The prevalence of obstructive sleep apnea hypopnea syndrome (OSAHS) is high. The development of telemedicine and mobile applications play an important role in the diagnosis and screening of OSAHS patients.

To evaluate the value of smartphone snoring analysis software Mianyun Sara in screening of Chinese adults with OSAHS.

One hundred and thirty patients〔mean age (49.7±17.4) years old, 70% male and 30% female, mean body mass index (28.2±5.0) kg/m²〕who were admitted to the Sleep Center of Peking University People's Hospital from April to December 2020 were selected and underwent overnight monitoring with Mianyun Sara and polysomnography (PSG) simultaneously. The relevant indicators generated by Mianyun Sara's automatic analysis and the relevant indicators interpreted by sleep professional technicians according to the recommended guidelines, the agreement between the apnea hypopnea index (AHI) derived from this method and PSG were evaluated, as well as the sensitivity and specificity of the diagnosis of OSAHS.

(1) The total sleep time (TST) monitored by Mianyun Sara was 523.67 (497.50, 542.64) min, and the TST monitored by PSG was 408.25 (364.25, 462.50) min, the difference was statistically significant (Z=-9.540, P<0.001) . The AHI monitored by Mianyun Sara was 15.83 (6.18, 27.49) times/h, and the AHI monitored by PSG was 18.25 (6.15, 35.68) times/h, the difference was statistically significant (Z=-2.601, P=0.009) . (2) There was a positive correlation between the AHI obtained by the two monitoring methods (r=0.645, P<0.001) . Bland-Altman analysis showed that the AHIs measured by Mianyun Sara and PSG were statistically consistent, with an average difference of -5.7 times/h, and the 95% consistency limit of (-40.5, 29.2) times/h. (3) Taking AHI≥5 times/h as the gold standard for the diagnosis of OSAHS, Mianyun Sara's optimal diagnostic value for OSAHS was AHI>8.34 times/h, with a corresponding sensitivity of 83.81% and a specificity of 92.00%. The area under the curve (AUC) was 0.91 (0.84, 0.95) , the positive predictive value (PPV) was 97.8%, and the negative predictive value (NPV) was 57.5%, at different AHI thresholds (5, 15, 30 times/h) , the sensitivity/specificity corresponding to the best diagnostic value were 83.8%/92.0%, 88.2%/74.1% and 64.9%/91.4%, respectively.

Mianyun Sara has a good screening value for adult OSAHS patients and there is close agreement between Mianyun Sara and PSG.

睡眠呼吸暂停低通气综合征（OSAHS）患病率高，而远程医疗的发展、便携式移动应用的使用在OSAHS患者的诊断、筛查中起着重要作用。

评价智能手机鼾声分析软件眠云Sara在中国成人OSAHS筛查中的价值。

对2020年4—12月就诊于北京大学人民医院睡眠中心的130例患者〔平均年龄（49.7±17.4）岁，男性占70%，平均体质指数（28.2±5.0） kg/m²〕，同时使用眠云Sara和多导睡眠监测（PSG）进行整夜监测，对比眠云Sara自动分析生成的相关指标与睡眠专业技术人员根据推荐指南判读PSG所得的相关指标，评价该方法得出的呼吸暂停低通气指数（AHI）与PSG结果的一致性，以及诊断OSAHS的灵敏度和特异度。

（1）眠云Sara监测的总睡眠时间（TST）为523.67（497.50，542.64）min，PSG监测的TST为408.25（364.25，462.50）min，差异有计学意义（Z=-9.540，P<0.001）。眠云Sara监测的AHI为15.83（6.18，27.49）次/h，PSG的AHI为18.25（6.15，35.68）次/h，二者差异也有统计学意义（Z=-2.601，P=0.009）。（2）两种监测方法所得AHI呈正相关（r=0.645，P<0.001），Bland-Altman一致性检验示眠云Sara及PSG所测得的AHI在统计学上相一致，其平均差异为-5.7次/h，95%一致性界限为（-40.5，29.2）次/h；（3）以PSG的AHI≥5次/h作为诊断OSAHS的金标准，眠云Sara对OSAHS的最佳诊断值为AHI>8.34次/h，其对应的灵敏度为83.81%、特异度为92.00%，曲线下面积（AUC）为0.91（0.84，0.95），阳性预测值（PPV）为97.8%，阴性预测值（NPV）为57.5%，在不同的AHI阈值下（5、15、30次/ h），其最佳诊断值所对应的灵敏度/特异度分别为83.8%/92.0%、88.2%/74.1%和64.9%/91.4%。

智能手机鼾声分析软件对中国成人OSAHS患者具有较好的初筛价值，与PSG具有良好的一致性。