Predicting metabolic syndrome by using hematogram models in elderly women

Abstract

Our findings have shown that all the three hematogram parameters are related to MetS. The results not only shed light on the complex relationships, but also demonstrate a common and easy model to aid clinicians to be more aware of the occurrence of MetS.

White Blood Cell Count to Mean Platelet Volume Ratio Is a Prognostic Factor in Patients with Non-ST Elevation Acute Coronary Syndrome with or without Metabolic Syndrome

“…The majority of cross-sectional studies have demonstrated that increased platelet count is associated with MetS patients. 19) 20) 22) 23) In a meta-analysis, platelet count in MetS patients was higher than that in non-MetS patients. 24) In contrast, in a cross-sectional investigation, there was no difference in platelet count between MetS and non-MetS individuals.…”

“…Regarding the relationship between WBC count and the presence of MetS, some studies have been conducted to assess this association. In some cross-sectional studies, 18) 19) 20) it has been found that WBC count in MetS patients is significantly higher than that in non-MetS ones, indicating that inflammation-based mechanism is involved in the MetS pathogenesis. However, Kutlucan et al 21) have found no difference regarding WBC count levels between patients with MetS and those without MetS.…”

Risk models and scores for metabolic syndrome: a systematic review

“…Consequently, a formal meta-analysis was precluded due to the heterogeneity of data particularly regarding the diverse demographics of the studied participants and different components of the scores. Surprisingly, the observed incidence/prevalence of MetS at the end of the study is not reported in nearly a third (twenty-nine per cent) of the studies [24,28,31,37,41,42]. For those that reported it, the prevalence/ incidence of MetS ranged from as little as one per cent to as high as thirty-seven per cent (median is thirteen per cent).…”

“…Of these 24 papers, 22 report about the development of one or more risk model or score [24][25][26][27][28][29][30][31][32][33][34][35]37,38,[40][41][42][43][44][45][46][47], and 2 studies report about the development and external validation of one or more risk model or scores on an external population [36,39].Overall, the 24 studies reported 40 models, out of which 24 models were selected for full data extraction. The rest (16 models) were not selected, either because they were judged to be minimally different from the reported ones or they were not the preferred models by the authors or they were significantly deficient in details or statistical reporting.…”

“…Regarding the age of the sample, more risk scores were reported in adults than in children or adolescent. Of the 24 included models, 15 risk models were focused on adult subjects [24,25,29,[31][32][33][34][35][36][37][38][41][42][43][44]47], while 8 targets children and adolescents [26][27][28]30,39,40,45,46]. Table 4.0 shows the details of the components of the included 24 risk models or scores as well as their statistical properties-which includes (where available) their "sensitivity, specificity, discrimination, calibration, positive and negative predictive values, AUROC".…”