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The biomarkers associated with non-dipper pattern in patients with type 2 diabetes with hypertension
Viorel Manea1, Daniel-Corneliu Leucuţa2, Călin Pop1,3
1Department of Cardiology, "Constantin Opriş" Emergency County Clinical Hospital, Baia Mare, Romania.
Insights
Non-dipper blood pressure patterns in type 2 diabetes and hypertension are linked to poor outcomes. The triglyceride-to-glucose ratio effectively distinguishes dippers from non-dippers, aiding in risk stratification.
Area of Science:
- Endocrinology
- Cardiology
- Clinical Biomarkers
Background:
- The non-dipper blood pressure pattern affects approximately 50% of patients with type 2 diabetes (T2D) and hypertension.
- This pattern is associated with increased cardiovascular complications and a poorer prognosis.
Purpose of the Study:
- To identify simple biomarkers for classifying dipper and non-dipper individuals with T2D and hypertension.
- To evaluate the discriminative capacity of these biomarkers.
Main Methods:
- 138 patients with T2D and hypertension underwent 24-hour ambulatory blood pressure monitoring (ABPM).
- Blood samples were analyzed for complete blood count (CBC) and various biomarkers.
- The area under the receiver operating characteristic curve (AUC) was used to assess biomarker performance.
Main Results:
- The triglyceride-to-hemoglobin A1c (HbA1c) ratio and the triglyceride-to-glucose ratio were statistically significant differentiators.
- Dippers exhibited higher values for both significant ratios compared to non-dippers.
- The triglyceride-to-glucose ratio demonstrated the highest discriminative capacity (AUC = 0.774).
Conclusions:
- The triglyceride-to-glucose ratio is a promising, simple biomarker for classifying dipper and non-dipper status in T2D and hypertension patients.
- This biomarker holds potential for risk stratification and personalized treatment strategies.
Background And Aims:
The non-dipper pattern is present in about 50 percent of patients with type 2 diabetes (T2D) and hypertension, a status associated with more frequent cardiovascular complications and restrained prognosis. This study aimed to identify simple biomarkers that can be used for the classification of dipper and non-dipper individuals with type 2 diabetes and hypertension.
Method:
138 consecutive patients with type 2 diabetes mellitus (DM) and hypertension underwent 24-hour ambulatory blood pressure monitoring (ABPM), 54 (39.1%) dippers and 84 (60.9%) non-dippers; CBC and determinations of different biomarkers, as well as their ratio was also performed, for comparing the two dipper profiles. The different dipper profiles were established by ABPM, which highlights the mean arterial pressure (MAP), the mean heart rate (MHR), and the mean pulse pressure (MPP). The area under the receiver operating characteristic curve (AUC) was used to evaluate the ability of biomarkers to differentiate dippers from non-dippers.
Results:
The study included 54 dipper and 84 non-dipper patients. The median age was 64 years (interquartile range 58-74), ranging from 24 to 85 years. The comparison between dipper and non-dipper in patients with type 2 diabetes and hypertension concerning different biomarkers found only two that were statistically significant: triglycerides to hemoglobin A1c (HbA1c) ratio and triglycerides to glucose ratio. For both biomarkers, the dippers had higher values than non-dippers. The best AUCs were found for triglycerides (Trig) to glucose ratio of 0.774 (95% confidence interval 0.601 - 0.92), statistically significant, followed at a distance by lymphocytes, platelets-lymphocytes ratio (PLR), platelet distribution width (PDW-SD), mean platelet volume (MPV) /Lymphocytes, and others, none of them being statistically significant.
Conclusions:
This study offers valuable insights into the classification of dipper and non-dipper individuals with type 2 diabetes and hypertension using several biomarkers. Notably, the triglyceride-to-glucose ratio appeared as a significant marker with considerable discriminative capacity, indicating its potential therapeutic value in risk stratification and personalized treatment strategies.
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