Evaluating heart rate variability by a novel stethoscopic approach to minimise stress in cats

Abstract

Objectives

Stress associated with manipulation during electrocardiography (ECG) recording in cats potentially limits the assessment of autonomic function through heart rate variability (HRV) in the feline population. This study proposed an alternative, cat friendly, stethoscopic approach to evaluate HRV with an easily acquired vasovagal tonus index (VVTI).

Methods

The aim of this prospective study was to evaluate whether VVTI derived from heart sound signals could distinguish between relaxed and stimulated states. A total of 29 cats with 56 recordings of heart sound and ECG on 31 occasions were included. In 25 cats in their home environment, a stethoscope connected to a digital recording device was used to record 2 mins of heart sounds twice – with the cats in a relaxed state and immediately after stimulation. The VVTI was calculated from 20, 60 and 120 consecutive beat-to-beat intervals on the heart sound spectrogram (stethoscopic-VVTI 20, 60 and 120), using the natural logarithm of the variance of the intervals based on previous literature. A 2-min ECG recording was obtained at home with the intention of avoiding strict restraint. To demonstrate the feasibility of the stethoscopic approach in a hospital setting, six cats (two of which were also recorded at home) underwent heart sound and ECG recordings during planned veterinary visits.

Results

Stethoscopic-VVTI 20 (5.43 to 4.79, P = 0.001), 60 (6.20 to 5.18, P <0.001) and 120 (6.24 to 5.60, P = 0.02) all significantly decreased after stimulation, indicating a reduced vasovagal tone as expected. Calculations of stethoscopic-VVTI from different sections of the recording yielded statistically similar results. Stethoscopic-VVTI showed a negative correlation with the corresponding heart rate. Bland–Altman analysis revealed a mean bias for the differences between stethoscopic-VVTI and ECG-VVTI of 0.50 and 1.07 at home and in the hospital, respectively.

Conclusions and relevance

VVTI can be successfully detected through a stethoscopic approach, serving as a less stressful tool for HRV evaluation in cats during routine auscultation.

Keywords

Auscultation autonomic tone cat friendly digital stethoscope heart rate variability vasovagal tonus index welfare

Introduction

Heart rate variability (HRV) evaluates the beat-to-beat variation of the heart. It is influenced by a broad range of factors, including sympathovagal balance, endocrine functions and diurnal rhythms, analysed using various techniques with differing recording lengths.^1,2 This non-invasive methodology for assessing dysregulation in the autonomic nervous control has been applied across various species, including humans and dogs, in the evaluation of cardiovascular diseases,^3–7 respiratory or sleep-associated disorders,^8–10 endocrinopathy^11,12 and other systemic diseases.^13,14 Conversely, HRV is less well characterised in cats and currently provides only limited understanding¹⁵; yet it has recently been applied to study hypertrophic cardiomyopathy in a colony of Maine Coon-cross cats that were bred and raised at a research laboratory.¹⁶ The vasovagal tonus index (VVTI) is an easily acquired time-domain analysis of HRV, representing the natural logarithm of variations in the R-R interval from a brief electrocardiographic (ECG) recording and primarily indicating rapid changes in parasympathetic tone in dogs.^1,7,17 Though HRV measurements over 24 h and short-term periods are not interchangeable owing to circadian rhythms and differing physiological influences, short-term or ultra-short-term HRV is still considered an efficient tool for both clinical and research purposes in the field of human medicine.¹⁸ Previous canine studies have shown that a decrease in VVTI was correlated with an increased severity of mitral valve disease,^1,7 and an increase in VVTI indicated a higher parasympathetic tone.¹⁷

In cats, the application of VVTI is limited in the current veterinary literature. To the authors’ knowledge, only two studies have investigated the use of VVTI in cats.^19,20 One study found an increase in VVTI after the study cats received a sedative medication, suggesting enhanced parasympathetic tone under sedation.²⁰ The other study reported no difference in VVTI in cats between home environments and hospital settings, despite a significantly higher heart rate (HR) observed at a hospital setting than at home.¹⁹ Otherwise, potential factors influencing VVTI, such as the different numbers of heartbeats in dogs’ calculations,²¹ remain unexplored in cats.

Emotional stress can significantly influence HRV in dogs.²² Consequently, the evaluation of VVTI may require animals to maintain recumbency for a variable period to acclimatise to the ECG clips in canine studies.^7,21 Cats are highly sensitive to manipulations, and the consequential stress not only affects the assessment of HRV but can also result in false clinical findings due to emotional bias, as well as pose further difficulties with handling at subsequent visits.²³ While VVTI can serve as a useful tool to benefit animal welfare because of its simplicity and brief duration, the dilemma in cats is that obtaining an ECG requires shaving and restraining, potentially limiting its use in HRV evaluation in the feline population. In contrast, auscultation is typically well tolerated with minimal stress, and heart sound digital recorders and phonocardiography have become readily available, with increased clinical application in cats.^24,25 Therefore, the aims of this study were to propose an alternative, cat friendly method to obtain VVTI in cats using a stethoscopic approach (stethoscopic-VVTI) and to compare VVTI values obtained using different numbers of consecutive heartbeats with this approach.

We hypothesised that stethoscopic-VVTI would demonstrate alterations in vagal tone across different emotional states, significantly decreasing in response to stimulation. In addition, stethoscopic-VVTI was calculated from the variances of 20, 60 and 120 heart beat-to-beat intervals, which were compared to determine the adequate length of the recording.

Materials and methods

Study design

Cats that were visited at home were prospectively recruited from veterinary students, university staff and pet owners who consented to participate in this study. In addition, cats with pre-scheduled hospital appointments were included in the study to test the feasibility of stethoscopic recording during veterinary visits; the pre-scheduled nature of these appointments avoided unnecessary transportation and stress. Cats were not excluded if they had mild but stable illness (eg, chronic gastrointestinal, respiratory or ocular problems), but these were documented for future analytical purposes. Cats that were critically ill, extremely uncooperative or easily aroused even in their home environments were excluded. The study was approved by the Institutional Animal Care and Use Committee (approval numbers NTU-109-EL-00182 and NTU-111-EL-00007) at the authors’ institutions. In total, 29 cats, with 56 recordings of heart sounds and ECG collected during 25 and six occasions at home and in the hospital, respectively, were included in the final analysis.

A total of 25 cats were visited in their homes by the same investigator, and the cats’ emotional status was assessed and reported by their owners. After a period of acclimation for the cat to adapt to the presence of the visitor, heart sounds and ECG were recorded in the home environment. Heart sounds were recorded twice: once while the cat was relaxed and calm, and also immediately after the owner performed an action to stimulate the cat to change its emotional status (eg, exercise, playing games, showing the cat the carrier to go out, etc; this was determined based on the owner’s evaluation of each cat’s characteristics). An ECG recording was also attempted at home during the same visit, though not simultaneously with the heart sound recording, with the intention of minimising strict restraint.

To evaluate the feasibility of the stethoscopic approach in a hospital setting, recordings of heart sounds and ECG were obtained from six cats during their scheduled veterinary visits by the same investigator. Among these six cats, two also had recordings taken in their home environment.

Stethoscopic-VVTI acquisition by auscultation

Auscultation was performed by the same investigator (CRC) using a conventional stethoscope (Littmann Master Cardiology; 3M) attached to a Bluetooth-enabled device (CORE Digital Attachment; Eko) for digital recording of heart sounds on the cat’s chest at the cardiac apex. The cardiac audio filter was chosen for all recordings. Each auscultation lasted for 2 mins and the phonocardiographic signals were wirelessly transmitted to a mobile device. Spectrographic phonocardiography was subsequently generated using fast Fourier transformation with freeware software (Audacity 3.4.1), setting a window size of 128, a zero padding factor of 64 and a Hann window type to optimise the visibility of heart sound signals (Figure 1). The first or second heart sound with the best signal clarity on the spectrogram was chosen to measure the beat-to-beat intervals using freeware medical imaging software (NIH ImageJ; NIH). The stethoscopic-VVTI was calculated as the natural logarithm of the variance of the beat-to-beat intervals for 20 (stethoscopic-VVTI 20), 60 (stethoscopic-VVTI 60) and 120 (stethoscopic-VVTI 120) consecutive heartbeats, following the methodology in previous feline and canine literature: VVTI = Ln(SD_RR)².^1,7,17,19,20 The stethoscopic-VVTI 20 was calculated twice, at the beginning and in the late period of the 2-min recording to evaluate its repeatability.

Figure 1

Spectrographic phonocardiography generated using freeware software (Audacity 3.4.1), with examples from two cats. Red solid triangles and hollow triangles represent two alternating heart sounds. White double arrows indicate the beat-to-beat intervals measured in milliseconds (ms)

ECG recording

The ECG recording (Bee; Beecardia) was obtained in unsedated cats, with electrodes connected using either alligator clips or patches attached to the cats’ skin. In the home environment, the cat was allowed to assume either a right lateral recumbency or another acceptable position, as no strict restraint would be applied. In a hospital setting, a standard six-lead ECG recording was acquired with the cat in right lateral recumbency. The ECG signal was recorded for at least 2 mins, ensuring a clear baseline and obtaining the R wave.

Statistical methods

Statistical analyses were conducted using SPSS version 26 (IBM Corp). The Shapiro–Wilk test was used to assess the normality of the data. Data with a normal distribution were presented as mean ± SD, whereas non-normally distributed data were presented as median (range). Stethoscopic-VVTI values of the 25 cats between relaxed and stimulated states in the home environment, as well as stethoscopic-VVTI 20 calculated at the beginning vs the late section from the 2-min recording, were compared using the paired t-test. Stethoscopic-VVTI data from 23 cats recorded in a home environment (excluding two cats that had measurements in both home and hospital environments) were compared with the stethoscopic-VVTI data from six cats recorded in a hospital environment using the independent t-test. A repeated measures one-way ANOVA was performed to compare the results among stethoscopic-VVTI 20, stethoscopic-VVTI 60 and stethoscopic-VVTI 120 of the 25 cats in the home environment, followed by a pairwise analysis. Spearman’s rank correlation analysis was used to assess the correlation between stethoscopic-VVTI and the simultaneous HR (the mean HR for the period over which the VVTI calculation was taken) in 25 cats in the home environment. Stethoscopic-VVTI values and the corresponding HR were categorised by HR intervals of 10 beats/min and illustrated with box and whisker plots. The Bland–Altman plots were used to separately compare stethoscopic-VVTI and ECG-VVTI in the home and hospital environments, with the limits of agreement calculated as the mean difference ± 1.96 SD. The mean difference indicates potential bias of one method over another, while the limits of agreement denote the variability in the differences. A P value <0.05 was considered statistically significant.

Results

Study population

A total of 29 cats (25 at home and six in the hospital, with two recorded in both environments) were enrolled. Four cats were excluded owing to uncooperativeness or stress response with visitors in their homes. Breeds of cats in the study consisted of 22 domestic shorthairs, two British Shorthairs, two Ragdolls and one each of British Longhair, Bengal and American Shorthair. The median age and 9-point body condition score of the cats in this study were 4.0 years (range 0.4–15.0) and 5 (range 4–8), respectively. There were 16 castrated males, 11 spayed females and one each of intact female and male. For the stethoscopic approach, all 29 cats successfully obtained heart sound recordings for calculating stethoscopic-VVTI, either at home or in the hospital, with minimal manipulation. Regarding ECG, 16/25 cats at home (with minimal manipulation) and all six cats in the hospital (with assistance from other hospital staff) were able to acquire recordings with sufficiently few artefacts for calculating ECG-VVTI.

Stethoscopic-VVTI: relaxed vs stimulated states (25 cats in the home environment)

The stethoscopic-VVTI values were statistically different between relaxed and stimulated states, with stethoscopic-VVTI 20, stethoscopic-VVTI 60 and stethoscopic-VVTI 120 significantly decreasing after stimulation (Table 1).

Table 1

Stethoscopic-VVTI values under relaxed and stimulated states in the home environment of the 25 study cats

Variables	Relaxed states	After stimulation	P
Stethoscopic-VVTI 20	5.43 ± 0.75	4.79 ± 0.81	0.001*
Stethoscopic-VVTI 60	6.20 ± 0.71	5.18 ± 0.72	<0.001*
Stethoscopic-VVTI 120	6.24 ± 0.66	5.60 ± 0.57	0.02*

Data are mean ± SD unless otherwise indicated

Significant differences (P <0.05)

VVTI = vasovagal tonus index

The stethoscopic-VVTI 20 calculated at the beginning was not statistically different from the value calculated in the late period of the 2-min recording (relaxed state: 5.24 ± 0.98 vs 5.54 ± 0.98, P = 0.27; stimulated state: 4.76 ± 0.80 vs 4.89 ± 0.66, P = 0.50). Regarding the stethoscopic-VVTI calculated from different numbers of consecutive heartbeats, all calculated values at 20, 60 and 120 beat-to-beat intervals showed a similar trend between relaxed and stimulated states. There were significant differences among variables except for stethoscopic-VVTI 60 and 120 under relaxed state (Figure 2).

Figure 2

Box and whisker plots illustrating the VVTI calculated from 20, 60 and 120 consecutive heartbeats using the stethoscopic approach (stethoscopic-VVTI 20, 60 and 120) in both relaxed and stimulated states. *P <0.05. VVTI = vasovagal tonus index

Stethoscopic-VVTI: correlations with simultaneous HR (25 cats in the home environment)

The stethoscopic-VVTI 60 (r_s = −0.40, P = 0.049) and stethoscopic-VVTI 120 (r_s = −0.56, P = 0.01) showed a moderate negative correlation with the corresponding HR, while stethoscopic-VVTI 20 did not reveal a significant correlation with the corresponding HR (r_s = −0.28, P = 0.17) (Figure 3). The relationship between stethoscopic-VVTI and the corresponding HR was visually depicted, with VVTI data descriptively illustrated across HR categories at intervals of 10 beats/min (Figure 4).

Figure 3

Scatter plot of stethoscopic-VVTI 20, 60 and 120 with the corresponding heart rates. VVTI = vasovagal tonus index

Figure 4

The VVTI values calculated from 20 consecutive heartbeats using the stethoscopic approach (stethoscopic-VVTI 20) are illustrated across categories of heart rate (HR) intervals of 10 beats/min. A wide range of VVTI values can be observed within a single HR category, with noticeable overlap between different HR categories. This indicates variability in vagal tone states within the same level of HR. VVTI = vasovagal tonus index

Stethoscopic-VVTI acquisition in a hospital setting (six cats)

The stethoscopic approach could be successfully conducted in all six cats during their veterinary visits in a hospital setting. The stethoscopic-VVTI 20 recorded in a hospital setting (3.62 ± 1.09) was significantly lower than that of the 23 cats recorded in a home environment (5.26 ± 0.99) (P = 0.001).

Agreement between stethoscopic-VVTI and ECG-VVTI (16 cats at home; six cats in hospital)

In 16 cats for which both stethoscopic-VVTI and ECG-VVTI were successfully obtained at their homes, the Bland–Altman analysis showed a mean bias for the differences between stethoscopic-VVTI and ECG-VVTI of 0.50 ± 0.95 (95% CI −1.37 to 2.36) (Figure 5a). In six cats with stethoscopic-VVTI and ECG-VVTI acquired in a hospital setting, the Bland–Altman plot revealed a mean bias for the differences between stethoscopic-VVTI and ECG-VVTI of 1.07 ± 1.15 (95% CI −1.1 to 3.32) (Figure 5b).

Figure 5

Bland–Altman plots of the difference in VVTI values calculated from stethoscopic approach compared with ECG (a) at home and (b) in hospitals. VVTI = vasovagal tonus index

Discussion

The study results demonstrated that stethoscopic-VVTI values in cats significantly decreased after stimulation, exhibiting a negative correlation with HR and variability over the same HR intervals as observed for conventional VVTI. In addition, the stethoscopic-VVTI 20 calculated at the beginning and during the late period of the 2-min heart sound recording did not show a statistically significant difference. Stethoscopic-VVTI 60 and 120 were significantly higher than stethoscopic-VVTI 20 in both relaxed and stimulated states; however, stethoscopic-VVTI 60 was not significantly different from stethoscopic-VVTI 120 when the cats were more relaxed. All calculated stethoscopic-VVTI values at 20, 60 and 120 beat-to-beat intervals exhibited a similar trend between relaxed and stimulated states.

The analysis of HRV can be assessed using time-domain, frequency-domain and non-linear measures.^{2,5,7,15,18,26–28} Among various methodologies, VVTI is a simple and intuitive approach to assess HRV by measuring R-R intervals over 20 heart cycles in dogs.¹ In autonomic regulation, changes in parasympathetic tone (<1 s) occur much more rapidly than changes in sympathetic tone (>5 s).^1,18,27 Consequently, the variation in R-R intervals in short-term recordings is primarily facilitated by the parasympathetic nervous system.¹ This phenomenon is supported by our results, as stethoscopic-VVTI values decreased significantly after the cats were stimulated, indicating the withdrawal of parasympathetic tone. Previous studies of cats that could tolerate Holter ECG recording have documented the common occurrence of respiratory sinus arrhythmia during a relaxed state in the home environment, suggesting a higher vagal tone in unstimulated cats.^29,30 Thus, stimulation applied to cats can reasonably lead to a decreased vagal tone and an index reflective of this, as shown in our study.

The stethoscopic-VVTI exhibited significant differences between relaxed and stimulated states, and the stethoscopic-VVTI of cats recorded at home was also higher than those recorded in a hospital setting. This is in contrast to a previous study that evaluated ECG-VVTI in cats in home vs hospital settings and found no difference in VVTI values. This inconsistency may arise from the inherently more stressful nature of obtaining an ECG in cats, which involves restraining and unpleasant manipulation, compared with the less intrusive stethoscopic approach. A similar trend can be observed in the Bland–Altman analysis of our study, showing higher vagal tone with the stethoscopic approach compared with the ECG method. This finding is expected, considering cats were likely under more stress when physically restrained for the ECG recording. As a result, ECG-VVTI might be less adept at discerning variations in cats’ autonomic tone under home and hospital conditions, especially when utilising a short-term HRV variable. For the evaluation of HRV within a relatively short period, a phonocardiogram may prove a more suitable tool than ECG. This innovative approach is not only cat friendly but also minimises stress, preserving a more normal parasympathetic tone and resulting in a less pronounced impact on HRV assessment.

A negative correlation between VVTI and HR has been reported in previous canine studies, with an increase in HR as VVTI decreases.^1,6,17,21 While the existence of this relationship is not surprising, it may raise the question about the rationale for calculating VVTI instead of solely evaluating HR. Despite VVTI being an index for HRV and influenced by HR, HR itself is also modulated by factors such as neurohumoral sympathetic drive and intrinsic properties of sinoatrial node cells.^1,2 In our study, after categorising cats into different HR intervals, a high variability of VVTI within each category with the same HR intervals was observed, along with an overlap of the VVTI range across multiple HR groups. A similar phenomenon has also been observed in dogs.²¹ Moreover, in some human cases, it has been observed that excluding HR as a significant risk factor can enhance the predictive power of HRV for patient outcomes.³¹ This indicates that the relationship between HR and HRV involves more than just a mathematical correlation and evaluating HRV holds unique value beyond merely assessing HR alone. Therefore, measuring VVTI could provide more information than HR alone, offering greater insight into the cat’s autonomic nervous system status and generating additional clinical values in prognosis.

The calculations of stethoscopic-VVTI from 20, 60 and 120 beat-to-beat intervals all exhibit a consistent trend as the values decrease from a relaxed to a stimulated status in our study. A closer alignment between stethoscopic-VVTI 60 and 120 was observed compared with stethoscopic-VVTI 20. Nevertheless, despite the similarity in relaxed conditions, a statistical difference between stethoscopic-VVTI 60 and 120 was detected when the cats were stimulated, highlighting that these two indices cannot be substituted for one another. Thus, the use of a fixed number of heartbeats is necessary for assessment with this tool. The authors recommend applying stethoscopic-VVTI 20 first, as it has proven useful in clinical studies of dogs and can be rapidly calculated, providing an advantage in a busy clinical practice. Alternatively, stethoscopic-VVTI 60 can be considered when there is a need to evaluate the vasovagal status for a more lasting period. The practical application of stethoscopic-VVTI 120 in clinical settings is hindered by the extended recording time required. Any occurrence of artefacts, such as movement or vocalisation during the 120-heartbeat recording, would compromise data reliability.

The assessment of autonomic function through HRV has gained recognition for its significance in risk stratification across a broad spectrum of medical conditions in human medicine, including myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, neurological disorders and sudden death events.^{3,4,9,13,28,32} Numerous veterinary studies have also explored the role of HRV in various canine diseases, as well as in the evaluation of animal welfare, such as in farm animals like cattle.^{1,5–7,10,11,14,27,33,34} In contrast, studies on HRV in cats remain limited,^15,16,19,20 likely due to the inherently sensitive nature of this species. Many cats exhibit lower tolerance for ECG procedures, and the potential stress induced by this method adds complexity to the evaluation of HRV. Therefore, the benefit of employing stethoscopic-VVTI is that it requires only minimal manipulation of the cats, and it can be applied with an easily available digital stethoscope with freeware software by feline practitioners. While HRV can be concurrently assessed during routine auscultation, it signifies a noteworthy prospect in the research of feline autonomic regulation. Moreover, because of its straightforward and simple execution, it holds the potential for training cat owners in adopting this as a future monitoring tool in home environments.

This study has some limitations. First, the stimulation applied in this study was determined based on each cat’s temperament and conducted by their owners. Therefore, the strength for altering emotional status might not be strictly consistent in each cat in the current study. However, our results showed that these stimulations were strong enough to yield detectable differences in VVTI recorded using the stethoscopic approach. Second, the time of day for recording was not standardised, and the potential influence of circadian rhythm on VVTI cannot be ruled out. Third, the stethoscopic approach for evaluating HRV is only applicable for short-term HRV assessment, as with prolonged auscultation, the cats usually start to move, vocalise or purr. In addition, an artefact sound might be misinterpreted as a heart sound without simultaneous ECG if not recorded and inspected carefully. Finally, although none of the study cats were critically ill, not every cat underwent baseline ECG recordings, echocardiography and comprehensive blood examinations. It is unknown whether certain mild but stable disease factors could affect the response to stimulation and the calculated VVTI data. Despite the potential confounding influence of diseases in some cats, detectable changes in stethoscopic-VVTI are still evident in response to stimulation. Considering that medical conditions such as subclinical cardiomyopathy, hyperthyroidism or diabetes mellitus may influence HRV, future studies using the stethoscopic approach reported here to investigate stethoscopic-VVTI or other HRV variables derived from heart sound signals should take into account different disease categories in clinical cats.

Conclusions

The stethoscope can serve as a clinically useful tool to evaluate HRV in cats during routine auscultation. A significant decrease in stethoscopic-VVTI after stimulation in this study indicates that depressed vasovagal tone can be detected with this approach. It appears that stethoscopic-VVTI calculated from 20 consecutive heartbeats has the potential to be used to assess the cat’s autonomic control status in a busy clinical practice, while the calculation from 60 consecutive heartbeats may be considered as an alternative. The approach to recording heart sounds for HRV analysis can be easily performed with minimal stress to cats during the process, in contrast to the manipulation associated with recording ECG. Further studies are warranted to investigate HRV using this cat friendly approach across diverse clinical scenarios.

Footnotes

Acknowledgements

We sincerely appreciate all the devoted cat owners in Taiwan, who provide the solid strength to strive for the improvement of feline healthcare.

Accepted: 1 July 2024

Conflict of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

Part of this research was granted by NSTC 111-2313-B-002-062 from National Science and Technology Council, Taiwan. Part of the research work and this manuscript was supported by the Grant 113L892501 from National Taiwan University.

Ethical approval

The work described in this manuscript involved the use of non-experimental (owned or unowned) animals. Established internationally recognised high standards (‘best practice’) of veterinary clinical care for the individual patient were always followed and/or this work involved the use of cadavers. Ethical approval from a committee was therefore not specifically required for publication in JFMS. Although not required, where ethical approval was still obtained, it is stated in the manuscript.

Informed consent

Informed consent (verbal or written) was obtained from the owner or legal custodian of all animal(s) described in this work (experimental or non-experimental animals, including cadavers, tissues and samples) for all procedure(s) undertaken (prospective or retrospective studies). No animals or people are identifiable within this publication, and therefore additional informed consent for publication was not required.

ORCID iD

Chung-Hui Lin

References

Haggstrom

Hamlin

Hansson

, et al. Heart rate variability in relation to severity of mitral regurgitation in Cavalier King Charles spaniels. J Small Anim Pract 1996; 37: 69–75.

Heart rate variability: standards of measurement, physiological interpretation and clinical use.

Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.

Circulation 1996; 93: 1043–1065.

Tsuji

Larson

Venditti

Jr , et al. Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study. Circulation 1996; 94: 2850–2855.

Lahiri

Kannankeril

Goldberger

JJ.

Assessment of autonomic function in cardiovascular disease.

J Am Coll Cardiol 2008; 51: 1725–1733.

Spier

Meurs

KM.

Assessment of heart rate variability in Boxers with arrhythmogenic right ventricular cardiomyopathy.

J Am Vet Med Assoc 2004; 224: 534–537.

Pereira

Woolley

Culshaw

, et al. The vasovagal tonus index as a prognostic indicator in dogs with dilated cardiomyopathy. J Small Anim Pract 2008; 49: 587–592.

Lopez-Alvarez

Boswood

Moonarmart

, et al. Longitudinal electrocardiographic evaluation of dogs with degenerative mitral valve disease. J Vet Intern Med 2014; 28: 393–400.

Ferinistrambi

Zucconi

Oldani

, et al. Heart rate variability during sleep in snorers with and without obstructive sleep apnea. Chest 1992; 102: 1023–1027.

Camillo

Laburu Vde

Goncalves

, et al. Improvement of heart rate variability after exercise training and its predictors in COPD. Respir Med 2011; 105: 1054–1062.

10.

Little

Julu

PO.

Investigation of heart rate variability in a dog with upper respiratory tract obstruction.

J Small Anim Pract 1995; 36: 502–506.

11.

Kenefick

Parker

Slater

, et al. Evidence of cardiac autonomic neuropathy in dogs with diabetes mellitus. Vet Rec 2007; 161: 83–88.

12.

Benichou

Pereira

Mermillod

, et al. Heart rate variability in type 2 diabetes mellitus: a systematic review and meta-analysis. PLoS One 2018; 13. DOI: 10.1371/journal.pone.0195166.

13.

Jarczok

Weimer

Braun

, et al. Heart rate variability in the prediction of mortality: a systematic review and meta-analysis of healthy and patient populations. Neurosci Biobehav Rev 2022; 143. DOI: 10.1016/j.neubiorev.2022.104907.

14.

Alfonso

Le Sueur

ANV

Geraldes

, et al. Heart rate variability and electrocardiographic parameters predictive of arrhythmias in dogs with stage IV chronic kidney disease undergoing intermittent haemodialysis. Animals (Basel) 2020; 10. DOI: 10.1016/j.neubiorev.2022.104907.

15.

Abbott

JA.

Heart rate and heart rate variability of healthy cats in home and hospital environments.

J Feline Med Surg 2005; 7: 195–202.

16.

Walker

Ueda

Crofton

, et al. Ambulatory electrocardiography, heart rate variability, and pharmacologic stress testing in cats with subclinical hypertrophic cardiomyopathy. Sci Rep 2022; 12. DOI: 10.1038/s41598-022-05999-x.

17.

Doxey

Boswood

Differences between breeds of dog in a measure of heart rate variability.

Vet Rec 2004; 154: 713–717.

18.

Shaffer

Ginsberg

JP.

An overview of heart rate variability metrics and norms.

Front Public Health 2017; 5. DOI: 10.3389/fpubh.2017.00258.

19.

Conti

Champion

Guberman

, et al. Evaluation of environment and a feline facial pheromone analogue on physiologic and behavioral measures in cats. J Feline Med Surg 2017; 19: 165–170.

20.

Carvalho

Champion

Vilani

RGDC

, et al. Sedative and electrocardiographic effects of low dose dexmedetomidine in healthy cats. Pesqui Vet Brasil 2019; 39: 142–147.

21.

Trauffler

Schuller

Kovacevic

, et al. Establishing reference standards for the vasovagal tonus index in a cohort of healthy French Bulldogs. Schweiz Arch Tierheilkd 2019; 161: 821–829.

22.

Zupan

Buskas

Altimiras

, et al. Assessing positive emotional states in dogs using heart rate and heart rate variability. Physiol Behav 2016; 155: 102–111.

23.

Taylor

St Denis

Collins

, et al. 2022 ISFM/AAFP cat friendly veterinary environment guidelines. J Feline Med Surg 2022; 24: 1133–1163.

24.

Saponaro

Mey

Vonfeld

, et al. Systolic third sound associated with systolic anterior motion of the mitral valve in cats with obstructive hypertrophic cardiomyopathy. J Vet Intern Med 2023; 37: 1679–1684.

25.

Vezzosi

Alibrandi

Grosso

, et al. Evaluation of a new smartphone-based digital stethoscope featuring phonocardiography and electrocardiography in dogs and cats. Vet J 2023; 295. DOI: 10.1016/j.tvjl.2023.105987.

26.

Blake

Shaw

Culshaw

, et al. Poincare plots as a measure of heart rate variability in healthy dogs. J Vet Cardiol 2018; 20: 20–32.

27.

Baisan

Vulpe

Ohad

DG.

Short-term heart rate variability in healthy dogs and dogs in various stages of degenerative mitral valve disease evaluated before pharmacotherapy.

Vet J 2021; 274. DOI: 10.1016/j.tvjl.2021.105704.

28.

Xhyheri

Manfrini

Mazzolini

, et al. Heart rate variability today. Prog Cardiovasc Dis 2012; 55: 321–331.

29.

Ware

WA.

Twenty-four-hour ambulatory electrocardiography in normal cats.

J Vet Intern Med 1999; 13: 175–180.

30.

Hanås

Tidholm

Egenvall

, et al. Twenty-four hour Holter monitoring of unsedated healthy cats in the home environment. J Vet Cardiol 2009; 11: 17–22.

31.

Sacha

Interaction between heart rate and heart rate variability.

Ann Noninvas Electro 2014; 19: 207–216.

32.

Sessa

Anna

Messina

, et al. Heart rate variability as predictive factor for sudden cardiac death. Aging (Albany, NY) 2018; 10: 166–177.

33.

Kovacs

Jurkovich

Bakony

, et al. Welfare implication of measuring heart rate and heart rate variability in dairy cattle: literature review and conclusions for future research. Animal 2014; 8: 316–330.

34.

Kovács

Kézér

Jurkovich

, et al. Heart rate variability as an indicator of chronic stress caused by lameness in dairy cows. PLoS One 2015; 10. DOI: 10.1371/journal.pone.0134792.