Circadian Rhythm of Heart Rate Variability Survivors of Cardiac Arrest
in
Heikki V. Huikuri, MD, Markku K. Linnaluoto, MSc, Tapio Seppanen, PhD, K. E. Juhani Airaksinen, MD, Kenneth M. Kessler, MD, Juha T. Takkunen, MD, and Robert J. Myerburg, MD
Reduced heart rate (HR) variability is associated with increased risk of cardiac arrest in patients with coronary artery disease. In this study, the power spectral components of HR variability and their circadian pattern in 22 survivors of out-ofhospital cardiac arrest not associated with acute myocardial infarction were compared with those of 22 control patients matched with respect to age, sex, previous myocardial infarction, ejection fraction and number of diseased coronary arteries. Survivors of cardiac arrest had significantly lower 24.hour average standard deviation of RR intervals than control patients (29 f 10 vs 51 f 15 ms, p 60 years; (2) male or female gender; (3) presenceor absenceof prior Q-wave myocardial infarction; (4) left ventricular ejection fraction 50%; and (5) l-vessel, 2-vessel,or 3-vesselcoronary artery diseaseon angiography. A patient in the control group was matched with a survivor of cardiac arrest for at least 4 of the 5 variables. The matching was performed before analysesof 24hour electrocardiographic recordings. The clinical data of the control group are summarized in Table I. All control patients underwent left-sided cardiac catheterization including the angio graphic studies. The 24-hour electrocardiographic recordings were performed in the hospital in all patients before cardiac catheterization studies. Beta-blocking and antiarrhythmic drugs were withdrawn at least 5 half-lives beforehand in all patients. Each patient gaveinformed consent for the studies. Invasive rtudler: Left-sided cardiac catheterization was performed by the Judkins’ technique. Left ventricular cineangiogramswere recorded in the 45Oright anterior oblique projection and the ejection fraction was calculated as a single-plane area-length method. Coronary artery stenoseswith >50% luminal narrowing were considered significant. recordings: All Ambulatory ektrocardiographk patients underwent a 24-hour electrocardiographic recording. Two-channel 24hour electrocardiographic recordings were analyzed by a Delmar Avionics scanner. The number of ventricular ectopic beats, episodesof repetitive ectopic beats and episodesof ventricular tachycardia were analyzed from the tape recordings. Analysis of heut rate vukb#ity: The digitally sampled electrocardiographic data were transferred from the Delmar Avionics scanner to a microcomputer for analysis of HR variability. A linear detrend was applied to the RR interval data in segmentsof 5 12 samplesto make it more stationary. This was implemented by first fitting a straight line to a segmentby a standard leastsquaresmethod and then subtracting it from the sample values. The computer program labels each QRS complex, and the RR interval seriesis passedthrough a filter that eliminates ectopic beats and artifacts and fills the resulting gaps with an average value computed in the local neighborhood. In addition, the RR intervals were reviewed on the computer display by an experienced observer, and only those RR intervals related to normal sinus beats in a stationary state were included in the final analysis. Segmentsthat qualified for >-9W of the RR intervals were included. An autoregressivemodel was used to estimate the power spectral densities of the RR interval variability.i2 The size of 10 was used for the model order in the analysis of the RR data.i3*t4The computer program calculates the autoregressivecoefficients to define the power spectral density. Power spectra were quantified by mea-
TABLE I Clinical and Angiographic Characteristics of Patients of
SuNivon
Clrnical data Age (years) Sex (women/men) History of congestive heart failure Cardiac medication Digitalis Diuretic Nitrate Calcium antagonist ACE inhibitor Previous myocardial infarction None Anterior Inferior Anterior+rnferior Electrocardiogram Q waves lntraventricular conduction defect New York Heart Association functional class 1 2 3 4 Time of cardiac arrest fn = 20) Bet. 12 P.M. and 6 A.M. Bet. 6 A.M. and 12 A.M. Bet. 12 A.M. and 6 P.M. Bet. 6 P.M. and 12 P.M. Angiographic data Ejection fraction (%) Coronary angiography l-vessel disease 2-vessel disease 3-vessel disease ACE
Cardiac Arrest (n = 22)
Control Patients (n = 22)
59 * 8 4118 4 118%)
60 ? 7 4118 5 (23%)
11 14 14 4 3
(50%) (64%) (64%) (18%) (14%)
5 7 19 11 3
(23%) (32%) (86%) (50%) 114%)
2 10 7 3
(9%) (45%) (32%) (14%)
2 10 7 3
(9%) (45%) (32%) (14%)
17 (77%) 5 (23%)
18 (82%) 2 (9%)
3 (14%) 11(50%) 6 (27%) 2 (9%)
2 11 8 1
(9%) (50%) (36%) (5%)
1 (6%)
9 (39%) 6 (33%) 4 (22%) 402
16
5 (23%) 9 (41%) 8 (36%)
44-t
15
3 (14%) 9 (41%) 10 (45%)
= angiotensln-converting enzyme;Bet. = between.
suring the area in 2 frequency bands: low-frequency power (0.04 to 0.15 Hz), and high-frequency power (0.15 to 0.40 Hz). The average RR interval and the standard deviation of the mean RR interval measured from successive5-minute periods were also calculated. The average HR, standard deviation of RR intervals, and low- and high-frequency spectral areas were calculated for each l-hour period and for the 24-hour period in each patient. Statistics: Spectral areas,averageHR and standard deviation of RR intervals were comparedbetweensurvivors of cardiac arrest and control patients with the unpaired Student’s t test. A p value 5 beats) VPCs = ventricular
premature
complexes:
VT = ventricular
TABLE Ill Twenty-Four-Hour Average Heart Rate Variability Survivors of Cardiac Arrest (n = 221
Control Patients SD of RR intervals (ms) High-frequency spectral area (ms* x 10) Low-frequency spectral area (ms2 x 10) Ratio between low- and highfrequency areas
7 (29%) 14 (64%) 1(5%) 0 (4%) 0 (4%)
‘p 50 ms: 1.5% RMS of succ diff: 417 ms*ms
-
8% I Power 0.40 I :: 549 105 ms*ms Power I 0.15 0.04 -- 0.15 ms*ms I 48% 1
10990-
lOOOO-
0.1
0.2 II
11
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0.3 II
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0.1
cycles/beat
scale : cycles/second
11
11
0.3
scale :
0.5
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SPECTRAL ANALYSIS OF ‘a:aarni.dat’ Period 04~00 - 05:OO
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SPECTRAL ANALYSIS OF ‘a:aarni.dat’ Period 08:OO - 9:W -i
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Aver hb period: 723 ms (82 hb/min) Standard deviation: 72 ms Oualifkd beats: 4934 (99%) Diff no succ hb > 50 ms: 2.7% RMS of succ diti 558 ms*ms
Oualifled beats: 3351 (99%) Diff no succ hb > 50 ms: 20.6% RMS of succ diff: 1806 ms*ms ;g:x:
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THE AMERICAN JOURNAL OF CARDIOLOGY VOLUME 70
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SEPTEMBER 1, 1992
vous systemlesion, a typical pattern of respiratory sinus arrhythmia remained intact.21 Further studies using different methods are needed to distinguish between changes in efferent neural activities or target function responsivenessas causative factors for impaired HR variability in survivors of cardiac arrest. Circadian dnythm of heart rate variability: A distinct reproducible circadian pattern of HR variability was observedin both patient groups, with the acrophase occurring in the morning hours before arousal. This was followed by an abrupt decreasein HR variability after arousal, resulting in very low vagal HR control in survivors of cardiac arrest in the morning. To our knowledge, no information has been previously available about the possible circadian rhythm of cardiac autonomic function in high-risk patients with coronary artery disease. We have previously reported a similar circadian rhythm of HR variability in normal healthy subjects3 Furlan et al4 demonstrateda rapid increasein sympathetic activity and concomitant vagal withdrawal both in hospitalized and nonhospitalized patients without evident heart disease. High values of circulating plasma catecholamine levels have also been observedin the morning.22 These data support the view that autonomic unbalance should be considered as a potential contributory factor for increasedprevalenceof suddencardiac death during the morning hours.
REFERENCES 1. Kleiger RE, Miller JP, Bigger JT, Moss AJ, the Multicenter Post-Infarction Research Group. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol 1987;59: 256-262. 2. Rich MW, Saini JS, Kleiger RE, Camey RM, teVelde A, Freedland KE. Correlation of heart rate variability with clinical and angiographicvariables and late mortality after coronary angiography. Am J Curdiol 1988;62:714-717. 3. Huikuri HV, KesslerKM, Terracall E, CastellancsA, Linnaluoto MK, Myerburg RJ. Reproducibility and circadian rhythm of heart rate variability in healthy subjects.Am J Cardiol 1990;65:391-393. 4. Furlan R, Guazetti S, Crivellaro W, Dassi S, Tinelli M, Baselli G, Cerutti S, Lombardi F, Pagani M, Malliani A. Continuous24hour assessmentof the neural regulation of systemicarterial pressureand RR variabilities in ambulantsubjects. Circulation 1990;81:537-547. 5. Muller JE, Ludmer PL, Willich SN, Tofler GH, Aylmer G, Klangos I, Stone
PH. Circadian variation in the frequency of suddencardiac death. Circulation 1987;75:131-138. 6. Lip&z LA, Mietus J, Moody GB, GoldbergerAL. Spectral characteristicsof heart rate variability before and during postural tilt. Relationsto agingand risk of syncope.Circulation 1990;81:1803-1810. 7. Airaksinen KEJ, Ikaheimo MJ, Linnaluoto MK, Niemela M, Takkunen JT. Impaired vagal heart rate control in coronary artery disease. Br Hear! J 1987;58:592-597.
8. Saul JP, Arai Y, Berger RD, Lilly LS, Colucci WS, CohenRJ. Assessmentof autonomic regulation in chronic congestiveheart failure by heart rate spectral analysis. Am J Cordiol 1988;61:1292-1296. 9. Hayano J, Sakakibara Y, Yamada M, Ohte N, Fujinami T, Yokoyama K, WatanabeY, Takata K. Decreasedmagnitudeof heart rate spectralcomponents in coronary artery disease.Its relation to angiographic severity. Circulation 1990;81:1217-1224. 10. Bigger JT, Kleiger RE, FleissJL, Rolnitzky LM, Steinman RC, Miller JP, the Multicenter Post-Infarction ResearchGroup. Componentsof heart rate variability measuredduring healing of acute myocardial infarction. Am J Cordial 1988;61:208-212. II. Lombardi F, SandroneG, Pernpruner S, Sala R, Garimoldi M, Cerutti S, Baselli G, Pagani M, Malliani A. Heart rate variability as an index of sympatho vagal interaction after acute myocardial infarction. Am J Cardiol 198760: 1239-1245. 12. PressWH, Flannery BP,Teukolsky SA, Vetterling WT. Numerical recipesin C. New York: Cambridge University Press,1988:447-452. 13. Kay SM, Marple SL. Spectrumanalysis- a modernperspective.Proc IEEE 1981;69:1380-1384. 14. Saul JP, Albrecht P, Berger RD, Cohen RJ. Analysis of long term heart rate variability: methods,I/f scalingand implications.Cornput Cardiol1988;419-422. 15. Halberg F, CarandenteF, ComelissenG, Katinas GS. Glossaryof chronobiology. Chronobiologia 1977;IV(suppl 1)1:187. 16. Martin GJ, Magid NM, Myers G, Barnett PS, SchaalJW, Lesch M, Singer DH. Heart rate variability and suddendeathsecondaryto coronary artery disease during ambulatory electrocardiographic monitoring. Am J Curdiol 1987;60: 86-89. 17. Myers GA, Martin GJ, Magid NM, Burnett PS, Schaad JW. Weiss JS,
Lesch M, Singer DH. Power spectralanalysisof heart rate variability in sudden cardiac death: comparisonto other methods.IEEE Trans Biomed Eng 1986;33: 1149-1156. IS. Akselrod S, Gordon D, Ubel FA, ShannonDC, Barger AC, CohenRJ. Power spectrumanalysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 1981;213:220-222. 19. PomeranzB, Macaulay RJB, Caudill MA, Kutz J, Adam D, Gordon D, Kilborn KM, Barger AC, Shannon DC, Cohen RJ, BensonH. Assessmentof autonomic function in humans by heart rate spectral analysis. Am J Physio! 1985;248:H151-H153. 20. Pagani M, Lombardi F, Guzzetti S, Rimoldi 0, Furlan R, Pizzinelli P, SandroneG, Malfatto G, Bell’Orto S, PiccalugaE, Turiel M, Baselli G, Cerutti S, Malliani A. Power spectralanalysisof heart rate and arterial pressurevariabilities as a marker of sympatho-vagalinteraction in man and consciousdog. Circ Res 1986;59:178-193. 21. Vallbona C, Cardus D, SpencerWA, Hoff HE. Patternsof sinusarrhythmia in patients with lesionsof the central nervous system.Am J Cardiol 1965;16: 379-384.
22. Turton MB, DeeganT. Circadian variations of plasmacatecholamine,cortisol,and immunoreactiveinsulin concentrationsin supinesubjects.Clin Cbim Acta 1974;55:389-397.
HEART RATE VARIABILITY AND CARDIAC ARREST 615
in
Heikki V. Huikuri, MD, Markku K. Linnaluoto, MSc, Tapio Seppanen, PhD, K. E. Juhani Airaksinen, MD, Kenneth M. Kessler, MD, Juha T. Takkunen, MD, and Robert J. Myerburg, MD
Reduced heart rate (HR) variability is associated with increased risk of cardiac arrest in patients with coronary artery disease. In this study, the power spectral components of HR variability and their circadian pattern in 22 survivors of out-ofhospital cardiac arrest not associated with acute myocardial infarction were compared with those of 22 control patients matched with respect to age, sex, previous myocardial infarction, ejection fraction and number of diseased coronary arteries. Survivors of cardiac arrest had significantly lower 24.hour average standard deviation of RR intervals than control patients (29 f 10 vs 51 f 15 ms, p 60 years; (2) male or female gender; (3) presenceor absenceof prior Q-wave myocardial infarction; (4) left ventricular ejection fraction 50%; and (5) l-vessel, 2-vessel,or 3-vesselcoronary artery diseaseon angiography. A patient in the control group was matched with a survivor of cardiac arrest for at least 4 of the 5 variables. The matching was performed before analysesof 24hour electrocardiographic recordings. The clinical data of the control group are summarized in Table I. All control patients underwent left-sided cardiac catheterization including the angio graphic studies. The 24-hour electrocardiographic recordings were performed in the hospital in all patients before cardiac catheterization studies. Beta-blocking and antiarrhythmic drugs were withdrawn at least 5 half-lives beforehand in all patients. Each patient gaveinformed consent for the studies. Invasive rtudler: Left-sided cardiac catheterization was performed by the Judkins’ technique. Left ventricular cineangiogramswere recorded in the 45Oright anterior oblique projection and the ejection fraction was calculated as a single-plane area-length method. Coronary artery stenoseswith >50% luminal narrowing were considered significant. recordings: All Ambulatory ektrocardiographk patients underwent a 24-hour electrocardiographic recording. Two-channel 24hour electrocardiographic recordings were analyzed by a Delmar Avionics scanner. The number of ventricular ectopic beats, episodesof repetitive ectopic beats and episodesof ventricular tachycardia were analyzed from the tape recordings. Analysis of heut rate vukb#ity: The digitally sampled electrocardiographic data were transferred from the Delmar Avionics scanner to a microcomputer for analysis of HR variability. A linear detrend was applied to the RR interval data in segmentsof 5 12 samplesto make it more stationary. This was implemented by first fitting a straight line to a segmentby a standard leastsquaresmethod and then subtracting it from the sample values. The computer program labels each QRS complex, and the RR interval seriesis passedthrough a filter that eliminates ectopic beats and artifacts and fills the resulting gaps with an average value computed in the local neighborhood. In addition, the RR intervals were reviewed on the computer display by an experienced observer, and only those RR intervals related to normal sinus beats in a stationary state were included in the final analysis. Segmentsthat qualified for >-9W of the RR intervals were included. An autoregressivemodel was used to estimate the power spectral densities of the RR interval variability.i2 The size of 10 was used for the model order in the analysis of the RR data.i3*t4The computer program calculates the autoregressivecoefficients to define the power spectral density. Power spectra were quantified by mea-
TABLE I Clinical and Angiographic Characteristics of Patients of
SuNivon
Clrnical data Age (years) Sex (women/men) History of congestive heart failure Cardiac medication Digitalis Diuretic Nitrate Calcium antagonist ACE inhibitor Previous myocardial infarction None Anterior Inferior Anterior+rnferior Electrocardiogram Q waves lntraventricular conduction defect New York Heart Association functional class 1 2 3 4 Time of cardiac arrest fn = 20) Bet. 12 P.M. and 6 A.M. Bet. 6 A.M. and 12 A.M. Bet. 12 A.M. and 6 P.M. Bet. 6 P.M. and 12 P.M. Angiographic data Ejection fraction (%) Coronary angiography l-vessel disease 2-vessel disease 3-vessel disease ACE
Cardiac Arrest (n = 22)
Control Patients (n = 22)
59 * 8 4118 4 118%)
60 ? 7 4118 5 (23%)
11 14 14 4 3
(50%) (64%) (64%) (18%) (14%)
5 7 19 11 3
(23%) (32%) (86%) (50%) 114%)
2 10 7 3
(9%) (45%) (32%) (14%)
2 10 7 3
(9%) (45%) (32%) (14%)
17 (77%) 5 (23%)
18 (82%) 2 (9%)
3 (14%) 11(50%) 6 (27%) 2 (9%)
2 11 8 1
(9%) (50%) (36%) (5%)
1 (6%)
9 (39%) 6 (33%) 4 (22%) 402
16
5 (23%) 9 (41%) 8 (36%)
44-t
15
3 (14%) 9 (41%) 10 (45%)
= angiotensln-converting enzyme;Bet. = between.
suring the area in 2 frequency bands: low-frequency power (0.04 to 0.15 Hz), and high-frequency power (0.15 to 0.40 Hz). The average RR interval and the standard deviation of the mean RR interval measured from successive5-minute periods were also calculated. The average HR, standard deviation of RR intervals, and low- and high-frequency spectral areas were calculated for each l-hour period and for the 24-hour period in each patient. Statistics: Spectral areas,averageHR and standard deviation of RR intervals were comparedbetweensurvivors of cardiac arrest and control patients with the unpaired Student’s t test. A p value 5 beats) VPCs = ventricular
premature
complexes:
VT = ventricular
TABLE Ill Twenty-Four-Hour Average Heart Rate Variability Survivors of Cardiac Arrest (n = 221
Control Patients SD of RR intervals (ms) High-frequency spectral area (ms* x 10) Low-frequency spectral area (ms2 x 10) Ratio between low- and highfrequency areas
7 (29%) 14 (64%) 1(5%) 0 (4%) 0 (4%)
‘p 50 ms: 1.5% RMS of succ diff: 417 ms*ms
-
8% I Power 0.40 I :: 549 105 ms*ms Power I 0.15 0.04 -- 0.15 ms*ms I 48% 1
10990-
lOOOO-
0.1
0.2 II
11
0.1
0.3 II
0.2
0.4
0.1
cycles/beat
scale : cycles/second
11
11
0.3
scale :
0.5
0.1
SPECTRAL ANALYSIS OF ‘a:aarni.dat’ Period 04~00 - 05:OO
-$
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0.5
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SPECTRAL ANALYSIS OF ‘a:aarni.dat’ Period 08:OO - 9:W -i
3oooo
Aver hb period: 723 ms (82 hb/min) Standard deviation: 72 ms Oualifkd beats: 4934 (99%) Diff no succ hb > 50 ms: 2.7% RMS of succ diti 558 ms*ms
Oualifled beats: 3351 (99%) Diff no succ hb > 50 ms: 20.6% RMS of succ diff: 1806 ms*ms ;g:x:
g:g
: ::;I
gf
“,$:;
I:q
2oooo
I
cyc::t: 0.1
1
614
’
1 ’ 1 ’ 1 ’ 1 ’ 1 scale: cycles/second 0.4 0.2 0.3 0.5 0.1
THE AMERICAN JOURNAL OF CARDIOLOGY VOLUME 70
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0.3
0.4
0.5
w 0.1 0.2 0.3 0.4 0.5 0.6 0.7
SEPTEMBER 1, 1992
vous systemlesion, a typical pattern of respiratory sinus arrhythmia remained intact.21 Further studies using different methods are needed to distinguish between changes in efferent neural activities or target function responsivenessas causative factors for impaired HR variability in survivors of cardiac arrest. Circadian dnythm of heart rate variability: A distinct reproducible circadian pattern of HR variability was observedin both patient groups, with the acrophase occurring in the morning hours before arousal. This was followed by an abrupt decreasein HR variability after arousal, resulting in very low vagal HR control in survivors of cardiac arrest in the morning. To our knowledge, no information has been previously available about the possible circadian rhythm of cardiac autonomic function in high-risk patients with coronary artery disease. We have previously reported a similar circadian rhythm of HR variability in normal healthy subjects3 Furlan et al4 demonstrateda rapid increasein sympathetic activity and concomitant vagal withdrawal both in hospitalized and nonhospitalized patients without evident heart disease. High values of circulating plasma catecholamine levels have also been observedin the morning.22 These data support the view that autonomic unbalance should be considered as a potential contributory factor for increasedprevalenceof suddencardiac death during the morning hours.
REFERENCES 1. Kleiger RE, Miller JP, Bigger JT, Moss AJ, the Multicenter Post-Infarction Research Group. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol 1987;59: 256-262. 2. Rich MW, Saini JS, Kleiger RE, Camey RM, teVelde A, Freedland KE. Correlation of heart rate variability with clinical and angiographicvariables and late mortality after coronary angiography. Am J Curdiol 1988;62:714-717. 3. Huikuri HV, KesslerKM, Terracall E, CastellancsA, Linnaluoto MK, Myerburg RJ. Reproducibility and circadian rhythm of heart rate variability in healthy subjects.Am J Cardiol 1990;65:391-393. 4. Furlan R, Guazetti S, Crivellaro W, Dassi S, Tinelli M, Baselli G, Cerutti S, Lombardi F, Pagani M, Malliani A. Continuous24hour assessmentof the neural regulation of systemicarterial pressureand RR variabilities in ambulantsubjects. Circulation 1990;81:537-547. 5. Muller JE, Ludmer PL, Willich SN, Tofler GH, Aylmer G, Klangos I, Stone
PH. Circadian variation in the frequency of suddencardiac death. Circulation 1987;75:131-138. 6. Lip&z LA, Mietus J, Moody GB, GoldbergerAL. Spectral characteristicsof heart rate variability before and during postural tilt. Relationsto agingand risk of syncope.Circulation 1990;81:1803-1810. 7. Airaksinen KEJ, Ikaheimo MJ, Linnaluoto MK, Niemela M, Takkunen JT. Impaired vagal heart rate control in coronary artery disease. Br Hear! J 1987;58:592-597.
8. Saul JP, Arai Y, Berger RD, Lilly LS, Colucci WS, CohenRJ. Assessmentof autonomic regulation in chronic congestiveheart failure by heart rate spectral analysis. Am J Cordiol 1988;61:1292-1296. 9. Hayano J, Sakakibara Y, Yamada M, Ohte N, Fujinami T, Yokoyama K, WatanabeY, Takata K. Decreasedmagnitudeof heart rate spectralcomponents in coronary artery disease.Its relation to angiographic severity. Circulation 1990;81:1217-1224. 10. Bigger JT, Kleiger RE, FleissJL, Rolnitzky LM, Steinman RC, Miller JP, the Multicenter Post-Infarction ResearchGroup. Componentsof heart rate variability measuredduring healing of acute myocardial infarction. Am J Cordial 1988;61:208-212. II. Lombardi F, SandroneG, Pernpruner S, Sala R, Garimoldi M, Cerutti S, Baselli G, Pagani M, Malliani A. Heart rate variability as an index of sympatho vagal interaction after acute myocardial infarction. Am J Cardiol 198760: 1239-1245. 12. PressWH, Flannery BP,Teukolsky SA, Vetterling WT. Numerical recipesin C. New York: Cambridge University Press,1988:447-452. 13. Kay SM, Marple SL. Spectrumanalysis- a modernperspective.Proc IEEE 1981;69:1380-1384. 14. Saul JP, Albrecht P, Berger RD, Cohen RJ. Analysis of long term heart rate variability: methods,I/f scalingand implications.Cornput Cardiol1988;419-422. 15. Halberg F, CarandenteF, ComelissenG, Katinas GS. Glossaryof chronobiology. Chronobiologia 1977;IV(suppl 1)1:187. 16. Martin GJ, Magid NM, Myers G, Barnett PS, SchaalJW, Lesch M, Singer DH. Heart rate variability and suddendeathsecondaryto coronary artery disease during ambulatory electrocardiographic monitoring. Am J Curdiol 1987;60: 86-89. 17. Myers GA, Martin GJ, Magid NM, Burnett PS, Schaad JW. Weiss JS,
Lesch M, Singer DH. Power spectralanalysisof heart rate variability in sudden cardiac death: comparisonto other methods.IEEE Trans Biomed Eng 1986;33: 1149-1156. IS. Akselrod S, Gordon D, Ubel FA, ShannonDC, Barger AC, CohenRJ. Power spectrumanalysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 1981;213:220-222. 19. PomeranzB, Macaulay RJB, Caudill MA, Kutz J, Adam D, Gordon D, Kilborn KM, Barger AC, Shannon DC, Cohen RJ, BensonH. Assessmentof autonomic function in humans by heart rate spectral analysis. Am J Physio! 1985;248:H151-H153. 20. Pagani M, Lombardi F, Guzzetti S, Rimoldi 0, Furlan R, Pizzinelli P, SandroneG, Malfatto G, Bell’Orto S, PiccalugaE, Turiel M, Baselli G, Cerutti S, Malliani A. Power spectralanalysisof heart rate and arterial pressurevariabilities as a marker of sympatho-vagalinteraction in man and consciousdog. Circ Res 1986;59:178-193. 21. Vallbona C, Cardus D, SpencerWA, Hoff HE. Patternsof sinusarrhythmia in patients with lesionsof the central nervous system.Am J Cardiol 1965;16: 379-384.
22. Turton MB, DeeganT. Circadian variations of plasmacatecholamine,cortisol,and immunoreactiveinsulin concentrationsin supinesubjects.Clin Cbim Acta 1974;55:389-397.
HEART RATE VARIABILITY AND CARDIAC ARREST 615
