Clinical risk factors and predictive score for the non-dipper profile in hypertensive patients: a case-control study
Abstract Background Night-time BP, especially non-dipper, is a stronger predictor of adverse cardiovascular outcomes. Ambulatory blood pressure monitoring (ABPM) is a gold standard for the detection of non-dippers but it often is unavailable and expensive. This study aims to determine clinical risk...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
BMC
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/529a4f1e8bb34f72bff31b4ca90e7135 |
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| Sumario: | Abstract Background Night-time BP, especially non-dipper, is a stronger predictor of adverse cardiovascular outcomes. Ambulatory blood pressure monitoring (ABPM) is a gold standard for the detection of non-dippers but it often is unavailable and expensive. This study aims to determine clinical risk factors that predict non-dipper. Methods An exploratory traditional case-control study, exclusive sampling of control was conducted from January 2013 to September 2018 to explore clinical risk factors associated with non-dippers in hypertensive patients. Subgroup analysis was performed in each treated and untreated hypertensive patient. The parsimonious predictive score for non-dippers was constructed. Results The study included 208 hypertensive patients receiving 24 h ABPM. There were 104 dippers and 104 non-dippers. Significant clinical risk factors associated with non-dippers were the age of > 65 years, average office diastolic blood pressure (DBP), and fasting plasma glucose of > 5.6 mmol/L. Results of subgroup analysis showed that dyslipidemia, history of coronary artery disease, use of angiotensin-converting enzyme inhibitors (ACEIs) and direct vasodilators, average office DBP, and serum uric acid were associated with non-dippers in treated hypertensive patients, however, there were no risk factors associated with non-dippers in the untreated group. The predictive score for non-dippers in treated group included average office DBP, dyslipidemia, serum uric acid, male, calcium channel blockers and ACEIs use. The area under Receiver Operating Characteristic (AuROC) was 0.723. A cut-off point which was > 0.0701 and prevalence of non-dippers of 46%, this score had a sensitivity of 77.4%, specificity of 65.6%, positive predictive value (PPV) of 66.1%, and negative predictive value (NPV) of 79.6%. For untreated group, age, hemoglobin and body mass index were included in the predictive model. AuROC was 0.74. There was a sensitivity of 51.9%, specificity of 91.2%, PPV of 82.4%, and NPV of 70.5% at the cut-off point of > 0.357, and prevalence of 44%. Conclusion There were several significant clinical risk factors associated with non-dippers in treated hypertensive patients. The predictive score might be useful for the detection of non-dippers; however, it cannot replace ABPM. |
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