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Automatic measurement of long-term heart rate variability by implanted single-chamber devices

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Abstract

Heart rate variability (HRV) measurement is an established technology for the assessment of cardiac autonomic status. Recently 24 h HRV has been shown to correlate with disease severity in heart failure. This potentially makes continuous 24h HRV measurement suitable for monitoring of heart-failure patients. Day-to-day 24 h measurement of HRV is, in principle, feasible when implemented using implanted devices (pacemakers and defibrillators)_ ued in patients who are predominantly in the sinus rhythm. However, a number of such devices used in heart-failure patients are single-chamber devices, in which the distinction between sinus rhythm beats and ectopic beats is problematic. The study investigates whether a reasonably accurate 24h HRV measurement can be achieved by automatic algorithms, suitable for implementation using implanted devices, without the need for identification of ectopic beats. A set of 5321 nominal 24 h Holter recordings of cardiac patients are used. Each of the recordings contains at least one ectopic beat; approximately 30% of the recordings have more than 1% of ectopic beats. Conventional 24h measures of HRV, that is the SDNN, HRV index, and SDANN indices, are obtained from each recording after elimination of the ectopic beats and are approximated by HRV measures computed by the same formulas without exclusion of the ectopic beats. The SDANN values are also approximated by the standard deviation of 5 min medians of all RR intervals (SDMRR measure). The errors introduced by including the ectopic beats in the HRV computation were evaluated using the Bland-Altman statistics and by Cohen's kappa statistics investigating the precision of identifying patients with depressed and preserved 24 h HRV. The SDNN measure is very sensitive to the quality of the RR interval sequence and cannot be reasonably used without the distinction between sinus rhythm and ectopic beats. The HRV index measure is marginally more acceptable when used without ectopic elimination. The SDANN is rather insensitive, and its replacement by SDMRR values leads to relative errors in the region of 2–5% that are almost independent of the number of ectopic beats included. Even in recordings with a substantial proportion of ectopic beats, a practically acceptable (κ>0.9) identification of depressed and preserved SDANN values is possible without ectopic elimination. Thus, continuous monitoring of 24h HRV is technically feasible within implanted devices, provided the SDANN measure is monitored and either computed from the sequence of all RR intervals or, potentially preferably, replaced by the SDMRR measure.

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References

  • Berntson, G. G., Bigger, J. T. Jr., Eckberg, D. L., Grossman, P., Kaufmann, P. G., Malik, M., Nagaraja, H. N., Porges, S. W., Saul, J. P., Stone, P. H., andvan der Molen, M. W. (1997): ‘Heart rate variability: Origins, methods, and interpretative caveats’,Psychophysiology,34, pp. 623–648

    Article  Google Scholar 

  • Bland, J. M., andAltman, D. G. (1986): ‘Statistical methods for assessing agreement between two methods of clinical measurement’,Lancet,1, (8476) pp. 307–310

    Google Scholar 

  • Cohen, J. (1968): ‘Weighted Kappa: nominal scale agreement with-provision for scaled disagreement or partial credit’,Psychol. Bull.,70, pp. 213–220

    Article  Google Scholar 

  • Copie, X., Guize, L., andLe Heuzey, J.-Y. (1998): ‘Heart rate variability in heart failure’,Heart Failure,14, pp. 185–191

    Google Scholar 

  • Hartikainen, J. E. K., Malik, M., Staunton, A., Poloniecki, J., andCamm, A. J. (1996): ‘Distinction between arrhythmic and nonarrhythmic death after acute myocardial infarction based on heart rate variability, signal-averaged electrocardiogram, ventricular arrhythmias and left ventricular ejection fraction’J. Am. Coll. Cardiol.,28, pp. 296–304

    Article  Google Scholar 

  • Kamen, P. W., Krum, H., andTonkin, A. M. (1997): ‘Low-dose but not high-dose captopril increases parasympathetic activity in patients with heart failure’,J. Cardiovasc. Pharmacol.,30, pp. 7–11

    Article  Google Scholar 

  • Kienzle, M., Ferguson, D. W., Birkett, C. L., Myers, G. A., Berg, W. J., andMarino, D. J. (1992): ‘Clinical, haemodynamic and sympathetic neural correlates of heart rate variability in congestive heart failure’,Am. J. Cardiol.,69, pp. 761–767

    Article  Google Scholar 

  • Kleiger, R. E., Miller, J. P., Bigger, J. T. Jr., andMoss, A. J. (1987): ‘Decreased heart rate variability and its association with increased mortality after acute myocardial infarction’,Am. J. Cardiol.,59, pp. 256–262

    Article  Google Scholar 

  • Malik, M., Cripps, T., Farrell, T., andCamm, A. J. (1989a): ‘Prognostic value of heart rate variability after myocardial infarction: a comparison of different data processing methods’,Med. Biol. Eng. Comput.,27, pp. 603–611

    Article  Google Scholar 

  • Malik, M., Farrell, T., Cripps, T., andCamm, A. J. (1989b): ‘Heart rate variability in relation to prognosis after myocardial infarction: selection of optimal data processing techniques’,Eur. Heart J.,10, pp. 1060–1074

    Google Scholar 

  • Malik, M., Xia, R., Odemuyiwa, O., Staunton, A., Poloniecki, J. andCamm, A. J. (1993): ‘Influence of the recognition artefact in the automatic analysis of long-term electrocardiograms on time-domain measurement of heart rate variability’,Med. Biol. Eng. Comput.,31, 539–544

    Article  Google Scholar 

  • Manolis, A. J., Olympios, C., Sifaki, M., Smirnioudis, N., Handanis, S., Argirakis, S., Katsaros, C., Gavras, I., andGavras, H. (1998): ‘Chronic sympathetic suppression in the treatment of chronic congestive heart failure’,Clin. Exper. Hypertens.,20, pp. 717–731

    Article  Google Scholar 

  • Nolan, J., Batin, P. D., Andrews, R., Lindsay, S. J., Brooksby, P., Mullen, M., Baig, W., Flapan, A. D., Cowley, A., Prescott, R. J., Neilson, J. M., andFox, K. A. (1998): ‘Prospective study of heart rate variability and mortality in chronic heart failure: results of the United Kingdom heart failure evaluation and assessment of risk trial (UK-heart)’,Circulation,98, 1510–1516

    Google Scholar 

  • Panina, G., Khot, U. N., Nunziata, E., Cody, R. J., andBinkley, P. F. (1996): ‘Role of spectral measures of heart rate variability as markers of disease progression in patients with chronic congestive heart failure not treated with angiotensin-converting enzyme inhibitors’,Am. Heart J.,131, pp. 153–157

    Article  Google Scholar 

  • Ponikowski, P., Anker, S. D., Chua, T. P., Szelemej, R., Piepoli, M., Adamopoulos, S., Webb-Peploe, K., Harrington, D., Banasiak, W., Wrabec, K., andCoates, A. J. S. (1997): ‘Depressed heart rate variability as an independent predictor of death in chronic congestive heart failure secondary to ischaemic or idiopathic dilated cardiomyopathy’,Am. J. Cardiol.,79, pp. 1645–1650

    Article  Google Scholar 

  • Ponikowski, P., Chua, T. P., Piepoli, M., Banasiak, W., Anker, S. D., Szelemej, R., Molenda, W., Wrabec, K., Capucci, A., andCoats, A. J. (1998): ‘Ventilatory response to exercise correlates with impaired heart rate variability in patients with chronic, congestive heart failure’,Am. J. Cardiol.,82, pp. 338–344

    Article  Google Scholar 

  • Radaelli, A., Coats, A. J., Leuzzi, S., Piepoli, M., Meyer, T. E., Calciati, A., Finardi, G., Bernardi, L., andSleight, P. (1996): ‘Physical, training enhances sympathetic and parasympathetic control of heart rate and peripheral vessels in chronic heart failure’,Clin. Sci.,91, (Suppl.) pp. 92–94

    Google Scholar 

  • Saul, J. P., Arai, Y., Berger, R. D., Lilly, L. S., Colucci, W. S., andCohen, R. J. (1988): ‘Assessment of autonomic regulation in chronic congestive heart failure by heart rate spectral analysis’,Am. J. Cardiol.,61, pp. 1292–1299

    Article  Google Scholar 

  • Stefenelli, Th., Berger-Klein, J., Globits, S., Pacher, R., andGlogar, D. (1992): ‘Heart rate behaviour at different stages of congested heart failure’,Eur. Heart J.,13, pp. 902–907

    Google Scholar 

  • Sweeney, M. O., Ruskin, J. N., Garan, H., McGovern, B. A., Guy, M. L., Torchiana, D. F., Vlahakes, G. J., Newell, J. B., Semigran, M. J., andDec, G. W. (1995): ‘Influence of the implantable cardioverter/defibrillator on sudden death and total mortality in patients evaluated for cardiac transplantation’,Circulation,92, pp. 3273–3281

    Google Scholar 

  • Szabo, B. M., vanVeldhuisen D. J., Brouwer, J., Haaksma, J., andLie, K. I. (1995): ‘Relation between severity of disease and impairment of heart rate variability parameters in patients with chronic congestive heart failure secondary to coronary artery disease’,Am. J. Cardiol.,76, pp. 713–716

    Article  Google Scholar 

  • Task Force of European Society of Cardiology and North American Society of Pacing & Electrophysiology (1996): ‘Heart rate variability—Standards of measurement, physiological interpretation, and clinical use’,Circulation,93, pp. 1043–1065

    Google Scholar 

  • Trappe, H. J., Wenzlaff, P., Pfitzner, P., andFieguth, H. G. (1997): ‘Long-term follow up of patients with implantable cardioverter-defibrillators and mild, moderate, or severe impairment of left ventricular function’,Heart,78, 254–249

    Google Scholar 

  • Tuininga, Y. S., vanVeldhuisen, D. J., Brouwer, J., Haaksma, J., Crijns, H. J. G. M., Man In't Veld, A. J., andLie, K. I. (1994): ‘Heart rate variability in left ventricular dysfunction and heart failure: effects and implications of drug treatment’,Br. Heart J.,72, pp. 509–513

    Article  Google Scholar 

  • Uretsky, B. F., andSheahan, R. G. (1997): ‘Primary prevention of sudden cardiac death in heart failure: will the solution be shocking?’,J. Am. Coll. Cardiol.,30, 1589–1597

    Article  Google Scholar 

  • Wijbenga, J. A. M., Balk, A. H. M. M., Meij, S. H., Simoons, M. L., andMalik, M. (1998): ‘Heart rate variability index in congestive heart failure: relation to clinical variables and prognosis’,Eur. Heart J.,19, pp. 1719–1724

    Article  Google Scholar 

  • Woo, M. A., Stevenson, W. G., Moser, D. K., andMiddlekauff, H. R. (1994): ‘Complex heart rate variability and serum norepinephrine levels in patients with advanced heart failure’,J. Am. Coll. Cardiol.,69, pp. 761–767

    Google Scholar 

  • Xia, R., Odemuyiwa, O., Gill, J., Malik, M., andCamm, A. J. (1993): ‘Influence of recognition errors of computerised analysis of 24-hour electrocardiograms on the measurement of spectral components of heart rate variability’,Int. J. Biomed. Comput.,32, pp. 223–235

    Article  Google Scholar 

  • Yi, G., Goldman, J. H., Keeling, P. J., Reardon, M., McKenna, W. J., andMalik, M. (1997): ‘Heart rate variability in idiopathic dilated cardiomyopathy: relation to disease severity and prognosis’,Heart,77, pp. 108–114

    Google Scholar 

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Malik, M., Padmanabhan, V. & Olson, W.H. Automatic measurement of long-term heart rate variability by implanted single-chamber devices. Med. Biol. Eng. Comput. 37, 585–594 (1999). https://doi.org/10.1007/BF02513352

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