Abstract
Approximate entropy (ApEn) of blood pressure (BP) can be easily measured based on software analysing 24-h ambulatory BP monitoring (ABPM), but the clinical value of this measure is unknown. In a prospective study we investigated whether ApEn of BP predicts, in addition to average and variability of BP, the risk of hypertensive crisis. In 57 patients with known hypertension we measured ApEn, average and variability of systolic and diastolic BP based on 24-h ABPM. Eight of these fifty-seven patients developed hypertensive crisis during follow-up (mean follow-up duration 726 days). In bivariate regression analysis, ApEn of systolic BP (P<0.01), average of systolic BP (P=0.02) and average of diastolic BP (P=0.03) were significant predictors of hypertensive crisis. The incidence rate ratio of hypertensive crisis was 14.0 (95% confidence interval (CI) 1.8, 631.5; P<0.01) for high ApEn of systolic BP as compared to low values. In multivariable regression analysis, ApEn of systolic (P=0.01) and average of diastolic BP (P<0.01) were independent predictors of hypertensive crisis. A combination of these two measures had a positive predictive value of 75%, and a negative predictive value of 91%, respectively. ApEn, combined with other measures of 24-h ABPM, is a potentially powerful predictor of hypertensive crisis. If confirmed in independent samples, these findings have major clinical implications since measures predicting the risk of hypertensive crisis define patients requiring intensive follow-up and intensified therapy.
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References
Zampaglione B, Pascale C, Marchisio M, Cavallo-Perin P . Hypertensive urgencies and emergencies prevalence and clinical presentation. Hypertension 1996; 27: 144–147.
Preston RA, Baltodano NM, Cienki J, Materson BJ . Clinical presentation and management of patients with uncontrolled, severe hypertension: results from a public teaching hospital. J Hum Hypertens 1999; 13: 249–255.
Blumenfeld JD, Laragh JH . Management of hypertensive crises: the scientific basis for treatment decisions. Am J Hypertens 2001; 14: 1154–1167.
Chobanian AV, Bakris GL, Black HR, Cushman WC, Lee AG, Izzo JL, et al., National High Blood Pressure Education Program Coordinating Committee. The seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. The JNC 7 report. JAMA 2003; 289: 2560–2572.
Tisdale JE, Huang MB, Borzak S . Risk factors for hypertensive crisis: importance of out-patient blood pressure control. Fam Pract 2004; 21: 420–424.
Shea S, Misra D, Ehrlich MH, Field L, Francis CK . Predisposing factors for severe, uncontrolled hypertension in an inner-city minority population. N Engl J Med 1992; 327: 776–781.
Sesoko S, Akema N, Matsukawa T, Kaneko Y . Predisposing factors for the development of malignant essential hypertension. Arch Intern Med 1987; 147: 1721–1724.
Grassberger P, Procaccia I . Characterization of strange attractors. Phys Rev Lett 1983; 50: 346–349.
Grassberger P, Procaccia I . Estimation of the Kolmogorov entropy from a chaotic signal. Phys Rev A 1983; 28: 2591–2593.
Pincus SM . Approximate entropy (ApEn) as a complexity measure. Chaos 1995; 5: 110–117.
Pincus SM, Goldberger AL . Physiological time-series analysis: what does regularity quantify? Am J Physiol Heart Circ Physiol 1994; 266: H1643–H1656.
Almog Y, Eliash S, Oz O, Akselrod S . Nonlinear analysis of BP signal. Can it detect malfunctions in BP control? Am J Physiol Heart Circ Physiol 1996; 271: H396–H403.
Wagner CD, Nafz B, Persson PB . Chaos in blood pressure control. Cardiovas Res 1996; 31: 380–387.
Wagner CD, Stauss HM, Persson PB, Kregel KC . Correlation integral of blood pressure as a marker for exercise intensities. Am J Physiol Regul Integr Comp Physiol 1998; 275: R1661–R1666.
Wagner CD, Persson PB . Nonlinear chaotic dynamics of arterial blood pressure and renal blood flow. Am J Physiol Heart Circ Physiol 1995; 268: H621–H627.
Theiler J, Eubank S, Longtin A, Galdrikian B, Farmer JD . Testing for nonlinearity in time series: the method of surrogate data. Physica D 1992; 58: 77–94.
Lee ET, Wang JW . Statistical Methods for Survival Data Analysis,3rd edn. John Wiley: New York, 2003.
Beaumont A, Marmarou A . Approximate entropy: a regularity statistic for assessment of intracranial pressure. Acta Neurochir Suppl 2002; 81: 193–195.
Kuusela TA, Jartti TT, Tahvanainen KU, Kaila TJ . Nonlinear methods of biosignal analysis in assessing terbutaline-induced heart rate and blood pressure changes. Am J Physiol Heart Circ Physiol 2002; 282: H773–H783.
Papaioannou TG, Vlachopoulos C, Ioakeimidis N, Alexopoulos N, Stefanadis C . Nonlinear dynamics of blood pressure variability after caffeine consumption. Clin Med Res 2006; 4: 114–118.
Jartti TT, Kuusela TA, Kaila TJ, Tahvanainen KU, Valimaki IA . The dose–response effects of terbutaline on the variability, approximate entropy and fractal dimension of heart rate and blood pressure. Br J Clin Pharmacol 1998; 45: 277–285.
Chatellier G, Dutrey-Dupagne C, Vaur L, Zannad F, Genes N, Elkik F et al. Home self blood pressure measurement in general practice. The SMART study. Am J Hypertens 1996; 9: 644–652.
Nicholls MG, Richards AM, Agarwal M . The importance of the renin-angiotensin system in cardiovascular disease. J Hum Hypertens 1998; 12: 295–299.
Laragh JH, Ulick S, Januszewicz V, Kelly WG, Liebemann S . Electrolyte metabolism and aldosterone secretion in benign and malignant hypertension. Ann Intern Med 1960; 53: 259–272.
Montgomery HE, Kiernan LA, Whitworth CE, Fleming S, Unger T, Gohlke P et al. Inhibition of tissue angiotensin converting enzyme activity prevents malignant hypertension in TGR(mREN2)27. J Hypertens 1998; 16: 635–643.
Varon J, Marik PE . Clinical review: the management of hypertensive crises. Crit Care 2003; 7: 374–384.
Hirschl MM, Binder M, Bur A, Herkner H, Woisetschlager C, Bieglmayer C et al. Impact of the renin-angiotensin-aldosterone system on blood pressure response to intravenous enalaprilat in patients with hypertensive crises. J Hum Hypertens 1997; 11: 177–183.
Acknowledgements
We thank Irene Baechler for her valuable assistance in the preparation of this manuscript. Andreas Schoenenberger is supported by a grant from the Robert Bosch Foundation (Stuttgart, Germany) and the Research Fund of the Department of General Internal Medicine, University Hospital, Berne, Switzerland.
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Schoenenberger, A., Erne, P., Ammann, S. et al. Prediction of hypertensive crisis based on average, variability and approximate entropy of 24-h ambulatory blood pressure monitoring. J Hum Hypertens 22, 32–37 (2008). https://doi.org/10.1038/sj.jhh.1002263
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DOI: https://doi.org/10.1038/sj.jhh.1002263
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