Habukawa Chizu, Ohgami Naoto, Matsumoto Naoki, Hashino Kenji, Asai Kei, Sato Tetsuya, Murakami Katsumi
Department of Pediatrics, Minami Wakayama Medical Center, Tanabe, Japan.
Technology Development HQ, Omron Healthcare Co., Ltd., Muko, Japan.
Asia Pac Allergy. 2020 Jul 13;10(3):e26. doi: 10.5415/apallergy.2020.10.e26. eCollection 2020 Jul.
Wheezing is a typical symptom of respiratory conditions. Few objective methods are available for predicting sleep disturbance in young children with wheezing.
We investigated whether wheezing characteristics, detected by lung-sound analysis, were associated with risk of sleep disturbance.
We recorded the lung sounds of 66 young children (4-59 months) every morning, for the entire duration of a wheezing episode. On lung-sound analysis, wheezing was displayed as horizontal bars of intensity with corresponding sharp peaks of power. The sharp peak of power was defined as a wheeze band. Wheezing characteristics (e.g., number, frequency, duration, and frequency of maximum intensity of wheeze bands) were analyzed using lung-sound analysis. Patients were divided into 3 groups based on sleep disturbance on the first night after wheezing was recorded: mild group (no sleep disturbance and disappearance of wheezing within 2 days), moderate group (no sleep disturbance but disappearance of wheezing after 3 or more days), and severe group (sleep disturbance and disappearance of wheezing after 3 or more days). Wheezing characteristics on the first morning were compared among the 3 groups based on sleep disturbance on the first night.
The highest frequency, the frequency of maximum intensity, and the number of wheeze bands per 30 seconds were significantly higher in the severe group than in the mild group ( < 0.005, < 0.005, < 0.001, respectively). The number of wheeze bands per 30 seconds was a predictor of nighttime sleep disturbance, with a cutoff value of 11.1. The sensitivity, specificity, and positive- and negative-predictive values were 100%, 65%, 32%, and 100% ( < 0.001), respectively, with an area under the curve of 0.86 ± 0.05.
The number of wheeze bands per 30 seconds on lung-sound analysis was a useful indicator of risk of prolonged exacerbation.
喘息是呼吸系统疾病的典型症状。目前几乎没有客观方法可用于预测喘息幼儿的睡眠障碍。
我们调查了通过肺音分析检测到的喘息特征是否与睡眠障碍风险相关。
我们在每天早晨记录66名幼儿(4 - 59个月)喘息发作全过程的肺音。在肺音分析中,喘息表现为强度的水平条以及相应的功率尖峰。功率尖峰被定义为喘息带。使用肺音分析对喘息特征(如喘息带的数量、频率、持续时间和最大强度频率)进行分析。根据记录喘息后第一晚的睡眠障碍情况,将患者分为3组:轻度组(无睡眠障碍且喘息在2天内消失)、中度组(无睡眠障碍但喘息在3天或更长时间后消失)和重度组(有睡眠障碍且喘息在3天或更长时间后消失)。基于第一晚的睡眠障碍情况,比较3组在第一个早晨的喘息特征。
重度组每30秒的最高频率、最大强度频率和喘息带数量显著高于轻度组(分别为P < 0.005、P < 0.005、P < 0.001)。每30秒的喘息带数量是夜间睡眠障碍的一个预测指标,截断值为11.1。敏感性、特异性、阳性预测值和阴性预测值分别为100%、65%、32%和100%(P < 0.001),曲线下面积为0.86±0.05。
肺音分析中每30秒的喘息带数量是长期病情加重风险的一个有用指标。