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Journal of Diabetes & Metabolic Disorders

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01-06-2021 | Research article

Validity of continuous metabolic syndrome score for predicting metabolic syndrome; a systematic review and meta-analysis

Authors: Maryam Khazdouz, Motahareh Hasani, Sanaz Mehranfar, Hanieh-Sadat Ejtahed, Shirin Djalalinia, Armita Mahdavi Gorabi, Mohammad Esmaeili-Abdar, Shahrokh Karbalahi Saleh, Seyed Masoud Arzaghi, Hoda Zahedi, Amir Kasaeian, Mostafa Qorbani

Published in: Journal of Diabetes & Metabolic Disorders | Issue 1/2021

Abstract

Background

Nowadays, use of continuous metabolic syndrome (cMetS) score has been suggested to improve recognition of metabolic syndrome (MetS). The aim of this study was to evaluate the validity of cMetS scores for predicting MetS.

Methods

We searched the electronic databases included MEDLINE/PubMed, Embase, ISI Web of Science, and Scopus from 1 January 1980 to 30 September 2020. Observational studies on participants with different cMetS scores were included in this meta-analysis. The sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR) and diagnostic odds ratio (DOR) with 95% CI were calculated.

Results

Ten studies involving a total of 25,073 participants were included. All studies had cross-sectional design. The pooled sensitivity and specificity of cMetS scores for predicting MetS were 0.90 (95% CI: 0.83 to 0.95) and 0.86 (95% CI: 0.83 to 0.89), respectively. Moreover, cMetS scores had the pooled LR+ of 6.5 (95% CI: 5.0 to 8.6), and a pooled (LR-) of 0.11 (95% CI: 0.063 to 0.21). The pooled DOR of cMetS scores to predict MetS were 57 (95% CI: 26 to 127).

Conclusions

The high sensitivity and specificity of cMetS scores indicates that it has a high accuracy to predict the risk of MetS. Furthermore, the cMetS scores has a good ability to rule out healthy people.

Study registration

This study was registered as PROSPERO CRD42020157273.

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Title: Validity of continuous metabolic syndrome score for predicting metabolic syndrome; a systematic review and meta-analysis
Authors: Maryam Khazdouz
Motahareh Hasani
Sanaz Mehranfar
Hanieh-Sadat Ejtahed
Shirin Djalalinia
Armita Mahdavi Gorabi
Mohammad Esmaeili-Abdar
Shahrokh Karbalahi Saleh
Seyed Masoud Arzaghi
Hoda Zahedi
Amir Kasaeian
Mostafa Qorbani
Publication date: 01-06-2021
Publisher: Springer International Publishing
Published in: Journal of Diabetes & Metabolic Disorders / Issue 1/2021
Electronic ISSN: 2251-6581
DOI: https://doi.org/10.1007/s40200-021-00771-w

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Background

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Results

Conclusions

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