Rachael L. Taylor 2 | Australia | prospective | 60 | 70 | 24 | 36 | 0 | 70 | Government |
| 2006 Timmer Ferdinand C A | USA | retrospective | 82 | 24 | 11 | 71 | 0 | 24 | Government |
| 2002 Yi-Ho Young | Taiwan | prospective | 20 | 20 | 11 | 9 | 0 | 20 | Government |
| 2009 Bernhard Baier | Germany | prospective | 16 | 126 | 11 | 5 | 0 | 126 | No funding |
| 2013 Young Joon Seo | South Korea | prospective | 26 | 26 | 25 | 1 | 0 | 26 | No funding |
Figure 2Evaluation of the methodological quality of the included studies according to quality assessment diagnostic accuracy studies tool (QUADAS) criteri.
Figure 3Forest plot of the sensitivity of included studies, summary sensitivity and I2 statistic for heterogeneity.
Figure 4Forest plot of the specificity of included studies, summary specificity and I2 statistic for heterogeneity.
Figure 5Hierarchical summary receiver operating characteristic curves of VEMPs for detecting EH.
The red square represents the summary estimate sensitivity and specificity with 95% confidence region and 95% prediction region for the diagnosis value of EH by VEMPs. The size of the circles indicates the total number in each study.
Subgroup analysis for accuracy of VEMP for MD detection.
| Subgroup | N | Sensitivity | Specificity | DOR | AUC |
|---|---|---|---|---|---|
| Race | |||||
| Caucasian | 12 | 0.43 | 0.99 | 57.25 | 0.95 |
| Asian | 18 | 0.53 | 0.92 | 28.59 | 0.69 |
| Study design | |||||
| prospective | 26 | 0.52 | 0.95 | 50.54 | 0.81 |
| retrospective | 4 | 0.36 | 0.94 | 10.62 | 0.78 |
| Control | |||||
| health | 20 | 0.49 | 0.96 | 44.93 | 0.82 |
| patients | 10 | 0.48 | 0.94 | 35.37 | 0.78 |
| Attacks | |||||
| Yes | 30 | 0.49 | 0.95 | 38.44 | 0.78 |
| No | 2 | 0.44 | 1.00 | 30.43 | — |
| Methods | |||||
| Air conduct | 29 | 0.48 | 0.95 | 36.48 | 0.76 |
| Bone conduct | 3 | 0.54 | 1.00 | 59.46 | 0.99 |
| o-VEMP | 10 | 0.48 | 0.96 | 20.96 | 0.45 |
| c-VEMP | 27 | 0.49 | 0.95 | 39.36 | 0.81 |
| Click | 6 | 0.45 | 0.95 | 22.18 | 0.59 |
| Tone burst | 23 | 0.48 | 0.99 | 60.66 | 0.97 |
| Stage(c-VEMP) | |||||
| I | 4 | 0.47 | 0.85 | 4.01 | 0.64 |
| II | 5 | 0.49 | 0.86 | 16.32 | 0.65 |
| III | 5 | 0.46 | 0.86 | 11.15 | 0.31 |
| IV | 4 | 0.54 | 0.85 | 12.13 | 0.39 |
| Funding | |||||
| Government | 13 | 0.45 | 0.94 | 27.60 | 0.77 |
| No | 17 | 0.52 | 0.97 | 53.63 | 0.80 |
DOR = Diagnostic Odds Ratio; AUC = the area under the summary receiver operating characteristic curve
Figure 6Publication bias was evaluated by Deek’s funnel plots.