Steven M. Barlow
Date of this Version
Marquez, A. (2021). Non-nutritive suck burst pattern stability in extremely premature infants. Master’s thesis, Department of Speech-Language Pathology and Audiology, University of Nebraska–Lincoln.
The development of non-nutritive suck (NNS) burst dynamics in preterm infants reflects the integrity of the brain and is used clinically to assess feeding readiness and orofacial motor development (Mizuno and Ueda, 2005). The application of NNS analytics in the present report represents one outcome measurement set that is part of an ongoing clinical trial involving extremely preterm infants (EPI’s,[GA]) randomized to receive either pulsed orocutaneous stimulation therapeutics or a sham (blind pacifier), in conjunction with salivary sampling twice weekly to map gene expression of key proteins involved in neural development and molecular sensing of feeding related pathways in the brain (NIH R01 HD086088, Barlow - PI).
This trial is entering its fourth year of preterm enrollment at neonatal intensive care units (NICU) in the United States, including Lincoln, NE; Boston, MA; and San Jose, CA). A fourth NICU, located in Los Angeles, California, joined this trial in December 2018. The present report aims to characterize the evolution of the NNS burst through implementation of a new automated Python software platform known as NeoNNS (Liao et al., 2019) that was developed in the Communication Neuroscience Laboratories at the University of Nebraska - Lincoln. NeoNNS was designed to handle large data sets sampled at multiple NICUs using batch processing to automatically perform NNS burst discrimination among cohorts of EPI’s stratified into one of two groups based on GA. The present report is an interim analysis designed to quantify NNS burst formation in EPI’s using the spatiotemporal index (STI) calculation as a function of sex, respiratory diagnosis (bronchopulmonary dysplasia (BPD) and respiratory distress syndrome (RDS)), orosensory treatment, and postmenstrual age (PMA) using a repeated measures design.
Linear Mixed Modeling (LMM) was utilized to calculate dependent variable STI on a sample of 817 NNS compression pressure waveforms sampled from 42 EPI participants. Main effects for Sex (p=.7263) and respiratory diagnosis [RDS, BPD] (p=.2128) were not significant. There was a marginally significant Treatment effect (p
In spite of the small sample size for this interim analysis of NNS burst pattern formation, these findings support the hypothesis that an automated quantitative measure of NNS burst variance in medically fragile EPI’s is strongly dependent on postmenstrual age, and can provide clinicians with an objective method for charting the progression of ororhythmic motor pattern formation as infants progress in the NICU towards independent oral feeding.
Faculty Mentor: Steven M. Barlow