SEARCH

SEARCH BY CITATION

Keywords:

  • Arrhythmias;
  • Canine;
  • Heart rate variability;
  • Myxomatous mitral valve disease

Abstract

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Footnotes
  7. Acknowledgments
  8. References

Background: Few reported studies describe normal values from 24-hour ECG (Holter) recordings of small breed dogs.

Objectives: To investigate influence of breed, age, sex, body weight, degree of recording artifact, and mitral valve prolapse (MVP) on Holter recordings of 3 breeds of small dogs that have differing predispositions for myxomatous mitral valve disease. The study also assessed if heart rate (HR) at clinical examination (HRex) was associated with HR during Holter monitoring and evaluated the reproducibility of Holter variables.

Animals: Fifty clinically healthy, privately owned dogs of the breeds Cavalier King Charles Spaniel (CKCS), Wire-haired Dachshund (wD), or Cairn Terrier (CT).

Methods: Prospective, longitudinal observational study. Dogs were recruited for clinical examination, echocardiography, and Holter monitoring. In 8 CKCS, Holter recordings were performed twice with a 7-day interval. Arrhythmia and heart rate variability (HRV) analysis (time and frequency domain analysis) were performed on Holter recordings.

Results: Fifteen out of 27 Holter derived variables were significantly associated with breed (P < .03), but not with age (P > .7), sex (P > .2), body weight (P > .7), degree of recording artifact (P > .4), or MVP (P > .6). During Holter recording, minimum (P= .0001) and mean HR (P= .0001) were higher in CKCS compared with wD. CKCS had significantly lower values than wD, CT, or both in 10 out of 13 HRV variables (P < .03). Minimum and mean HR during Holter recording were correlated with HRex (r= 0.55, P= .0003). HR and time domain variables had a coefficient of variation <10%.

Conclusions and Clinical Importance: There is an influence of breed on Holter-derived variables in 3 breeds of small dogs. Arrhythmia and HRV analysis can be performed on 24-hour ambulatory ECG (Holter) recordings. Arrhythmia analysis includes HR measurements and identification of arrhythmias.

Abbreviations:
APC

atrial premature complexes

AV

atrioventricular

bpm

beats per minute

CKCS

Cavalier King Charles Spaniel

CT

Cairn Terrier

CV

coefficient of variation

HF

high frequency

HFn

normalized high frequency

Holter

24-hour ECG

HR

heart rate

HRV

heart rate variability

LF

low frequency

LFn

normalized low frequency

MMVD

myxomatous mitral valve disease

MVP

mitral valve prolapse

N

QRS complex of sinus or supraventricular origin

SVT

supraventricular tachycardia

TI

triangular index

TP

total power

ULF

ultra low frequency

VLF

very low frequency

VPC

ventricular premature complexes

VVTI

vasovagal tonus index

wD

wire-haired standard size Dachshund

The heart rate variability (HRV) analysis is a beat-to-beat analysis that mirrors influence of the autonomic nervous system on heart rhythm, presence of arrhythmia, or both. HRV analysis can be divided into a time and a frequency domain analysis and both analyses are based on measuring intervals between adjacent sinus QRS complexes.1 In the frequency domain analysis, the high frequency (HF) band is influenced by respiration and known to reflect parasympathetic modulation of heart rate (HR). The low frequency (LF) band is influenced by both parasympathetic and sympathetic activity.2–4 Breed differences in variables from Holter recordings have been documented in dogs of large and medium breed.5 In addition, breed differences are found in the vasovagal tonus index (VVTI), which is a measurement of HRV on short-time ECG.6 Moreover, increased HRV has been found in people and dogs with mitral valve prolapse (MVP).7–10 MVP is an early sign of myxomatous mitral valve disease (MMVD), which is the most common cardiac disease in dogs.11,12 Small dogs are most likely to develop MMVD, and some breeds are more likely to develop MMVD than others.12 The Cavalier King Charles Spaniel (CKCS) is at high risk for developing MMVD, whereas the Dachshund is at moderate risk12–14 and Cairn Terriers (CT) are at low risk.12,13 It is suggested that HRV changes in relation to MMVD severity are caused by autonomic dysfunction as a part of the complex pathophysiology of the disease.9,10 The aim of this study was to investigate influence of breed, age, sex, body weight, degree of recording artifact, and MVP on Holter recordings of breeds of small dogs with different predisposition for developing MMVD. The study also assessed if HR at clinical examination was associated with HR during Holter monitoring. Furthermore, the study evaluated reproducibility of arrhythmia and HRV variables.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Footnotes
  7. Acknowledgments
  8. References

Study Population

This prospective study included privately owned dogs of 3 different breeds: CKCS, Wire-haired standard size Dachshund (wD), and CT. Dogs were examined between December 2008 and June 2009. Only nonpregnant, nonlactating dogs between 2 and 9 years old were included. Dogs were not receiving systemic medication or had abnormal heart sounds. Dogs were included in the study only if their echocardiographic examination showed no or minimal mitral regurgitation (mitral regurgitant jet < 20% of the left atrial area).15 Dogs were excluded if they had signs of systemic disease on history, clinical examination, serum biochemistry, or CBC. Furthermore, dogs with <20-hour readable data on the Holter recording were excluded. All owners gave their consent. The study was approved by the Danish Animal Welfare Division.

Examination Procedure

All dogs were examined by a standardized protocol that included blood sampling, physical examination, cardiac auscultation, and echocardiography, performed in that order. HR was estimated during cardiac auscultation. Holter recording was performed within a month after echocardiographic examination. Holter recordings were performed twice with a 7-day interval in a convenience sample of 8 CKCS.

Echocardiography

Two-dimensional echocardiographya was performed and recorded for later analysis by an individual masked to identify of the dog (L.H.O.). First, left ventricular dimensions were measured by use of M-mode echocardiography performed on short-axis views at the chordae tendineae level.16 Second, the degree of MVP was evaluated in the right parasternal long axis 4-chamber view.17 Third, a short-axis view at the level of the aortic valve was used to assess the left atrial and aortic root diameter.18 Fourth, maximal aorta flow velocity was measured with pulsed wave Doppler in the left side 5-chamber view.16 Finally, a color-flow mapping of the mitral- and tricuspid valve area was performed in the left caudal 4-chamber view to evaluate the degree of mitral and tricuspid regurgitatio.15 None of the dogs were sedated during the examination and the owners were present to calm the dogs.

Holter Monitoring

A Holter recorderb was placed on the dog with a 2 lead system with electrodesc in a standard precordial placement.19 Before electrode placement, an area was prepared by shaving and cleaning the skin with alcohol. An elastic bandage and a specially designed vest were used to secure the Holter recorder and leads to the dog. All dogs wore the Holter monitor for at least 24 hours and owners were instructed to note the general activity of the dog in a diary during the monitoring period.

HR and Arrhythmia Analysis

A standardized protocol for semiautomatic arrhythmia analyses was performed by commercially available softwared and with the observer blinded to the identity of the dog. The software was designed for Holter recording in people; however, definition of events was adjusted for dogs (except the definition of bradycardia and “dropped beat”). The editing protocol included 2 main steps. Step 1 (chronological analysis): The Holter recordings were chronologically checked to ensure that the software triggered correctly on every beat. Step 2 (event analysis): Events marked by the software were manually checked to confirm correct classification. The software classifies QRS complexes of sinus and supraventricular origin as normal beats (N) and wide QRS as abnormal beats.e Bradycardia was defined as more than 4 successive N at a HR lower than 45 beats per minute (bpm). NN-intervals more than 180% longer than the previous NN-interval were defined as “dropped beats.” Sinus pauses were defined as NN-intervals longer than 2.0 seconds.20 The software registered episodes with a NN-interval 50% shorter than the previous NN-interval. These episodes were manually differentiated into atrial premature complexes (APCs) (a premature beat with abnormal P-wave morphology conducting a normal-appearing QRS complex) and “premature normals” (the remaining episodes).10,21 The software also registered episodes where an APC or a “premature normal” was followed by 2 or more successive N at a HR above 150 bpm and with NN-intervals shorter than or equal to the previous. These episodes were manually differentiated into supraventricular tachycardia (SVT) (all beats with an abnormal P-wave morphology conducting a normal appearing QRS complex) or tachycardia (remaining episodes).21,22 Complexes classified as abnormal by the software were manually differentiated into ventricular premature complexes (VPC), late VPC, RonT, ventricular escape beats, or fusion beats. VPCs should occur before a period similar to the previous NN-interval and were defined as wide and bizarre looking QRS complexes, not associated with a P-wave, but accompanying a large T-wave of opposite polarity.21 Late VPC was defined as a VPC occurring within a period longer than the previous NN-interval but shorter than 2 seconds. RonT was defined as a VPC occurring before the previous T-wave returned to baseline21 and registered based on a software defined equation.e Ventricular escape beats were defined as wide QRS complexes of different orientation occurring after a sinus pause.21 A fusion beat was defined as a normal P-wave followed by an intermediate-shaped QRS complex.23 Second-degree atrioventricular (AV) block was manually registered during the chronological analysis.21

HRV Analysis

HRV analysis was performed by commercially available softwaref including both time- and frequency-domain analysis. HRV analysis was carried out automatically by the software on Holter recordings already processed through the arrhythmia analysis protocol. Abnormal beats, defined by the arrhythmia analysis software, were not included in the HRV analysis. The HRV analysis was divided into 4 analysis periods: 24-hours, 6-hours inactivity, 1-hour activity, and 1-hour inactivity. The 1-hour activity period started 90 minutes before the dog went to sleep (bedtime) and the 6- and 1-hour inactivity period started 30 minutes after bedtime. The diary was used to identify bedtime for the dog. If bedtime was not noted in the diary, it was defined as the 1st period of 10 minutes after 9:00 pm with a HR below mean HR during Holter recording. Analysis periods with <90% valid NN-intervals, decided by the software, were excluded from all statistical analyses. All 4 periods were analyzed in 1-time segment using nonaveraged power spectral density. Total power (TP) (0–0.4 Hz) was divided into the following frequency bands: ultra low frequency (ULF): 0–0.00333 Hz, very low frequency (VLF) 0.00333–0.04 Hz, LF 0.04–0.15 Hz, and HF 0.15–0.4 Hz. Gaps longer than 2.5 seconds were interpolated to sample rate (4 Hz) using a curved interpolation (Cubic Spline). Linear subtraction was used to remove constant offset or bias in the rhythm data and a Hamming window was used as algorithm to reduce frequency artifacts. The 24-hour period included 524,288 samples (178,688 zero padding). LF and HF were adjusted for TP and lower frequencies by normalizing LF and HF (LFn and HFn) by the following formula: LFn = LF/(TP−ULF−VLF) × 100 and HFn = HF/(TP−ULF−VLF) × 100. Besides the above-mentioned frequencies, the following HRV variables were also included in the study: HF/LF, mean of all NN-intervals (MEAN), % of successive NN-intervals differing more than 50 ms (pNN50), square root of the mean squared differences of successive NN-intervals (RMSSD), standard deviation of the NN-intervals (SD), and triangular index (TI) (total number of NN-intervals/maximum number of NN-intervals of equal length measured on a discrete scale with bins of 1/128s).g

Statistical Analysis

Data are expressed as mean ± standard deviation unless otherwise noted. All statistical analyses were performed with commercially available software. All shown P-values, except from posthoc test, were Bonferroni's adjusted. Analyses of variance were used to test arrhythmia and HRV variables for influence of breed, body weight, age, sex, degree of recording artifact, and MVP (P < .0008). Interactions between MVP and breed, MVP and age and in addition, breed and age were included in the statistical model if indicated by visual inspection of the distributions. Stepwise backwards elimination was used in all models until only statistically significant variables remained. Model control was performed by testing residuals for homogeneity of variation and Gaussian distribution by residual plot and Shapiro-Wilks test, respectively. Data were transformed if model control failed, and if transformed data failed the model control, data was tested separately via appropriate nonparametric tests. If a breed had a statistically significant influence on an arrhythmia or HRV variable, Students t-test or Wilcoxon's Signed Ranks test was used as posthoc test (P < .05). Spearman's correlation was used to test for association between HR at clinical examination and maximum, minimum, and mean HR during Holter recording (P < .02). To assess reproducibility, Wilcoxon's matched pairs test was used to test for difference in arrhythmia and HRV variables between the 2 Holter recordings from the same dog (P < .0008). Furthermore, reproducibility was evaluated based on coefficient of variation (CV). A CV was separately calculated for each dog (CVdog= standard deviation 1–2 weeks/mean 1–2 weeks × 100) and a CV for the variable was calculated as the mean CVdog for the 8 dogs (CVvariable= mean CVdog 1, 2, 3, …, 8).

Results

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Footnotes
  7. Acknowledgments
  8. References

Data were collected from 57 dogs: 23 CKCS, 18 wD, and 16 CT. However, 7 dogs were excluded from the study because of the presence of preexcitation (1 CT), high serum concentration of bile acids (1 CT), suspicion of Cushing's disease (1 CT), and <20 hours of readable data on the Holter recording (2 CKCS and 2 wD). The characteristics of the 50 remaining dogs (21 CKCS, 16 wD, and 13 CT) are shown in Table 1. Three CKCS and 1 wD had an innocent flow-murmur grade I. It was not possible to draw blood from 1 CT, but this dog appeared clinically healthy and all statistical analyses were statistically the same whether this dog was included or not. None of the dogs had tricuspid regurgitation.

Table 1.   Characteristics of the 50 small dogs.
 All DogsCKCSwDCT
  • CKCS, Cavalier King Charles Spaniels; wD, Wirehaired Dachshunds; CT, Cairn Terriers; HR, heart rate; bpm, beats per minute; LVIDd, left ventricular end diastolic diameter; LVIDs, left ventricular end systolic diameter; LVWd, left ventricular free wall thickness in diastole; LVWs, left ventricular free wall thickness in systole; IVSTd, interventricular septal thickness in diastole; IVSTs, interventricular septal thickness in systole.

  • Data are expressed as mean ± standard deviation. Left ventricular dimensions are given as percentage difference from the expected dimension (diff).24

  • *

    P < .05 difference from CKCS.

  • **

    P < .05 difference from CT.

n50211613
Sex (M/F)20/309/126/105/8
Intact dogs (M/F)16/258/124/75/6
Age (years)5.2 ± 1.85.1 ± 1.65.5 ± 2.15.1 ± 1.9
Body weight (kg)9.6 ± 1.99.3 ± 1.710.2 ± 1.99.4 ± 2.1
HR (bpm)107.4 ± 18.9120.4 ± 11.795.0 ± 18.7*102.4 ± 15.5*
IVSTd diff (%)13.5 ± 16.216.2 ± 14.99.9 ± 15.413.8 ± 20.0
IVSTs diff (%)11.1 ± 16.214.8 ± 19.45.9 ± 12.111.6 ± 13.9
LVIDd diff (%)− 4.0 ± 9.2− 0.5 ± 8.9− 5.5 ± 9.0− 7.8 ± 8.5
LVIDs diff (%)− 1.9 ± 18.04.9 ± 14.6**1.1 ± 16.8**− 16.3 ± 17.5
LVPWd diff (%)16.9 ± 13.618.2 ± 12.213.2 ± 14.619.1 ± 14.7
LVPWs diff (%)3.9 ± 17.0− 0.7 ± 13.50.1 ± 9.116.1 ± 23.6
FS (%)33.7 ± 8.031.5 ± 6.6**30.5 ± 7.9**41.5 ± 9.9
LA/Ao (ratio)1.3 ± 0.11.3 ± 0.11.3 ± 0.11.4 ± 0.1
Mitral valve prolapse (mm)0.9 ± 0.73.2 ± 2.3**3.3 ± 2.2**− 0.1 ± 1.8
Max. aorta flow (m/s)1.4 ± 0.31.3 ± 0.1**1.3 ± 0.2**1.6 ± 0.3

HR and Arrhythmia Analysis

The CKCS had statistically significant higher minimum HR during Holter recording compared with wD and CT (Table 2). CKCS also had a statistically significantly higher mean HR compared with wD (P= .0001), but maximum HR was not related to breed. During the 24-hour recording period CT and wD had statistically significantly more episodes of sinus pauses than CKCS (712 ± 1,113, 551 ± 388, and 26 ± 63, respectively, all P= .0001). Furthermore, CT had statistically significantly more episodes of sinus pauses than wD (P= .03). Moreover, wD had statistically significantly more episodes of “premature normals” than CKCS (1,650 ± 1,755 versus 404 ± 471, P= .0006) and CT (651 ± 1,250, P= .0009). The occurrence of bradycardia, tachycardia, SVT, “dropped beats,” 2nd-degree AV-block, APCs, VPCs, escape or fusion beats were not associated with breed, age, sex, body weigh, recording artifact, or MVP. Fifty-six percent of the dogs had 2nd-degree AV-block (all: median 1, [range 0–5,210 episodes in 24-hours], CKCS: 1 [0–139], wD: 0 [0–5,210], and CT: 66 [0–2,351]). All 2nd-degree AV-blocks had a 2 : 1 conduction ratio, except 2 CT with 1 and 8 episodes of 3 : 1 conduction, respectively. Sixteen percent of the dogs had APCs and 25% had VPCs. The numbers of APCs and VPCs are shown in Figure 1. Related to the total number of QRS complexes in the Holter recording, all dogs had <0.01 APCs and 0.02% VPCs, except 2 dogs which had 0.16 APCs and 0.16% VPCs. The majority of VPCs were single, isolated, and monomorphic. However, 1 CKCS had polymorphic VPCs, 1 CKCS had a 9 beat long ventricular bigeminy, 2 CKCS and 1 wD had <3 RonTs, and finally, <2 late VPCs were seen in 2 CKCS. None of the dogs had escape beats, except 1 wD that had 32 ventricular escape beats. Three CKCS, 2 wD, and 2 CT had <2 fusion beats.

Table 2.   Heart rate during Holter monitoring in 3 breeds of small dogs.
BreedAll Dogs (n= 50)CKCS (n= 21)wD (n= 16)CT (n= 13)
  • CKCS, Cavalier King Charles Spaniels; wD, Wirehaired Dachshunds; CT, Cairn Terriers; HR, heart rate; bpm, beats per minute.

  • Values are expressed as mean ± standard deviation.

  • *

    Significantly lower HR compared with CKCS (P < .015).

Maximum HR (bpm)181.9 ± 29.8191.7 ± 35.9167.4 ± 20.6184.8 ± 22.8
Minimum HR (bpm)46.8 ± 8.351.7 ± 7.541.8 ± 6.6*45.3 ± 7.2*
Mean HR (bpm)75.5 ± 12.382.4 ± 12.867.3 ± 7.5*74.9 ± 10.3
image

Figure 1.  Graphs showing the total number of atrial premature complexes (APCs) (A) and ventricular premature complexes (VPCs) (B) during 24 hours in 21 CKCS, 16 wD, and 13 CT. There is no statistically significant difference in the occurrence of APCs or VPCs between the 3 dog breeds. Please note that the Y-axis is divided in 2 segments. CKCS, Cavalier King Charles Spaniels; wD, Wire-haired Dachshunds; CT, Cairn Terriers.

Download figure to PowerPoint

HRV Analysis

In the frequency and time domain analysis, CKCS had statistically significantly lower values in 10 out of 13 variables compared with wD, CT, or both (Figs 2 and 3). In the 6-hour inactivity period, breed influenced 8 out of 13 HRV variables (Figs 2 and 3). None of the frequency or time domain variables were associated with age, sex, body weight, recording artifact, or MVP.

image

Figure 2.  Graphs showing frequency domain analysis values for 3 dog breeds in 4 analysis periods. P-values for the statistical test of each analysis period are displayed on the right side of the graphs. The 6- and 1-hour inactivity heart rate variability (HRV) analysis period included 50 dogs, but a few dogs were excluded from the 24-hour and 1-hour activity HRV analysis periods (because of <90% valid NN-interval). Consequently, the 24-hour HRV analysis included 48 dogs (21 CKCS, 14 wD, and 13 CT) and the 1-hour activity HRV analysis included 48 dogs (21 CKCS, 15 wD, and 12 CT). Whiskers represent interquartile range and the following symbols represents median for 3 dog breeds ▴, CKCS; •, wD; ▪, CT; *, significantly lower compared with the 2 other breeds; $, significantly lower compared with wD; inline image, significantly lower compared to CT; #, data tested nonparametrically. See text for abbreviations and for definition of NN-interval, frequency domain variables, and analysis periods.

Download figure to PowerPoint

image

Figure 3.  Graphs showing time domain analysis values for 3 dog breeds in 4 analysis periods. P-values for the statistical test of each analysis period are displayed on the right side of the graphs. The 6- and 1-hour inactivity heart rate variability (HRV) analysis period included 50 dogs, but a few dogs were excluded from the 24-hour and 1-hour activity HRV analysis periods (because of <90% valid NN-interval). Consequently, the 24-hour HRV analysis included 48 dogs (21 CKCS, 14 wD, and 13 CT) and the 1-hour activity HRV analysis included 48 dogs (21 CKCS, 15 wD, and 12 CT). Whiskers represent standard deviation and the following symbols represents mean for 3 dog breeds ▴, CKCS; •, wD; ▪, CT; *, significantly lower compared with the 2 other breeds; $, significantly lower compared with wD. See text for abbreviations and for definition of NN-interval, time domain variables, and analysis periods.

Download figure to PowerPoint

Correlation between HR at Clinical Examination and during Holter Monitoring

Minimum and mean HR during Holter recording were positively correlated with HR at clinical examination (Fig 4), but maximum HR was not correlated with HR at clinical examination.

image

Figure 4.  Correlations between heart rate at clinical examination and minimum and mean heart rate during 24-hour Holter recording. Spearman's correlation coefficient r and P-value are shown above the plot. HR, heart rate.

Download figure to PowerPoint

Reproducibility

None of the arrhythmia or HRV variables were statistically significantly different between the 2 Holter recordings from the same dog. High reproducibility was seen for maximum HR (mean CV 8%, range 2–18%), minimum HR (4, 0–13), and mean HR (4, 0.8–6) during the Holter recording. The remaining arrhythmia variables showed greater CVs: bradycardia (81, 0–141), sinus pause (115, 28–141), dropped beat (40, 9–68), “premature normals” (31, 1–60), APC (37, 0–141), tachycardia (36, 3–114), SVT (35, 0–114), and VPC (47, 0–141). None of the 8 dogs selected for studying reproducibility had escape or fusion beats. In general, time domain variables showed high reproducibility in the 24-hour analysis period (CV < 10%) (Table 3).

Table 3.   Coefficient of variation for heart rate variability.
HRV Variables/Analysis Period24-Hours (%)6-Hours (%)1-Hour Activity (%)1-Hour Inactivity (%)
  1. The table shows the coefficient of variation for HRV variables measured twice with a 7-day interval in 8 CKCS. Values are expressed as mean (min.–max.). Because a few dogs had <90% valid NN-intervals, n= 6 for all 4 HRV analysis periods (the excluded dogs were not the same in all analysis periods). Se text for abbreviations and for definition of NN-interval, HRV variables, and analysis periods.

TP17.126.915.636.4
(3.2–28.6)(6.1–67.9)(3.1–60.2)(4.5–68.6)
ULF19.241.929.568.5
(3.9–31.2)(17.5–94.8)(18.8–43.0)(33.6–118.4)
VLF17.225.614.327.8
(3.5–25.4)(16.3–39.4)(1.6–32.9)(4.4–60.1)
LF22.331.028.138.0
(0.5–59.0)(1.0–123.8)(2.3–47.4)(8.0–82.1)
HF16.823.532.145.6
(1.5–38.0)(4.1–40.2)(5.0–105.0)(3.5–80.9)
LFn11.528.925.534.7
(1.0–36.3)(1.9–101.2)(9.3–38.8)(11.0–62.5)
HFn4.28.226.212.9
(0.8–9.8)(0.4–27.5)(1.2–66.0)(0.0–29.5)
HF/LF15.133.441.744.9
(0.5−45.1)(0.4–112.9)(10.3–76.6)(5.9–75.3)
MEAN4.34.37.16.2
(1.6–6.1)(2.7–7.8)(0.2–19.5)(3.4–9.3)
pNN505.22.413.45.1
(0.3–10.9)(0.7–4.3)(3.8–34.4)(1.4–8.2)
RMSSD10.011.318.117.3
(2.4–18.8)(0.2–21.2)(3.7–42.4)(8.6–27.4)
SD8.713.58.517.3
(0.7–17.0)(1.4–31.7)(0.6–25.8)(3.8–31.8)
TI8.69.212.521.5
(1.4–14.8)(0.3–26.5)(5.1–22.1)(9.1–42.0)

Discussion

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Footnotes
  7. Acknowledgments
  8. References

This study showed that CKCS, compared with wD, had a higher minimum and mean HR during Holter recording and fewer episodes of “premature normals” and that CKCS had fewer episodes of sinus pauses compared with both wD and CT. CKCS had lower HRV, which was confirmed as CKCS had lower values of many HRV variables compared with those of wD and CT. However, the statistical differences between CKCS and the 2 other breeds were most apparent in the 6-hour inactivity period. Minimum and mean HR during Holter recording was moderately correlated with HR at the clinical examination. HR during Holter recording and all time domain variables in the 24-hour period showed high reproducibility (CV < 10%).

To minimize total variability this study was based on a standardized protocol, included only pure breed dogs of 3 specified breeds and echocardiographic, arrhythmia, and HRV variables were evaluated by trained observers being blinded to the identity of the dogs. All Holter recordings in this study were carefully manually edited because of the use of a Holter analysis software designed for people.

Breed differences exist in arrhythmia variables from Holter recordings of Cocker Spaniels, Boxers, and Dobermans.5 Moreover, the short-time ECG HRV variable, VVTI are influenced by breed.6 The present study also showed breed differences in both arrhythmia and HRV variables, which suggests that breed should be taken into account when evaluating Holter recordings. The high HR found in CKCS in this study could be associated with high sympathetic modulation of HR. However, in the HRV analysis CKCS had low LF and LFn values, which are related to low sympathetic tone.

Age, sex, and body weight have previously been associated with HRV variables in people and dogs.3,9,25–27 However, other studies in dogs find no association between age and HRV28 or between body weight and HR.29 In the present study, age, sex, and body weight were not associated with arrhythmia or HRV variables. The association in people clearly demonstrates decreasing HRV with increasing age and lower HRV in women.3,25–27

Autonomic dysfunction is suggested to play a role in the pathophysiology of MMVD. There is a positive association between HRV and MVP in healthy dogs.9,10 However, the present study did not detect associations between MVP and arrhythmias or HRV variables. The lack of association might be explained by the minimal degree of disease in dogs included in this study. Studies in people concerning MVP and HRV have conflicting evidence.7,8,30

HR measured from short-time ECG during in the clinical examination does not reliably estimate mean HR during Holter recording of dogs with heart failure and atrial fibrillation.31 This study demonstrates a correlation between HR estimated by auscultation at clinical examination and minimum and mean HR during Holter recording. However, minimum and mean HR during Holter monitoring cannot accurately be predicted from HR at clinical examination. Spontaneous variability accounted for 80% of VPCs in a Holter study performed on Boxers with arrhythmogenic right ventricular hypertrophy.32 Although the number of VPCs in this study is much lower, our results also suggest a large spontaneous variability of VPCs (CV 47.4%). In people with various heart diseases, the spontaneous variability of VPCs was 83%.33 The present study and a study of healthy Dobermans showed higher reproducibility of the time domain variables than the frequency domain variables. In addition, both studies showed a higher reproducibility in the 24-hour analysis period compared with a night or inactivity period of shorter duration.34 Studies in people have also shown high reproducibility of time domain variables measured over a 24-hour period.26,35

It is remarkable that CKCS, the dog breed included in this study at highest risk for developing MMVD, overall had lower HRV values compared with both wD and CT. It is also interesting that CKCS had a higher HR at clinical examination compared with wD and CT and a higher minimum and mean HR during Holter recording compared with wD. Further studies are needed to clarify if these findings and CKCS having lower HRV play a role in the pathophysiology of MMVD and are related to CKCS being predisposed for developing MMVD.

In conclusion, many HRV variables were influenced by breed, but no variables were influenced by age, sex, body weight, recording artifact, or MVP. CKCS differed most prominently from wD by having higher HR and lower HRV. HR measured at clinical examination was moderately correlated with minimum HR and mean HR during Holter monitoring. Furthermore, the study showed high reproducibility of HR and time domain variables during 24-hours Holter monitoring.

Limitations

The Holter analysis software does not mark APCs as abnormal beats and therefore APCs are included in the HRV analysis, which might have influenced the HRV variables in the study. In addition, the HRV analysis software does not include gaps longer than 2.5 seconds, which could bias ULF and VLF in dogs with longer sinus pauses. Only 8 dogs of the same breed was examined to assess reproducibility.

Footnotes

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Footnotes
  7. Acknowledgments
  8. References

aVivid I Echocardiograph, GE-Medical, Milwaukee, WI

bLifecard CF Digital Holter Recorder, SPACELABS Healthcare Company (previously Delmar Reynolds), Issaquah, WA

c3M Red Dot Electrodes, 3M, St Paul, MN

dPathfinder digital Holter Analysis System V8.701, SPACELABS Healthcare Company (previously Delmar Reynolds)

ePathfinder 700/600/500 Instruction manual ©2004. Delmar Reynolds Medical Limited, Hertford, England. Drawing No. 038/0360/0 Issue 1 CN 4340. Part no 18-6032

fHRV Tools Software Package Version 1.73, SPACELABS Healthcare Company (previously Delmar Reynolds)

gHRV Tools. Installation and instruction manual. ©2004 Delmar Reynolds Medical Limited, Hertford, England. Drawing No. 038/0369/0 Issue 2 CN 4657. Part No 18-0369

Acknowledgments

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Footnotes
  7. Acknowledgments
  8. References

The authors thank Birgitte Holle, Christina Tirsdal Kjempff, Dennis Jensen, and Hanne Carlsson at the Department of Basic Animal and Veterinary Sciences, University of Copenhagen, Frederiksberg, Denmark for their excellent technical assistance. Furthermore, we thank Professor N. Sydney Moïse from Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York for her comments and advice regarding arrhythmia and HRV analysis.

The study was supported by the Danish Council of Independent Research Medical Sciences (project no. 271-08-0998 and 271-05-03335) and Synergy in Human and Animal Research (SHARE), Faculty of Life Sciences, University of Copenhagen.

References

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Footnotes
  7. Acknowledgments
  8. References
  • 1
    Stein PK, Bosner MS, Kleiger RE, Conger BM. Heart rate variability: A measure of cardiac autonomic tone. Am Heart J 1994;127:13761381.
  • 2
    Akselrod S, Gordon D, Ubel FA, et al. Power spectrum analysis of heart rate fluctuation: A quantative probe of beat-to-beat cardiovascular control. Science 1981;213:220222.
  • 3
    Pagani M, Lombardi F, Guzzetti S, et al. Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympathovagal interaction in man and conscious dog. Circ Res 1986;59:178193.
  • 4
    Strauss-Blasche G, Moser M, Voica M, et al. Relative timing of inspiration and expiration affects respiratory sinus arrhythmia. Clin Exp Pharmacol Physiol 2000;27:601606.
  • 5
    Neto ML, Larsson MHMA, Pereira L, Brito FS. Standardization of the 24-hour electrocardiographic monitoring in dogs. Arq Bras Med Vet Zootec 2002;54:133138 (Portuguese).
  • 6
    Doxey S, Boswood A. Differences between breeds of dogs in a measure of heart rate variability. Vet Rec 2004;154:713717.
  • 7
    Boudoulas H, Kolibash AJ, Baker P, et al. Mitral valve prolapse and the mitral valve prolapse syndrome: A diagnostic classification and pathogenesis of symptoms. Am Heart J 1989;118:796818.
  • 8
    Frisinghelli A, Turiel M, Milletich A, et al. The role of mitral regurgitation in the neurovegetative regulation of mitral valve prolapse. Cardiologia 1992;37:781783 (Italian).
  • 9
    Olsen LH, Mow T, Koch J, Pedersen HD. Heart rate variability in young clinically healthy Dachshunds: Influence of sex, mitral valve prolapse status, sampling period and time of day. J Vet Cardiol 1999;1:715.
  • 10
    Pedersen HD. Mitral Valve Prolapse in the Dog. Pathogenesis, Pathophysiology, Diagnosis and Comparative Aspects of Early Myxomatous Mitral Valve Disease. The Royal Veterinary and Agricultural University, Copenhagen, Denmark; 2000. Thesis.
  • 11
    Pedersen HD, Häggström J. Mitral valve prolapse in the dog: A model of mitral valve prolapse in man. Cardiovasc Res 2000;47:234243.
  • 12
    Thrusfield MV, Aitkent CGG, Darke PGG. Observations on breed and sex in relation to canine heart valve incompetence. J Small Anim Pract 1985;26:709717.
  • 13
    Egenvall A, Bonnett BN, Häggström J. Heart disease as a cause of death in insured Swedish dogs younger than 10 years of age. J Vet Intern Med 2006;20:894903.
  • 14
    Olsen LH, Fredholm M, Pedersen HD. Epidemiology and inheritance of mitral valve prolapse in Dachshunds. J Vet Intern Med 1999;13:448456.
  • 15
    Pedersen HD, Häggström J, Falk T, et al. Auscultation in mild mitral regurgitation in dogs: Observer variation, effects of physical maneuvers, and agreement with color Doppler echocardiography and phonocardiography. J Vet Intern Med 1999;13:5664.
  • 16
    Thomas WP. Two-dimensional, real-time echocardiography in the dog: Technique and anatomic validation. Vet Radiol 1984;25:5064.
  • 17
    Pedersen HD, Olsen LH, Mow T, Christensen NJ. Neuroendocrine changes in Dachshunds with mitral valve prolapse examined under different study conditions. Res Vet Sci 1999;66:1117.
  • 18
    Häggström J, Hansson K, Karlberg BE, et al. Plasma concentration of atrial natriuretic peptide in relation to severity of mitral regurgitation in Cavalier King Charles Spaniels. Am J Vet Res 1994;55:698703.
  • 19
    Petrie JP. Practical application of Holter monitoring in dogs and cats 3. Clin Tech Small Anim Pract 2005;20:173181.
  • 20
    Hall LW, Dunn JK, Delaney M, Shapiro LM. Ambulatory electrocardiography in dogs. Vet Rec 1991;129:213216.
  • 21
    Kittleson MD. Diagnosis and treatment of arrhytmias (dysrhythmias). In: KittlesonMD, KienleRD, eds. Small Animal Cardiovascular Medicine. St Louis, MO: Mosby; 1998:449494.
  • 22
    Kligfield P, Devereux RB. Arrythmia in mitral valve prolapse. In: PodridPJ, KoweyPR, eds. Cardiac Arrhythmias: Mechanisms, Diagnosis and Management. Philiadelphia, PA: Williams and Wilkins; 1995:12531266.
  • 23
    Tilley LP. Analysis of common canine cardiac arrhythmias. In: CannCC, HunsbergerSL, eds. Essentials of Canine and Feline Electrocardiography. Malvern, PA: Lea & Febiger; 1992:127207.
  • 24
    Cornell CC, Kittleson MD, la Torre P, et al. Allometric scaling of M-mode cardiac measurements in normal adult dogs. J Vet Intern Med 2004;18:311321.
  • 25
    Yeh JR, Sun WZ, Shieh JS, Huang NE. Investigating fractal property and respiratory modulation of human heartbeat time series using empirical mode decomposition. Med Eng Phys 2010;32:490496.
  • 26
    Van Hoogenhuyze D, Weinstein N, Martin GJ, et al. Reproducibility and relation to mean heart rate of heart rate variability in normal subjects and in patients with congestive heart failure secondary to coronary artery disease. Am J Cardiol 1991;68:16681676.
  • 27
    Zhang J. Effect of age and sex on heart rate variability in healthy subjects. J Manipulative Physiol Ther 2007;30:374379.
  • 28
    Minors SL, O'Grady MR. Heart rate variability in the dog: Is it too variable? Can J Vet Res 1997;61:134144.
  • 29
    Lamb AP, Meurs KM, Hamlin RL. Correlation of heart rate to body weight in apparently normal dogs. J Vet Cardiol 2010;12:107110.
  • 30
    Marangoni S, Scalvini S, Mai R, et al. Heart rate variability assessment in patients with mitral valve prolapse syndrome. Am J Noninvas Card 1993;7:210214.
  • 31
    Gelzer AR, Rishniw M, Kraus MS. In-hospital electrocardiography overestimates 24-hour ventricular rate in dogs with atrial fibrillation. Proceedings of the American College of Veterinary Internal Medicine (ACVIM) Forum, Montréal, Canada, 2009:80.
  • 32
    Spier AW, Meurs KM. Evaluation of spontaneous variability in the frequency of ventricular arrhythmias in Boxers with arrhythmogenic right ventricular cardiomyopathy. J Am Vet Med Assoc 2004;224:538541.
  • 33
    Morganroth J, Michelson EL, Horowitz LN, et al. Limitations of long-term electrocardiographic monitoring to assess ectopic ventricular frequency. Circulation 1978;58:408414.
  • 34
    Calvert CA, Wall M. Evaluation of stability over time for measures of heart rate variability in overtly healthy Doberman Pinschers. Am J Vet Res 2002;63:5359.
  • 35
    Kleiger RE, Bigger JT, Bosner MS, et al. Stability over time of variables measuring heart rate variability in normal subjects. Am J Cardiol 1991;68:626630.