Sources of methodological variability in phase angles from respiratory inductance plethysmography in preterm infants

Abstract

Rationale: Better phenotypic descriptions are needed for chronic lung disease among surviving premature infants.

Objectives: The purpose of this study was to evaluate the potential usefulness of respiratory inductance plethysmography in characterizing respiratory system mechanics in preterm infants at 32 weeks postmenstrual age.

Methods: Respiratory inductance plethysmography was used to obtain the phase angle, Φ, to describe rib cage and abdominal dyssynchrony in 65 infants born between 23 and 28 weeks gestation, all of whom were studied at 32 weeks postmenstrual age. Up to 60 breaths were evaluated for each subject. Sources of intrasubject variability in Φ arising from our methods were explored using mechanical models and by evaluating interobserver agreement.

Measurements and main results: The mean Φ from infants ranged from 5.8-162.9°, with intrasubject coefficients of variation ranging from 11-123%. On the basis of the mechanical model studies, respiratory inductance plethysmography recording and analysis software added <2.3% to the intrasubject variability in Φ. Potential inconsistencies in breaths selected could have contributed 8.1%, on average, to the total variability. The recording sessions captured 22.8 ± 9.1 minutes of quiet sleep, and enough breaths were counted to adequately characterize the range of Φ in the session.

Conclusion: Φ is quite variable during even short recording sessions among preterm infants sleeping quietly. The intrasubject variability described herein arises from the instability of the rib cage and abdominal phase relationship, not from the recording and analytical methods used. Despite the variability, Φ measurements allowed the majority (80%) of infants to be reliably categorized as having relatively synchronous or dyssynchronous breathing. Respiratory inductance plethysmography is easy to use and should prove useful in quantifying respiratory mechanics in multicenter studies of preterm infants.

Keywords: inductance plethysmography; phase angle; premature infant respiration.

Figures

Figure 1.

Recruitment tree. NICU, Neonatal Intensive Care Unit.

Figure 2.

Φ results for all breaths for each of 65 subjects. Plotted are the medians and the 25th and 75th percentiles with ranges. Of the 65 infants, 50 had 60 acceptable breaths and 15 had fewer than 60 acceptable breaths (median, 50 breaths; range, 19–58 breaths). Line at 60° is drawn to provide a magnitude context for these results by showing the mean value for Φ derived from a published report on infants with CLD and is not meant to indicate a cut point for normal versus abnormal (14). Indeed, the intent in assessing RIP is to validate a continuous variable.

Figure 3.

Coefficients of variation in Φ are plotted versus the median Φ for the breaths chosen. This figure illustrates that the variability shown in Figure 2, when corrected for Φ size, is actually larger at smaller Φ values and decreases with increases in the size of Φ. The smaller coefficient of variation for the larger Φ values likely reflects a “ceiling effect,” with no values >180° possible.

Figure 4.

Interobserver differences for 25 infants illustrated by a Bland-Altman plot showing the differences in mean Φ obtained by two independent observers (L.N.U., J.S.K.) versus the average of their two means (mean observer 1 + mean observer 2, divided by 2). The result indicated by the large filled circle is for the 1 of 25 subjects compared when Φ results differed statistically between the two observers.

Figure 5.

Differences between observers in breath selection had a minimal impact on variability. For the 25 recordings scored by 2 observers, individual subjects’ coefficients of variation are plotted on the y-axis against interobserver differences divided by mean Φ r2 = 0.081. For clarity, dividing by the mean Φ was a necessary size correction because a small mean Φ with, for example, a SD of 10, would have a large coefficient of variation, whereas the same SD would be associated with a much smaller coefficient of variation if the mean Φ were, for example, >> 100°.

Figure 6.

Φ variability from synchronous and dyssynchronous mechanical models with Vf of approximately 40 and 60 breaths per minute. Shown are the 25th and 75th percentiles and the medians with ranges for Φ from the synchronous model (*) near 0°. For the dyssynchronous model (**), Φ coefficients of variation are 1.1% and 2.3% at Vf of 40 and 60 per minute, respectively. These results show that the recording and analysis equipment contributed minimally to the variability in Φ measurements.

Figure 7.

How many breaths for evaluation are enough? Shown are the absolute differences between mean Φ calculated from 10, 20, 30, 40, and 50 breaths and the mean Φ for 60 breaths, or the highest number counted, for 55 subjects with more than 50 usable breaths. The dashed horizontal lines are at +10° and −10°. By 50 breaths, the mean Φ values were within 10° of the “true” mean for 90% of subjects and within 19° for all 55 subjects with more than 50 usable breaths. Shown are the 25th and 75th percentiles, the median, the 10th and 90th percentiles (T-bars), and the outlying results (circles and stars).