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Comparing differences and correlation between 24-hour ambulatory blood pressure and office blood pressure monitoring in patients with untreated hypertension

OBJECTIVE: We assessed differences and correlations between 24-hour ambulatory blood pressure (ABP) and office blood pressure (OBP) monitoring. METHODS: We conducted an observational study among 85 untreated patients with essential hypertension and measured 24-hour ABP, OBP, target organ damage (TOD...

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Detalles Bibliográficos
Autores principales: Zhang, Zhenhong, Wang, Shunyin, Yan, Junru, Xu, Zhiwen, Liang, Dongliang, Liu, Baohua, Liang, Junjie, Chen, Mingjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8252350/
https://www.ncbi.nlm.nih.gov/pubmed/34187215
http://dx.doi.org/10.1177/03000605211016144
Descripción
Sumario:OBJECTIVE: We assessed differences and correlations between 24-hour ambulatory blood pressure (ABP) and office blood pressure (OBP) monitoring. METHODS: We conducted an observational study among 85 untreated patients with essential hypertension and measured 24-hour ABP, OBP, target organ damage (TOD) markers, and metabolism indexes. Variance analysis and the Pearson method were used to compare differences and correlation between the two methods. The Spearman or Pearson method was applied to compare the correlation between TOD markers, blood pressure index, and metabolism index. Linear regression analysis was applied to estimate the quantitative relationship between the blood pressure index and TOD markers. RESULTS: There were significant differences in the mean and variance of systolic blood pressure (SBP) and diastolic blood pressure and a positive correlation between ABP and OBP. Correlations between the left ventricular mass index (LVMI) and average ambulatory SBP, daytime ambulatory SBP, nighttime ambulatory SBP, and fasting blood glucose were significant. Correlations between left intima-media thickness (IMT) and average ambulatory SBP, nighttime ambulatory SBP, right IMT, and nighttime ambulatory SBP were significant. In linear regression analysis of the LVMI (y) and ambulatory SBP (x), the equation was expressed as y = 0.637*x. CONCLUSION: Nighttime ambulatory SBP may be an optimal predictor of TOD.