Predicting metabolic syndrome by using hematogram models in elderly women

Development and Validation of a Simple Risk Model for Predicting Metabolic Syndrome (MetS) in Midlife: A Cohort Study

Purpose

To develop and validate a simple risk model for predicting metabolic syndrome in midlife using a prospective cohort data.

Design

Prospective cohort study.

Participants

A total of 7626 members of the 1958 British birth cohort (individuals born in the first week of March 1958) participated in the biomedical survey at age 45 and have completed information on metabolic syndrome.

Methods

Variables utilised were obtained prospectively at birth, 7, 16, 23 and 45 years. Multivariable logistic regression was used to develop a total of ten (10) MetS risk prediction models taking the life course approach. Measures of discrimination and calibration were used to evaluate the performance of the models. A pragmatic criteria developed was used to select one model with the most potential to be useful. The internal validity (overfitting) of the selected model was assessed using bootstrap technique of Stata.

Main Outcome Measure

Metabolic syndrome was defined based on the NCEP-ATP III clinical criteria.

Results

There is high prevalence of MetS among the cohort members (19.6%), with males having higher risk as compared to females (22.8% vs 16.4%, P < 0.001). Individuals with MetS are more likely to have higher levels of HbA1c and low HDL-cholesterol. Similarly, regarding the individual components of MetS, male cohort members are more likely to have higher levels of glycaemia (HbA1c), BP and serum triglycerides. In contrast, female cohort members have lower levels of HDL-cholesterol and higher levels of waist circumference. Furthermore, a total of ten (10) MetS risk prediction models were developed taking the life course approach. Of these, one model with the most potential to be applied in practical setting was selected. The model has good accuracy (AUROC 0.91 (0.90, 0.92)), is well calibrated (Hosmer-Lemeshow 6.47 (0.595)) and has good internal validity.

Conclusion

Early life factors could be included in a risk model to predict MetS in midlife. The developed model has been shown to be accurate and has good internal validity. Therefore, interventions targeting socioeconomic inequality could help in the wider prevention of MetS. However, the validity of the developed model needs to be further established in an external population.

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

BACKGROUND AND OBJECTIVES

Leukocyte and platelet have been found to be associated with metabolic syndrome (MetS). We aimed to determine the usefulness of a novel marker named white blood cell count to mean platelet volume ratio (WMR) for predicting outcomes of non-ST elevation acute coronary syndrome (NSTE-ACS) with or without MetS.

SUBJECTS AND METHODS

A total of 331 NSTE-ACS individuals (60±12.5 years, 57.4% male) were enrolled and followed for a median of 24 months. MetS was identified using the National Cholesterol Education Program Adult Treatment Panel III criteria.

RESULTS

Patients were divided into two groups: high WMR (WMR≥720) and low WMR (WMR<720). Major adverse cardiovascular events (MACE) and MetS rates were significantly greater in the higher WMR group compared to those in the low WMR group (MACE: 14.3% vs. 25%, p=0.014; MetS: 50.9% vs. 75%, p<0.001). MetS was diagnosed in 62.2% of patients. MACE incidence in patients with or without MetS was comparable (p=0.737). Among MetS individuals, patients in the high WMR group had more MACE than the low WMR group (11.2% vs. 26.5%, p=0.007). However, MACE was comparable among non-MetS individuals (p=0.681). In multivariable Cox regression analysis, hazard ratios (HR) of MACE incidence for high-WMR in MetS individuals was 2.616 (95% confidence interval: 1.282-5.339, p=0.008). However, HR of MACE incidence for high WMR in non-MetS individuals was not significant.

CONCLUSION

Among NSTE-ACS patients without revascularization therapy, elevated admission WMR was associated with an increased risk of developing composite MACE in MetS individuals but not in non-MetS patients.

Platelet count can predict metabolic syndrome in older women

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 × 10(3)/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 × 10(3)/μl in elderly women.