Red Blood Cell Parameters and Their Correlation with Glycemic Control Among Type 2 Diabetic Adult Patients in Eastern Ethiopia: A Comparative Cross-Sectional Study

Arkew, Mesay; Asmerom, Haftu; Tesfa, Tewodros; Tsegaye, Setegn; Gemechu, Kabtamu; Bete, Tilahun; Haile, Kassahun

doi:10.2147/dmso.s386093

Cited by 16 publications

(17 citation statements)

References 33 publications

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“…Despite the differences in group means being statistically significant, there may be considerable overlap between individual results in the disease and control groups, impacting the meaningfulness of test results. This is particularly noteworthy for the studies of Arkew et al and Jabeen et al, 1 , 5 , 7 where the differences in group means are ~1 fL, despite the statistically significant difference between the two cohorts. Without a rigorous control of the preanalytical and analytical phase variables, individual patient results may be difficult or impossible to interpret.…”

Section: Dear Editormentioning

confidence: 87%

“…Arkew et al have published an article entitled “Red Blood Cell Parameters and Their Correlation with Glycemic Control Among Type 2 Diabetic Adult Patients in Eastern Ethiopia: A Comparative Cross-Sectional Study” in Diabetes, Metabolic Syndrome and Obesity. 1 I congratulate the authors on their work, which adds to the already extensive literature on the use of the red blood cell distribution width (RDW) as a surrogate biomarker of systemic inflammation in the setting of type 2 diabetes mellitus (T2DM). I would like to add some technical details about the RDW which would be of interest to the readership of the journal who are considering the use of the RDW for this or related purposes.…”

Section: Dear Editormentioning

confidence: 99%

“…To assess the degree to which these issues have been addressed in the study of Arkew et al and the other studies cited in their paper, I extracted the relevant data which are summarized in Table 1 . 1 , 3–8 The preanalytical variables that may impact the RDW were largely unreported, with time between phlebotomy and analysis reported in 1/7 studies and no reporting of storage temperature and transport conditions in any of the studies. It is not surprising that these variables are underreported, since guidelines such as the Standards for Reporting of Diagnostic Accuracy Studies (STARD) do not mandate the reporting of preanalytical and analytical phase variables, despite their obvious importance in the outcomes of many laboratory tests, including the RDW.…”

Section: Dear Editormentioning

confidence: 99%

“…Daves et al have reported that time delays as short as 3 hours have resulted in an erroneous RDW result. 10 A lack of control for these preanalytical phase variables may account in part for the different cutoffs for the RDW and the lack of statistical significance in the study of Adane et al 3 Due to the lack of standardization of the RDW across different instrumentation platforms, the wide variety of instruments used in these studies, including devices manufactured by Sysmex (Kobe, Japan), 3 , 6 Abbott (Chicago, IL, USA), 4 Beckman Coulter (Brea, CA, USA), 1 , 5 and Horiba (Kyoto, Japan), 7 may add additional biases.…”

Section: Dear Editormentioning

confidence: 99%

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Red Blood Cell Distribution Width as a Biomarker in Type 2 Diabetes Mellitus: Technical Notes [Letter]

Frater¹

2023

DMSO

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Section: Dear Editormentioning

confidence: 87%

Section: Dear Editormentioning

confidence: 99%

Section: Dear Editormentioning

confidence: 99%

Section: Dear Editormentioning

confidence: 99%

See 2 more Smart Citations

Red Blood Cell Distribution Width as a Biomarker in Type 2 Diabetes Mellitus: Technical Notes [Letter]

Frater¹

2023

DMSO

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“…Some studies showed that hyperglycemia reduced erythrocyte deformability and shortened lifespan, which seemed to cause changes in RDW levels. 27 , 28 However, there are no studies on the relationship between RDW levels and FBG in patients with ACS. Therefore, we investigated the relationship between RDW and FBG or HbA1c in ACS patients but not find a correlation between RDW and HbA1c.…”

Section: Discussionmentioning

confidence: 99%

Relation of Red Cell Distribution Width to Glucose Metabolism and Adverse Long-Term Prognosis in Patients with Acute Coronary Syndrome

Xiong¹,

Xu²,

Shou³

et al. 2023

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Introduction Red cell distribution width (RDW) reflects the heterogeneity of red blood cell size. However, few studies examined whether RDW is related to glucose metabolism indices, such as fasting blood glucose (FBG) and hemoglobin A1c (HbA1c), diabetic mellitus (DM) state or long-term outcomes of acute coronary syndrome (ACS) patients. Methods and Results A total of 448 consecutive patients with ACS were enrolled in this study. All patients were followed up for major cardiovascular adverse events (MACEs), and the mean follow-up was 952 days. Linear regression analysis showed that RDW inversely correlated with FBG but not HbA1c or DM. Kaplan-Meier survival curve analysis demonstrated that higher RDW levels were significantly positively associated with MACEs in the whole study population and the ACS patients with high FBG but not the low FBG group. Cox multivariate regression analysis revealed the independent function of RDW on MACEs in all ACS patients and ACS patients with high FBG. The receiver operating characteristic (ROC) curve demonstrated the optimal cutoff value of RDW for MACEs. Conclusion We first reported that higher RDW was associated with decreased FBG but not HbA1c or DM and an increased risk of MACEs in patients with ACS. This relationship was also found in ACS patients with higher FBG levels but not in ACS patients with lower FBG.

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Fingerprinting hyperglycemia using predictive modelling approach based on low-cost routine CBC and CRP diagnostics

Tahir,

Asghar,

Shafiq

et al. 2024

Sci Rep

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Hyperglycemia is an outcome of dysregulated glucose homeostasis in the human body and may induce chronic elevation of blood glucose levels. Lifestyle factors such as overnutrition, physical inactivity, and psychosocials coupled with systemic low-grade inflammation have a strong negative impact on glucose homeostasis, in particular, insulin sensitivity. Together, these factors contribute to the pathophysiology of diabetes (DM) and expanding landscape of its prevalence regionally and globally. The rapid rise in the prevalence of type 2 diabetes, therefore, underscores the need for its early diagnosis and treatment. In this work, we have evaluated the discriminatory capacity of different diagnostic markers including inflammatory biomolecules and RBC (Red Blood Cell) indices in predicting the risk of hyperglycemia and borderline hyperglycemia. For that, 208,137 clinical diagnostic entries obtained over five years from Chugtai Labs, Pakistan, were retrospectively evaluated. The dataset included HbA1c (n = 142,011), complete blood count (CBC, n = 84,263), fasting blood glucose (FBG, n = 35,363), and C-reactive protein (CRP, n = 9035) tests. Our results provide four glycemic predictive models for two cohorts HbA1c and FBG) each having an overall predictive accuracy of more than 80% (p-value < 0.0001). Next, multivariate analysis (MANOVA) followed by univariate analysis (ANOVA) was employed to identify predictors with significant discriminatory capacity for different levels of glycemia. We show that the interplay between inflammation, hyperglycemic-induced derangements in RBC indices, and altered glucose homeostasis could be employed for prognosticating hyperglycemic outcomes. Our results then conclude a glycemic predictor with high sensitivity and specificity, employing inflammatory markers coupled with RBC indices, to predict glycemic outcomes (ROC p-value < 0.0001). Taken together, this study outlines a predictor of glycemic outcomes which could assist as a prophylactic intervention in predicting the early onset of hyperglycemia and borderline hyperglycemia.

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Red Blood Cell Parameters and Their Correlation with Glycemic Control Among Type 2 Diabetic Adult Patients in Eastern Ethiopia: A Comparative Cross-Sectional Study

Cited by 16 publications

References 33 publications

Red Blood Cell Distribution Width as a Biomarker in Type 2 Diabetes Mellitus: Technical Notes [Letter]

Red Blood Cell Distribution Width as a Biomarker in Type 2 Diabetes Mellitus: Technical Notes [Letter]

Relation of Red Cell Distribution Width to Glucose Metabolism and Adverse Long-Term Prognosis in Patients with Acute Coronary Syndrome

Fingerprinting hyperglycemia using predictive modelling approach based on low-cost routine CBC and CRP diagnostics

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