Dataset Information

Frequency-modulated orocutaneous stimulation promotes non-nutritive suck development in preterm infants with respiratory distress syndrome or chronic lung disease.

ABSTRACT: For the premature infant, extrauterine life is a pathological condition, which greatly amplifies the challenges to the brain in establishing functional oromotor behaviors. The extent to which suck can be entrained using a synthetically patterned orocutaneous input to promote its development in preterm infants who manifest chronic lung disease (CLD) is unknown. The objective of this study was to evaluate the effects of a frequency-modulated (FM) orocutaneous pulse train delivered through a pneumatically charged pacifier capable of enhancing non-nutritive suck (NNS) activity in tube-fed premature infants.A randomized trial to evaluate the efficacy of pneumatic orocutaneous stimulation 3 × per day on NNS development and length of stay (LOS) in the neonatal intensive care unit among 160 newborn infants distributed among three sub-populations, including healthy preterm infants, respiratory distress syndrome (RDS) and CLD. Study infants received a regimen of orocutaneous pulse trains through a PULSED pressurized silicone pacifier or a SHAM control (blind pacifier) during gavage feeds for up to 10 days.Mixed modeling, adjusted for the infant's gender, gestational age, postmenstrual age and birth weight, was used to handle interdependency among repeated measures within subjects. A significant main effect for stimulation mode (SHAM pacifier vs PULSED orosensory) was found among preterm infants for NNS bursts per min (P=0.003), NNS events per min (P=0.033) and for total oral compressions per min (NNS+nonNNS) (P=0.016). Pairwise comparison of adjusted means using Bonferroni adjustment indicated RDS and CLD infants showed the most significant gains on these NNS performance indices. CLD infants in the treatment group showed significantly shorter LOS by an average of 2.5 days.FM PULSED orocutaneous pulse train stimuli delivered through a silicone pacifier are effective in facilitating NNS burst development in tube-fed RDS and CLD preterm infants, with an added benefit of reduced LOS for CLD infants.

SUBMITTER: Barlow SM

PROVIDER: S-EPMC3946759 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Frequency-modulated orocutaneous stimulation promotes non-nutritive suck development in preterm infants with respiratory distress syndrome or chronic lung disease.

Barlow S M SM Lee J J Wang J J Oder A A Hall S S Knox K K Weatherstone K K Thompson D D

Journal of perinatology : official journal of the California Perinatal Association 20131205 2

<h4>Objective</h4>For the premature infant, extrauterine life is a pathological condition, which greatly amplifies the challenges to the brain in establishing functional oromotor behaviors. The extent to which suck can be entrained using a synthetically patterned orocutaneous input to promote its development in preterm infants who manifest chronic lung disease (CLD) is unknown. The objective of this study was to evaluate the effects of a frequency-modulated (FM) orocutaneous pulse train delivere ...[more]

PMID: 24310444

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Project description:Background and Objective: The emergence of the nonnutritive suck (NNS) pattern in preterm infants reflects the integrity of the brain and is used by clinicians in the neonatal intensive care unit (NICU) to assess feeding readiness and oromotor development. A critical need exists for an integrated software platform that provides NNS signal preprocessing, adaptive waveform discrimination, feature detection, and batch processing of big data sets across multiple NICU sites. Thus, the goal was to develop and describe a cross-platform graphical user interface (GUI) and terminal application known as NeoNNS for single and batch file time series and frequency-domain analyses of NNS compression pressure waveforms using analysis parameters derived from previous research on NNS dynamics. Methods. NeoNNS was implemented with Python and the Tkinter GUI package. The NNS signal-processing pipeline included a low-pass filter, asymmetric regression baseline correction, NNS peak detection, and NNS burst classification. Data visualizations and parametric analyses included time- and frequency-domain view, NNS spatiotemporal index view, and feature cluster analysis to model oral feeding readiness. Results. 568 suck assessment files sampled from 30 extremely preterm infants were processed in the batch mode (<50 minutes) to generate time- and frequency-domain analyses of infant NNS pressure waveform data. NNS cycle discrimination and NNS burst classification yield quantification of NNS waveform features as a function of postmenstrual age. Hierarchical cluster analysis (based on the Tsfresh python package and NeoNNS) revealed the capability to label NNS records for feeding readiness. Conclusions. NeoNNS provides a versatile software platform to rapidly quantify the dynamics of NNS development in time and frequency domains at cribside over repeated sessions for an individual baby or among large numbers of preterm infants at multiple hospital sites to support big data analytics. The hierarchical cluster feature analysis facilitates modeling of feeding readiness based on quantitative features of the NNS compression pressure waveform.

Project description:BackgroundNeonatal acute respiratory distress syndrome (ARDS) is a critical clinical disease with high disability and mortality rates. Early identification and treatment of neonatal ARDS is critical. This study aimed to build a perinatal prediction nomogram for early prediction of neonatal ARDS.MethodsA prediction model was built including 243 late-preterm and full-term infants from Daping Hospital in Chongqing, China, hospitalised between Jan 1, 2018 and Dec 31, 2019. 80 patients from the Children's Hospital in Chongqing, China, hospitalised between Jan 1, 2018 and June 30, 2018 were considered for external validation. Multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of neonatal ARDS. Both discrimination and calibration were assessed by bootstrapping with 1000 resamples.FindingsMultivariate logistic regression demonstrated that mother's education level (odds ratio [OR] 0·478, 95% confidence interval [CI] 0·324-0·704), premature rupture of membrane (OR 0·296, 95% CI 0·133-0·655), infectious disease within 7 days before delivery (OR 0·275, 95% CI 0·083-0·909), hospital level (OR 2·479, 95% CI 1·260-4·877), and Apgar 5-min score (OR 0·717, 95% CI 0·563-0·913) were independent predictors for neonatal ARDS in late-preterm and full-term infants, who experienced dyspnoea within 24 h after birth and required mechanical ventilation. The area under the curve and concordance index of the nomogram constructed from the above five factors were 0·760 and 0·757, respectively. The Hosmer-Lemeshow test showed that the model was a good fit (P = 0.320). The calibration curve of the nomogram was close to the ideal diagonal line. Furthermore, the decision curve analysis demonstrated significantly better net benefit in the model. The external validation proved the reliability of the prediction nomogram.InterpretationA nomogram based on perinatal factors was developed to predict the occurrence of neonatal ARDS in late-preterm and full-term infants who experienced dyspnoea within 24 h after birth and required mechanical ventilation. It provided clinicians with an accurate and effective tool for the early prediction and timely management of neonatal ARDS.FundingNo funding was associated with this study.

Dataset Information

Frequency-modulated orocutaneous stimulation promotes non-nutritive suck development in preterm infants with respiratory distress syndrome or chronic lung disease.

Publications

Frequency-modulated orocutaneous stimulation promotes non-nutritive suck development in preterm infants with respiratory distress syndrome or chronic lung disease.

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