A method to assess heart rate variability in neonate rats: validation in normotensive and hypertensive animals.
Sarah Cristina Ferreira FreitasC Paixão Dos SantosA ArnoldFilipe F Stoyell-ContiM R H DutraMariana Matera VerasM C IrigoyenKátia De AngelisPublished in: Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas (2020)
Several studies have focused on the heart rate variability (HRV) of murine species, while studies discussing HRV in murine neonates and infants remain scarce, since recording hemodynamic signals through invasive methods in small animals has been found to be quite challenging. Thus, this study aimed at describing and validating a novel method to assess HRV in newborn rats. An electrocardiogram (ECG) system was used to determine RR intervals in awake newborns and evaluate HRV in normotensive (Wistar) and hypertensive (SHR) neonate rats. After birth, ECG was recorded in the awake newborns, and they were allowed to rest on a heated surface, restricted only by the weight of the adhesive ECG electrodes. The electrodes were cut and adapted to provide more comfort to the animal, and gently placed on the newborn's skin. RR intervals were recorded over a 30-min period using an ECG system together with LabChart software (4 KHz). Three sequences of 5 min each from the ECG recording period were analyzed in time and frequency domains, using CardioSeries software. ECG data resulted in a clearly interpretable signal that was used to generate an RR interval sequence through time for the analysis of HRV. SHR neonates presented increased cardiac sympathovagal balance compared to Wistar neonates (low frequency/high frequency: 3.85±0.71 vs 0.90±0.09). In conclusion, the ECG setup here described may be used to record RR intervals to assess HRV in neonate rats, thus detecting early impairment of HRV in hypertensive newborns.
Keyphrases
- heart rate variability
- heart rate
- high frequency
- blood pressure
- low birth weight
- pregnant women
- gestational age
- transcranial magnetic stimulation
- cord blood
- left ventricular
- body mass index
- weight loss
- heart failure
- data analysis
- machine learning
- artificial intelligence
- gold nanoparticles
- big data
- atrial fibrillation
- case control
- soft tissue
- body weight
- solid state
- pregnancy outcomes
- carbon nanotubes