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Published on: August 19, 2020
Feasibility of Spectral Analysis as a Tool in Nursing Research to Quantify Patterns of Respiration in Premature
Khlood Bubshait1, Olivia Dizon2, Charlene Krueger2
1Fundamental of Nursing Department, Imam Abdulrahman Bin Faisal University, Dammam 1980, Saudi Arabia.
Insights
Spectral analysis of heart rate variability can quantify respiratory patterns in preterm infants. This method offers a novel biomarker for assessing respiration in vulnerable newborns, aiding clinical practice and research.
Area of Science:
- Neonatal physiology
- Biomarker development
- Respiratory monitoring
Background:
- Preterm infants frequently experience respiratory difficulties, potentially leading to long-term health issues.
- Limited research exists on using spectral analysis as a biomarker for quantifying infant respiration patterns.
Purpose of the Study:
- To assess the feasibility of using spectral analysis of heart rate variability (HRV) to quantify respiratory patterns in very-low-birth-weight preterm infants.
- To compare spectral analysis findings with direct observational data of infant respiration.
Main Methods:
- A small-scale feasibility study involving 18 preterm infants (27-28 weeks gestational age, <1500g).
- Direct observation of respiratory patterns (regular/irregular, shallow/deep) during speech playback.
- Simultaneous measurement of HRV using spectral analysis, focusing on respiratory sinus arrhythmia (RSA) frequencies (0.30-1.0 Hz).
Main Results:
- The magnitude of RSA was higher in infants with irregular shallow respiration compared to those with regular deep respiration.
- A frequency shift in RSA was observed, moving from lower peaks (0.30 Hz) to higher peaks (0.70 Hz).
Conclusions:
- Spectral analysis provides a quantifiable method for assessing respiratory patterns in preterm infants, complementing direct observation.
- This technique holds promise as a biomarker for evaluating developmental and pathological respiratory trends in this vulnerable population.
Background:
Respiratory difficulties are a common concern in preterm infants, and they can lead to long-term health problems. Few studies have investigated the use of spectral analysis as a biomarker to quantify respiration patterns in preterm infants.
Objective:
To evaluate the feasibility of using spectral analysis of heart rate variability as a biomarker for the quantification of respiratory patterns in very-low-birth-weight preterm infants compared to direct observation.
Methods:
In a comparative, small-scale feasibility study, 18 preterm infants born during their 27th to 28th gestational week (weighing <1500 grams) participated by convenience. Respiratory patterns (regular or irregular; shallow or deep) were directly observed on the 28th week during playback of speech recording. Heart rate variability was simultaneously measured using spectral analysis of heart periods, from which the mean values influenced by respiratory sinus arrhythmia (frequencies of 0.30-1.0 Hz) were compared to each observed respiratory pattern. The magnitudes of respiratory sinus arrhythmia and the area under the curve were determined.
Results:
The magnitude of respiratory sinus arrhythmia (frequencies of 0.30-1.0 Hz) in infants observed to be displaying irregular shallow respiration was greater than that in infants with regular deep respiration. Further, there was a shift from lower frequencies (frequency peak = 0.30 Hz) to higher frequencies (peak = 0.70 Hz).
Conclusion:
In contrast with direct observation, spectral analysis allowed for the quantification of respiratory patterns in a vulnerable population of preterm infants of interest to the nursing scientific and practice community. Future directions include applying this biomarker to evaluate both developmental and pathological trends in the respiratory patterns of preterm infants.
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