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Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Diagnostic value of visceral adiposity index in chronic kidney disease: a meta-analysis
Tingting Fang1, Qiuling Zhang2, Yanmei Wang3
1School of Public Health, Hangzhou Normal University, Hangzhou, 311121, Zhejiang Province, China.
Insights
The visceral adiposity index (VAI) shows promise as a tool for predicting chronic kidney disease (CKD). This meta-analysis suggests VAI can aid in CKD detection, though further validation is recommended.
Area of Science:
- Nephrology and Endocrinology
- Diagnostic Accuracy Studies
Background:
- Inconsistencies exist regarding the predictive value of the visceral adiposity index (VAI) for chronic kidney disease (CKD).
- The diagnostic utility of VAI for CKD requires further clarification.
Approach:
- A systematic meta-analysis was conducted, searching PubMed, Embase, Web of Science, and Cochrane databases up to November 2022.
- Seven studies with 65,504 participants were included, with quality assessed using QUADAS-2.
- Statistical analyses, including heterogeneity and publication bias assessments, were performed using Review Manager, Meta-disc, and STATA.
Key Points:
- The pooled analysis yielded a sensitivity of 0.67, specificity of 0.75, and an AUC of 0.77.
- The positive likelihood ratio was 2.7 and the negative likelihood ratio was 0.44.
- Mean age of participants was identified as a potential source of heterogeneity.
Conclusions:
- The visceral adiposity index (VAI) demonstrates potential as a valuable biomarker for predicting and detecting chronic kidney disease (CKD).
- Further research is warranted to validate these findings and establish VAI's role in clinical practice.
Aims:
Several studies have revealed inconsistencies about the predictive properties of visceral adiposity index (VAI) in identifying chronic kidney disease (CKD). To date, it is unclear whether the VAI is a valuable diagnostic tool for CKD. This study intended to evaluate the predictive properties of the VAI in identifying CKD.
Methods:
The PubMed, Embase, Web of Science, and Cochrane databases were searched for all studies that met our criteria from the earliest available article until November 2022. Articles were assessed for quality using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The heterogeneity was explored with the Cochran Q test and I2 test. Publication bias was detected using Deek's Funnel plot. Review Manager 5.3, Meta-disc 1.4, and STATA 15.0 were used for our study.
Results:
Seven studies involving 65,504 participants met our selection criteria and were therefore included in the analysis. Pooled sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and area under the curve (AUC) were 0.67 (95%CI: 0.54-0.77), 0.75 (95%CI: 0.65-0.83), 2.7 (95%CI: 1.7-4.2), 0.44 (95%CI: 0.29-0.66), 6 (95%CI:3.00-14.00) and 0.77 (95%CI: 0.74-0.81), respectively. Subgroup analysis indicated that mean age of subjects was the potential source of heterogeneity. The Fagan diagram found that the predictive properties of CKD were 73% when the pretest probability was set to 50%.
Conclusions:
The VAI is a valuable agent in predicting CKD and may be helpful in the detection of CKD. More studies are needed for further validation.
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