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Platelets. 2014 Feb 10. [Epub ahead of print]

Platelet count can predict metabolic syndrome in older women.

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  • 1Department of Pathology, Cardinal Tien Hospital , New Taipei City, Taiwan , R.O.C .

Abstract

Abstract Platelet count (PC) has been found to be related to the metabolic syndrome (MetS). However, the role of PC on MetS remained unclear. In order to evaluate the relationship between PC and MetS components cross-sectionally and determine the optimal cutoff PCs for predicting the subsequent risk of MetS development with sex specificity, two stages included cross-sectional (stage 1) and prospective (stage 2) cohort study were conducted. Stage 1 involved 10 579 subjects aged ≥60 years, of which 7718 subjects advanced to stage 2 with a mean 3.8 year follow-up were enrolled. The MetS components and PC were determined. The PC cutoffs for higher chances of developing MetS in stage 1 were calculated using receiver operating characteristic (ROC) curve analyses. In stage 2, non-MetS subjects were classified into high-PC (HPC) and low-PC (LPC) groups according to the cutoff values from stage 1. We examined the difference of future MetS incidence and calculated the odds ratio (OR) between these two groups. In stage 1, multiple regression showed that age and triglyceride (both sexes) and waist circumstance and high-density lipoprotein cholesterol (only women) were independently correlated with PC. There was significant difference in the area under the ROC curve (AUC) only of HPC women, which exceeded the standard curve (AUC = 0.542, p < 0.001), with a cutoff PC of 223 × 103/μl. HPC women had an OR of 1.287 (95% confidence interval: 1.135-1.461) of developing MetS after 3.8 years. The Kaplan-Meier curve demonstrated a higher incidence of MetS development in HPC women. In conclusion, our results suggest that PC was associated with MetS with sex effects. Most of the MetS components were independent factors for increasing PC, and the risk for subsequent development of MetS was noted when PC >223 × 103/μl in elderly women.

PMID:
24512307
[PubMed - as supplied by publisher]
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