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Predicting metabolic syndrome by using hematogram models in elderly women
Haixia Liu1, Chun-Hsien Hsu, Jiunn-Diann Lin
1Department of Endocrinology and Metabolism, The 2nd Affiliated Hospital of Dalian Medical University , Dalian , China .
Platelets
|March 29, 2013
Summary
Metabolic syndrome (MetS) can be predicted using routine blood tests. White blood cell (WBC) count, hemoglobin (Hb), and platelet (PLT) levels are associated with MetS, offering a simple predictive model.
Area of Science:
- Clinical Medicine
- Biochemistry
- Hematology
Background:
- Low-grade inflammation is a key factor in metabolic syndrome (MetS).
- White blood cell (WBC) count is a known inflammatory marker linked to MetS.
- Hemoglobin (Hb) and platelet (PLT) counts also show associations with MetS.
Purpose of the Study:
- To develop predictive models for MetS using hematogram components.
- To enable MetS prediction via low-cost, routine laboratory tests.
- To further elucidate the relationship between low-grade inflammation and MetS.
Main Methods:
- Analysis of 13,132 female subjects aged over 65 from a health screening database (1999-2008).
- Exclusion of participants on medication for hypertension, hyperlipidemia, or diabetes.
- Development and evaluation of predictive models based on hematogram parameters.
Main Results:
- Hematogram parameters (WBC, Hb, PLT) and MetS components were elevated in the MetS group.
- WBC, Hb, and PLT were correlated with MetS components, except for Hb and HDL-C.
- A model combining PLT, Hb, and WBC demonstrated the highest predictive capability (AUC=0.631).
Conclusions:
- All three hematogram parameters (WBC, Hb, PLT) are significantly related to MetS.
- These findings support a simple, accessible model for clinicians to identify MetS risk.
- The study enhances understanding of inflammation's role in MetS.
