Association Between Platelet Count and Components of Metabolic Syndrome in Geriatric Taiwanese Males

Sex differences in the relationship between platelet count and type 2 diabetes risk in community-dwelling adults: Longitudinal findings over 14 years

AIMS

Emerging evidence suggests that platelet count predicts the development of type 2 diabetes; however, there is conflicting evidence concerning the relationship in men and women. This study aimed to assess the longitudinal association between platelet count and the incidence risk of type 2 diabetes.

MATERIALS AND METHODS

Among 10,030 participants, 7325 participants (3439 men and 3886 women) without diabetes were selected from the Korean Genome and Epidemiology Study. Platelet count quartiles were divided as follows: Q1 ≤219, Q2, 220-254, Q3, 255-296 and Q4 ≥297 (x103 /ml) for men and ≤232, 233-266, 267-305 and ≥306 (x103 /μL) for women. The hazard ratios (HRs) with 95% confidential intervals (CIs) for incident type 2 diabetes were calculated using multiple Cox proportional hazards regression models according to sex-specific platelet count quartiles.

RESULTS

During the biennial follow-up period from 2001 to 2002 to 2013-2014, 750 male participants (21.8%, 750/3439) and 730 female participants (18.8%, 730/3886) had newly developed type 2 diabetes. For women, compared to the reference first quartile, the HRs for incident type 2 diabetes in the second, third, and fourth platelet count quartiles were 1.20 (0.96-1.50), 1.21(0.97-1.51), and 1.47 (1.18-1.82) after adjusting for age, body mass index, smoking status, alcohol intake, physical activity, mean arterial blood pressure, family history of diabetes, and HOMA-IR. However, these positive relationships were not observed in men after adjusting for the same co-variables.

CONCLUSIONS

Platelet count was independently associated with an increased risk of incident type 2 diabetes only in women.

Role of platelet indices as diagnostic and predictive biomarkers for comorbidity of diabetes and metabolic syndrome in southern Ethiopia: A comparative cross-sectional study

BACKGROUND

Metabolic syndromes (MetS) and diabetes mellitus (DM) comorbidity is a growing major global public health problem with huge morbidity and mortality. It is a pro-inflammatory and prothrombotic disorder characterized by alteration of platelet indices and increased platelet activation, however, the tendency to use them in diagnosis is not yet fully evaluated in our context and there is limited evidence on the role of platelet indices in predicting and differentiating DM+MetS comorbidity in Ethiopia. Thus, this study aimed to evaluate platelet indices in HC, DM, and DM+MetS, and to determine their role in the prediction of DM+MetS comorbidity risk and the distinction between DM+MetS and DM or healthy persons in southwest Ethiopia.

METHOD AND MATERIALS

A comparative cross-sectional study was conducted in Wolkite University specialized hospital from March to August 2021. A total of 336 study participants (112 healthy controls (HC), 112 DM, 112 DM+MetS) was included in this study. Anthropmetric data were measured and the venous blood sample was collected to determine platelet indices, lipid profiles, and blood glucose levels. The SPSS version 21 statistical software was used to perform receiver operating curve (ROC), one-way ANOVA, and independent T-test analysis. The p-value for statistical significance was set at <0.05.

RESULT

In the present study, we found a significant difference in the mean value of PLT, MPV, and PDW between DM+MetS, DM, and HC. A statistically significant difference in the mean value of MPV and PDW was observed between HC and DM+MetS as well as DM and DM+MetS (p-value<0.001). At the cutoff value of 9.65fl with a sensitivity of 81.3% and a specificity of 67.9%, MPV differentiates DM+MetS from HC with an AUC of 0.859. MPV can differentiate DM+MetS from DM at a cutoff value of 10.05fl with sensitivity, specificity, and an AUC of 67.9%, 65.2%, and 0.675, respectively. At the cutoff value of 9.65fl with a sensitivity of 69.6% and a specificity of 67.9%, MPV differentiates DM from HC with an AUC of 0.747. The best platelet parameter identified in this study for predicting the presence of DM+MetS comorbidity was MPV (AUC=0.859; 95%CI=0.81-0.90).

CONCLUSION

In this study, a significant difference in the mean value of PLT, MPV, and PDW was found between DM+MetS, DM, and HC. The mean value of platelet indices showed significant increases in DM+MetS patients in comparison to HC and DM. MPV has been identified as a good potential marker to predict DM+MetS comorbidity and to differentiate DM+MetS comorbidity from the HC or DM. Our results show that MPV could be a good hematological marker to differentiate DM+MetS comorbidity from the HC or DM, and may offer supportive information for early diagnosis, prevention, and control. Thus, the findings of this study should be taken into account for the prevention and control of DM+MetS comorbidity.

Platelet mean volume, distribution width, and count in type 2 diabetes, impaired fasting glucose, and metabolic syndrome: a meta-analysis

BACKGROUND

Platelet activation contributes to cardiovascular disease (CVD), the main complication of type 2 diabetes mellitus (T2DM) and pre-diabetic conditions. Mean platelet volume is an easy-to-measure platelet parameter that has been associated with CVD. We sought to assess mean platelet volume, platelet distribution width, and platelet count in T2DM, impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and metabolic syndrome.

METHODS

Web-based literature search (PubMed, EMBASE, and Web of Science) of studies published in English through June 2014 was performed to select case-control and cross-sectional studies that reported data on mean platelet volume, platelet distribution width, or platelet count in cases (subjects with T2DM, IFG, IGT, or metabolic syndrome) and noncases. Descriptive and quantitative information was extracted, and within-study standardized mean difference was estimated from means and standard deviations. Standardized mean differences across studies were synthesized using a random random-effects model, and subgroup analyses were performed on pre-specified study-level characteristics.

RESULTS

Thirty-nine studies were included. Compared with controls, mean platelet volume was significantly higher in T2DM (standardized mean difference, 95% confidence interval: 0.70, 0.50-0.91; N = 24,245), IFG (0.14, 0.02-0.26; N = 17,389) but not in metabolic syndrome (0.15, -0.24 to 0.55; N = 14,990). Platelet distribution width was wider in T2DM (0.93, 0.09-1.76; N = 471). Platelet count resulted higher in IFG (0.18, 0.12-0.24; N = 3960) and metabolic syndrome (0.39, 0.01-0.78; N = 4070). Only two studies included IGT.

CONCLUSIONS

Available data suggest that T2DM subjects tend to have higher mean platelet volume and platelet distribution width values, but nondifferent platelet count as compared with subjects without T2DM. Whether and how these morphometric changes contribute to CVD of T2DM or can be used as CVD biomarker awaits further investigation.

Using hematogram model to predict future metabolic syndrome in elderly: a 4-year longitudinal study

OBJECTIVES

The metabolic syndrome (MetS) is proposed to predict future occurrence of cardiovascular diseases and diabetes. There are some other "non-traditional" risk factors such as hematogram components that are also related to the same endpoints as MetS. In this four-year longitudinal study, we used hematogram components to build models for predicting future occurrence of MetS in older men and women separately.

METHODS

Subjects above 65 years without MetS and related diseases were enrolled. All subjects were followed up until they developed MetS or until up to four years from the day of entry, whichever was earlier.

RESULTS

Among the 4539 study participants, 1327 developed MetS. Models were built for men and women separately and the areas under the receiver operation curves were significant. The Kaplan-Meier plot showed that the models could predict future MetS. Finally, Cox regression analysis showed that the hematogram model was correlated to future MetS with hazard ratios of 1.567 and 1.738 in men and women, respectively.

CONCLUSION

Our hematogram models could significantly predict future MetS in elderly and might be more practical and convenient for daily clinical practice.