SPC365

Comparison Between Office Blood Pressure and Ambulatory Blood Pressure Monitoring in Predicting Cardiovascular Events

Session: SESSÃO DE POSTERS 09 - OBESIDADE E HIPERTENSÃO: VELHOS CONHECIDOS, NOVAS FERRAMENTAS
Speaker: Simão De Almeida Carvalho

Congress: CPC 2025
Topic: I. Hypertension
Theme: 27. Hypertension
Subtheme: 27.6 Hypertension – Clinical
Session Type: Cartazes
FP Number: ---
Authors: Simão De Almeida Carvalho; Carlos Costa; Inês Cruz; Tiago Aguiar; Adriana Pacheco; Andreia Fernandes; Ana Briosa Neves; José Mesquita Bastos
<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><strong><span style="color:black">Introduction:</span></strong></span></span></span></p>

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif">Hypertension is a major risk factor for cardiovascular disease. While office blood pressure (BP) is commonly used in practice, it may fail to capture BP variability and nocturnal patterns, which are crucial for assessing cardiovascular risk.</span></span></p>

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<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><strong><span style="color:black">Objective:</span></strong></span></span></span></p>

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><span style="color:black">This study compares the ability of office BP and Ambulatory Blood Pressure Monitoring (ABPM) to predict cardiovascular events. </span></span></span></span></p>

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<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><strong><span style="color:black">Methods:</span></strong><br />
<span style="color:black">A single-center cross-sectional study of hypertensive patients undergoing ABPM. Parametric tests analyzed variables with normal distribution, using Independent-Samples T Test, Chi-square, logistic and ROC analysis for model comparison in SPSS.</span></span></span></span></p>

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><span style="color:black">Patients were classified by office BP, ABPM, and anti-hypertensive medications into Ambulatory Resistant Hypertension (ARH), Ambulatory Non-Resistant Hypertension (ANRH), White Coat Uncontrolled Resistant Hypertension (WCURH), and Controlled Hypertension (CH). The composite endpoint included stroke, acute coronary syndrome (ACS), or heart failure (HF) hospitalization.</span></span></span></span></p>

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<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><strong><span style="color:black">Results:</span></strong></span></span></span></p>

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><span style="color:black">The study included 958 patients (mean age: 58.7 &plusmn; 11.5 years; 51.3% female), followed for 11.9 &plusmn; 5.5 years. Cardiovascular risk factors included mean BMI of 28.2 &plusmn; 4.7 kg/m&sup2;, diabetes (29.2%), smoking history (35.3%), and dyslipidemia (68.6%). Office BP showed mean systolic BP of 153.1 &plusmn; 22.2 mmHg and pulse pressure (PP) of 58.8 &plusmn; 18.2 mmHg. ABPM showed 24-hour systolic BP of 131.5 &plusmn; 15.8 mmHg and PP of 52.1 &plusmn; 11.0 mmHg, with nocturnal dipping&nbsp;in 52.1%.</span></span></span></span></p>

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><span style="color:black">During follow-up, 18.8% of patients had cardiovascular events: stroke (8.7%), ACS (5.6%), or HF hospitalization (4.5%). Compared to event-free patients, those with events had higher BMI (29.3 &plusmn; 4.3 vs. 27.8 &plusmn; 4.8 kg/m&sup2;; p=0.002), casual systolic BP (158.3 &plusmn; 23.5 vs. 151.9 &plusmn; 21.7 mmHg; p&lt;0.001), and PP (62.3 &plusmn; 19.9 vs. 58.0 &plusmn; 17.7 mmHg; p=0.004). ABPM showed higher 24-hour systolic BP (137.3 &plusmn; 17.1 vs. 130.1 &plusmn; 15.2 mmHg; p&lt;0.001), nighttime systolic BP (130.0 &plusmn; 19.7 vs. 120.8 &plusmn; 15.6 mmHg; p&lt;0.001), and reduced nocturnal dipping (42.1% vs. 55.1%; p=0.002).</span></span></span></span></p>

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><span style="color:black">Logistic regression models compared office BP (Model 1: systolic BP and PP) and ABPM (Model 2: 24-hour systolic BP, PP, daytime and nighttime systolic BP, nighttime diastolic BP, and nocturnal dipping). Model 2 had a higher AUC (0.65, 95% CI: 0.60&ndash;0.70) than Model 1 (0.60, 95% CI: 0.55&ndash;0.64), though the difference was not statistically significant (p=0.10). Subgroup analysis showed that ABPM significantly outperformed casual BP in ARH (AUC 0.77 vs. 0.63; p=0.04) and ANRH (AUC 0.62 vs. 0.52; p=0.03). In WCURH (AUC 0.60 vs. 0.56; p=0.28) and CH (AUC 0.65 vs. 0.63; p=0.23), differences were not significant.</span></span></span></span></p>

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<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Arial,Helvetica,sans-serif"><span style="color:#000000"><strong><span style="color:black">Conclusion:</span></strong><br />
<span style="color:black">ABPM demonstrated clear superiority in ARH and ANRH, improving predictive accuracy in these subgroups. In WCURH and CH, differences were not significant but favored ABPM, highlighting its value in complex cases where office BP may not fully reflect cardiovascular risk.</span></span></span></span></p>

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