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Background: Digital stethoscope (DS) technology has been used to assess normal and abnormal breath sounds in children. However, this technology has not been used to describe characteristics of breath sounds in preterm and term neonates. Method(s): A commercially available DS and smartphone software was used to record breath sounds of self-ventilating preterm and term neonates for one minute on day 2 of life. Recordings were extracted, filtered and spectral analysis performed to assess parameters including peak width (PW), spectrum slope (SL), area under the regression line (PLN) and mel-frequency cepstral coefficients (MFCC). PW, SL and PLN depend on the distribution of sound power in the frequency domain, while MFCCs represent smoothed log magnitude spectra in the nonlinear mel-scale of frequency and are known to depend on chest shape and resonance of breath sounds. Result(s): Thirty neonates were studied. After exclusions due to sound quality, 13 preterm (mean (SD) gestational age 32.8 (1.6) weeks, birth weight 1926.6 (429.4) grams), and 14 term neonates (38.8 (1.4) weeks, 3470.7(481.3) grams, p < 0.001) were analysed. There were no significant differences in PW, SL, or PLN between preterm and term infants. However, significant differences were noted between preterm and term MFCCs in scales 3-6 (p values of difference ranging between 0.002 to 0.05). Conclusion(s): Recording of breath sounds using DS is quick and feasible and showed no major differences between preterm and term self-ventilating infants. DS technology may pick up subtle differences related to inherent chest wall and lung resonance characteristics of preterm neonates.

Background: Digital stethoscope technology has been used to record and study normal and abnormal breath sounds in the paediatric population. There may be scope to utilise this technology to describe breath sound characteristics in the transitioning newborn. Method(s): A commercially available digital stethoscope and acquisition software was used to record breath sounds of term infants born via normal vaginal delivery (NVD) and elective caesarean section (CS) at one minute and two hours of life. Recordings had a bandpass filter applied and analysed using MATLAB. Power spectrum profiles, total power (TP), peak width (PW), spectrum slope (SL) and area under the regression line (PLN) were extracted and compared between delivery modes. Result(s): Sixty-one newborns were studied. Mean (SD) gestation and weight of 32 NVD infants was 38 (0.9) weeks and 3165.6 (447.1) grams, and 29 elective CS infants was 38 (0.9) weeks and 3222.1 (297.1) grams. 83.6% of 1 min and 100% of 2-h recordings were analysable. Mean difference in spectral features between CS and NVD groups at 1-min: TP 1.56 dB/Hz (p < 0.001), PW 4.14 Hz (p < 0.001), PLN 412.82 dB (p = 0.002), SL 0.63 dB/octave (p = 0.003). Mean difference at 2 h: TP 0.99 dB/Hz (p = 0.004), PW 1.54 Hz (p = 0.01), PLN 200.56 dB (p = 0.03), SL 0.34 dB/octave (p = 0.01). Conclusion(s): It is feasible to use digital stethoscope technology to assess breath sounds in the transitioning newborn. We were able to depict a difference in breath sound characteristics between infants delivered via elective CS and NVD. This may be associated with differential lung fluid clearance.