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Validation of computerized wheeze detection in young infants during the first months of life
© Puder et al.; licensee BioMed Central Ltd. 2014
Received: 17 April 2014
Accepted: 22 September 2014
Published: 9 October 2014
Several respiratory diseases are associated with specific respiratory sounds. In contrast to auscultation, computerized lung sound analysis is objective and can be performed continuously over an extended period. Moreover, audio recordings can be stored. Computerized lung sounds have rarely been assessed in neonates during the first year of life. This study was designed to determine and validate optimal cut-off values for computerized wheeze detection, based on the assessment by trained clinicians of stored records of lung sounds, in infants aged <1 year.
Lung sounds in 120 sleeping infants, of median (interquartile range) postmenstrual age of 51 (44.5–67.5) weeks, were recorded on 144 test occasions by an automatic wheeze detection device (PulmoTrack®). The records were retrospectively evaluated by three trained clinicians blinded to the results. Optimal cut-off values for the automatically determined relative durations of inspiratory and expiratory wheezing were determined by receiver operating curve analysis, and sensitivity and specificity were calculated.
The optimal cut-off values for the automatically detected durations of inspiratory and expiratory wheezing were 2% and 3%, respectively. These cutoffs had a sensitivity and specificity of 85.7% and 80.7%, respectively, for inspiratory wheezing and 84.6% and 82.5%, respectively, for expiratory wheezing. Inter-observer reliability among the experts was moderate, with a Fleiss’ Kappa (95% confidence interval) of 0.59 (0.57-0.62) for inspiratory and 0.54 (0.52 - 0.57) for expiratory wheezing.
Computerized wheeze detection is feasible during the first year of life. This method is more objective and can be more readily standardized than subjective auscultation, providing quantitative and noninvasive information about the extent of wheezing.
Wheezes consisting of continuous musical sounds of one or more tonal components [1, 2] among the most common adventitious lung sounds in children . Wheezes are usually louder than underlying breath sounds  and occur within a broad frequency range , with a mean dominant frequency in infants of 225.5 Hz . Wheezing is the acoustic manifestation of lower airway obstruction limiting air-flow in a collapsible tube, thus inducing wall flutter . This phenomenon is usually encountered in asthmatic children [7, 8], but can also occur in children with bronchiolitis , cystic fibrosis , foreign body aspiration , bronchomalacia  and primary ciliary dyskinesia . Therefore, detection of wheezing can be useful in diagnosing respiratory disorders and in assessing the efficacy of treatments [9, 13].
Wheezing is most frequently diagnosed by auscultation using a stethoscope or is based on parental reports of wheezes. However, parents often differ in their understanding of wheeze [14, 15] and parentally reported wheezing often cannot be confirmed by auscultation . Moreover, the inter-observer reliability between doctors has been questioned [17, 18] and the quality of auscultation has generally been described as insufficient [4, 7, 19]. This insufficiency is likely due to disparities in the nomenclature used to describe lung sounds [17, 20], in the varying quality of stethoscopes [4, 17] and high noise levels in clinical settings . Computerized lung sound analysis, especially computerized wheeze detection, has been reported to be a more objective and standardizable method, which can overcome the limitations of subjective auscultation [3, 9, 21, 22]. In contrast to auscultation, computerized lung sound analysis can be performed continuously over an extended period of time, and audio recordings can be stored for later assessment and quality monitoring.
To date, few studies have used computerized methods to detect wheezes during the first year of life [9, 23]. The inspiratory and expiratory times are shorter in infants aged <1 year than in older infants, for which cut-off values for the duration of wheezing have been determined . The authors hypothesized that, by determining optimal cut-off values for wheezing, computerized wheeze detection would be an objective, reliable and easy to use method of assessing wheezing also in infants aged <1 year. Therefore the aim of this feasibility study was to determine and validate optimal cut-off values for computerized wheeze detection, based on the assessment by trained clinicians of stored records of lung sounds in infants who recovered after a stay in the neonatal intensive care unit.
Patient characteristics during the neonatal period and at the time of measurement, presented as median [interquartile range] or n (%)
Neonatal period(N = 120)
Gestational age (weeks)
Birth weight (g)
Birth weight <1000 g
Fetal lung maturation1)
At day of measurement (N = 144)
Postmenstrual age (weeks)
Body length (cm)
62 (55.0 – 69.125)
Body weight (g)
5995 (4213.75 – 7142.5)
All parents provided written informed consent before each LFT, and the study protocol was approved by our Institutional Data Safety Committee.
Computerized wheeze detection
where Tw in/ex is the breathing time with wheeze during inspiration/expiration and Tin/ex is the total inspiratory/expiratory breathing time.
Subjective wheeze detection
Recorded sounds coded for each infant were retrospectively evaluated by three medical doctors working in the neonatal intensive care unit and trained before the study using a computer aided instruction on respiratory sounds (R.A.L.E.® Lung Sounds 3.2). Using headphones that minimized surrounding noise, each observer listened to the sound of each infant in a blinded fashion and assessed if wheezing was present or absent, independent of the strength and duration of sounds.
Lung sounds were recorded in clinically stable and sleeping infants who had no respiratory infections during the 3 weeks preceding the tests. Sleep was induced 15–30 min before LFT by oral administration of chloral hydrate (50 mg∙kg−1), since sedation was necessary for subsequent more complex LFT [25, 26].
To prevent any interactions lung sound recordings were performed before LFT and before a face mask was applied. Sounds were measured while the infants were supine, with the neck in a neutral position and supported by a neck roll. After attachment of the microphones and breathing belt, an adaptation time of 10–15 min was allowed before lung sounds were recorded. The duration of each recording was 10 minutes. No other lung function tests were performed simultaneously.
Patient characteristics and lung sound data are reported as rates (%) or as medians and interquartile ranges (IQR). Incidences of wheezing were compared using Fisher’s exact test. The Kruskal-Wallis rank test was used to investigate the influence of birth weight, mechanical ventilation and BPD on wheeze rates. Inter-observer reliability of lung sound assessment was assessed using Fleiss’ kappa, which is a generalization of Cohen’s kappa to multiple raters that provides a conservative measure of agreement. The 95% confidence interval of Fleiss’ kappa was calculated as described , with Fleiss’ kappa scores of 1.0, 0.81–0.99, 0.61–0.80, 0.41–0.60, 0.2–0.40 and <0.2 indicating perfect, almost perfect, substantial, moderate and poor agreement, respectively. Receiver operating characteristic (ROC) curves were calculated to determine the optimal cut-off values for inspiratory and expiratory wheezing times, as measured by the PulmoTrack® and compared with subjective evaluations. All statistical analyses were performed using Statgraphics Centurion® software (Version 16.0, Statpoint Inc., Herndon, VA, USA) and MEDCALC (Version 220.127.116.11, MedCalc Software, Mariakerke Belgium), with p < 0.05 defined as statistically significant.
Lung sounds were recorded in 120 infants on 144 test occasions, with 98 infants (82%) tested on one occasion, 20 (17%) on two occasions and 2 (1.7%) on three occasions. Patient characteristics are shown in Table 1. Most patients (95%) were premature infants with less than 37 gestational weeks and almost half (49%) of all patients were former extremely low birth weight (ELBW) infants, with a birth weight <1000 g. On the day of measurement, their median postmenstrual age (PMA) was 51 weeks, with none requiring any respiratory support.
Computerized wheeze detection
Subjective wheeze detection and inter-observer reliability
Lung sounds in investigated infants detected by three observers and the inter-observer variability assessed by Fleiss’ kappa with 95% confidence interval (CI)
0.59 (0.57 - 0.62) (moderate)
0.54 (0.52 - 0.57) (moderate)
Cut-off values for computerized wheeze detection
The study showed that the PulmoTrack® can reliably detect wheezing in neonates, with sensitivities of 85.7% for inspiratory and 84.6% for expiratory wheezes and specificities of 80.7% and 82.5%, respectively, using appropriate cut-off values. Computerized wheeze detection reliably detects even short periods of wheezing, as reflected by the low cut-off values of 2% for inspiratory and 3% for expiratory wheezing.
The equipment used in this study differs from that used in previous studies in older children, in which sound was recorded by five sensors [13, 23]. Due to the smaller thoraxes in infants aged <1 year, we used only two chest microphones, as suggested by the developers of the PulmoTrack®. Using five sensor positions simultaneously, the PulmoTrack® has been validated in children aged 6–14 years, with a slightly higher sensitivity (91%) and specificity (89%) in wheeze detection than the consensus by a panel of pulmonary experts who performed auscultation of the same respiratory sounds .
The inter-observer reliability for wheeze detection, expressed as the Fleiss Kappa coefficient, was moderate in our study, reflecting a higher inter-observer reliability than reported in most previous studies [17, 28–30]. ROC analysis showed cut-off values of >2% for inspiratory and >3% for expiratory wheeze. In contrast, wheeze rates <5% in older children were not considered clinically significant , as healthy children have wheeze rates <5%, with a wheeze rate >10% proposed as a cutoff value .
The disparity in lung sound nomenclature has been cited as contributing to disagreements among observers [4, 5, 31]. To prevent this disparity we followed the standardized nomenclature proposed by the American Thoracic Society (ATS)  and the International Symposium on Lung Sounds (ILSA) . Although the frequency and duration of wheezes in adults have been defined [32, 34], these definitions are lacking for neonates. Cutoff values in neonates <1 year may differ from those in older children and adults.
This study has several strengths and limitations. The main strengths include the use of a larger sample size than in previous studies on wheeze detection in infants [3, 20] and the use of the same investigators, equipment, and protocol for all patients. Moreover, all the assessed lung sounds were recorded, allowing the three observers to listen to exactly the same sounds. To our knowledge, this study is one of the largest single-center comprehensive studies to compare computerized wheeze detection with the assessment of an expert panel and to analyze inter-observer reliability regarding the detection of wheezing.
One study limitation was that all sound recordings were performed in a quiet lung function testing unit. Thus, we cannot determine the quality of computerized wheeze detection in noisier clinical settings. Moreover, all infants included in our study were sedated for LFT, preventing a determination of the quality of computerized wheeze detection in awake and possibly restless infants.
Computerized wheeze detection using PulmoTrack® is feasible and reliable in neonates <1 year when using appropriate cut-off values for inspiratory and expiratory wheeze rate. This method provided quantitative and noninvasive information about the extent of wheezing, in contrast to the assessment by trained clinicians, which was subjective and only moderate in the inter-observer agreement. Since this included only infants indicated for LFT due to pulmonary impairment, further studies are needed to evaluate lung sounds in healthy infants.
The authors thank Dr. Scott Butler of English Manager Science Editing, Sydney, Australia, for linguistic revision.
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