Lindén Henriikka, Teppo Heikki, Revonta Matti
Department of Otorhinolaryngology, Kanta-Hame Central Hospital, Hameenlinna, Finland.
Eur Arch Otorhinolaryngol. 2007 May;264(5):477-81. doi: 10.1007/s00405-006-0206-8. Epub 2006 Nov 11.
Diagnosis of otitis media is based on detection of middle-ear fluid (MEF) and is both important and difficult to achieve. Also non-infectious MEF is important to detect, since it can compromise hearing. In this prospective, blinded study, spectral gradient acoustic reflectometry (SG-AR) was evaluated as an indicator of MEF among children. Sensitivity, specificity and positive and negative predictive values of SG-AR in detecting MEF were calculated in children undergoing ambulatory surgery for recurrent or secretory otitis media using otomicroscopic myringotomy as the reference method of confirming middle-ear status. Final study material consisted of 376 ears. Pattern recognition of SG-AR curves reached the best combination of sensitivity and specificity (69 and 97%, respectively), and the best combination of positive (PPV) and negative (NPV) predictive values (93 and 83%, respectively), in detection of MEF. With a spectral gradient value of <80 degrees , the sensitivity was 75% and specificity 71%. With <50 degrees , PPV was 78%, and with >or=100 degrees , NPV was 86%. The diagnostic power of SG-AR was comparable to that reported with pneumatic otoscopy and tympanometry. It was equally effective in detecting both MEF cases and healthy ears. Pattern recognition seems to improve its performance. We recommend the use of pattern recognition of SG-AR as a screening method for MEF among children.
中耳炎的诊断基于中耳积液(MEF)的检测,这一过程既重要又颇具难度。检测非感染性MEF也很重要,因为它可能会损害听力。在这项前瞻性双盲研究中,对光谱梯度声反射测量法(SG-AR)作为儿童MEF指标进行了评估。以耳显微镜下鼓膜切开术作为确认中耳状态的参考方法,计算了接受门诊手术治疗复发性或分泌性中耳炎的儿童中SG-AR检测MEF的敏感性、特异性以及阳性和阴性预测值。最终研究材料包括376只耳朵。在检测MEF时,SG-AR曲线的模式识别达到了敏感性和特异性的最佳组合(分别为69%和97%),以及阳性(PPV)和阴性(NPV)预测值的最佳组合(分别为93%和83%)。光谱梯度值<80度时,敏感性为75%,特异性为71%。<50度时,PPV为78%,≥100度时,NPV为86%。SG-AR的诊断能力与鼓气耳镜检查和鼓室导抗图报告的结果相当。它在检测MEF病例和健康耳朵方面同样有效。模式识别似乎能提高其性能。我们建议将SG-AR的模式识别作为儿童MEF的筛查方法。