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Non-contact infrared thermometry temperature measurement for screening fever in children.

机译:非接触式红外测温仪可测量儿童发烧的温度。

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BACKGROUND: During the SARS epidemic, mass fever screening at border control points and public hospitals was done by measuring forehead temperature by non-contact infrared thermometry. However, its accuracy is not well documented. METHODS: We evaluated the agreement of non-contact infrared forehead temperature (NIFT) measurement by comparing NIFT readings with tympanic temperatures taken in children (1 mth to 18 yrs) admitted to the general paediatric wards of Kwong Wah Hospital, Hong Kong. RESULTS: A total of 567 patients were recruited and 1000 pairs of readings were obtained. The incidence of fever, defined as tympanic temperature (in rectal model) >38 degrees C (100.4 degrees F), was 12.3%. The mean difference between NIFT and tympanic temperature was 2.34 degrees C (4.21 degrees F) and the 95% limit of agreement between NIFT and tympanic temperature was 0.26-4.42 degrees C (0.47-7.96 degrees F). NIFT was significantly lower than tympanic temperature readings. The optimal cut-off point of NIFT derived from the receiver-operator characteristics curve for fever definition was 35.1 degrees C (95.2 degrees F). The sensitivity, specificity, positive predictive value and negative predictive value of this cut-off point for fever screening were 89.4%, 75.4%, 33.7% and 98.1%, respectively. CONCLUSIONS: NIFT measurement has a reasonable accuracy in detecting tympanic fever in children. However, one should be aware of the high false-positive rate of fever screening using NIFT.
机译:背景:在SARS流行期间,通过非接触式红外测温仪测量额头温度,在边境检查站和公立医院进行了大规模发热筛查。但是,其准确性尚未得到充分证明。方法:我们通过将NIFT读数与香港广华医院普通儿科病房儿童(1个月至18岁)的鼓膜温度进行比较,评估了非接触式红外前额温度(NIFT)测量的一致性。结果:共招募567例患者,获得1000对读数。发烧的发生率定义为鼓膜温度(在直肠模型中)> 38摄氏度(100.4华氏度),为12.3%。 NIFT与鼓膜温度之间的平均差为2.34摄氏度(4.21华氏度),NIFT与鼓膜温度之间的一致性的95%限制为0.26-4.42摄氏度(0.47-7.96华氏度)。 NIFT显着低于鼓膜温度读数。从接收者-操作者特征曲线得出的发烧清晰度的最佳NIFT截止点为35.1摄氏度(95.2华氏度)。该临界点对发烧筛查的敏感性,特异性,阳性预测值和阴性预测值分别为89.4%,75.4%,33.7%和98.1%。结论:NIFT测量在检测儿童鼓膜热方面具有合理的准确性。但是,应该意识到使用NIFT进行发烧筛查的假阳性率很高。

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