Links between High-Sensitivity C-Reactive Protein and Pulse Wave Analysis in Middle-Aged Patients with Hypertension and High Normal Blood Pressure.
Ioana M MozoșDaniela JianuCristina GugDana Liana StoianPublished in: Disease markers (2019)
Arterial stiffness and arterial age provide valuable prognostic cardiovascular information. The present study aimed at assessing the levels of vitamin D, high-sensitivity C-reactive protein (hsCRP), low-density lipoprotein cholesterol (LDL), and oxidized LDL (oxLDL) in a group of middle-aged hypertensive patients and their relationship with pulse wave velocity (PWV), central blood pressure, and early arterial aging (EAA), respectively. A total of 56 patients, aged 48 ± 6 years, 57% males, with hypertension and high normal blood pressure (HNBP), were investigated using a Mobile-O-Graph, to assess central and peripheral blood pressure, PWV, and arterial age. Additionally, hsCRP, LDL, oxLDL, and 25-hydroxy vitamin D3 were assessed. PWV, 25-hydroxy vitamin D3, hsCRP, oxLDL, and LDL levels were 7.26 ± 0.69 m/s, 25.99 ± 11.17 microg/l, 0.48 ± 0.44 mg/dl, 261.37 ± 421 ng/ml, and 145.73 ± 39.53 mg/dl, respectively. Significant correlations were obtained between oxLDL and pulse pressure amplification (rS = -0.347, p = 0.028) and between hsCRP and LDL levels with PWV and EAA, respectively. ROC curve analysis revealed that hsCRP is a sensitive and specific predictor of EAA and increased PWV values. Concluding, vitamin D deficiency and increased hsCRP and LDL values are very common, and high oxidized LDL is related to pulse pressure amplification in patients with elevated blood pressure. Vitamin D level and high-sensitivity C-reactive protein and LDL provide valuable information in middle-aged hypertensive and HNBP patients related to arterial stiffness and early arterial aging, but only hsCRP is a sensitive predictor of EAA and PWV.
Keyphrases
- blood pressure
- hypertensive patients
- low density lipoprotein
- middle aged
- heart rate
- end stage renal disease
- chronic kidney disease
- ejection fraction
- newly diagnosed
- blood glucose
- prognostic factors
- healthcare
- type diabetes
- machine learning
- insulin resistance
- single cell
- adipose tissue
- deep learning
- label free
- single molecule