Purpose

To construct normalized ocular surface temperature (NOST) models for different tear film characteristics and evaluate its potential in dry-eyes screening.

Methods

We included 227 right eyes of 227 patients. Tear film characteristics were categorized into 4 types according to fluorescein tear film breakup time (FTBUT) and Schirmer test results, namely type 1: FTBUT>5 and Schirmer>5; type 2: FTBUT≤5 and Schirmer>5; type 3: FTBUT≤5 and Schirmer≤5; and type4: FTBUT>5 and Schirmer≤5. Ocular surface temperature was measured by a video-thermographer. Mean temperatures of the central cornea were calculated from the videos of each frame during the 4-s blink interval. We first constructed individual NOST model for every tear characteristic. Patients with short TFBUT were included for further analysis when their OSDI was ≥23, FTBUT≤5, and Schirmer>5 mm. They were subdivided into short-BUT and short BUT with SPK subgroups according to the absence or presence of corneal fluorescein-stain. The NOST models of the normal, short-BUT and short BUT with SPK groups were separately constructed and the potential of screening analyzed via ROC curves.

Results

Each tear film type had a different NOST model. At 3 s after blinking, the order of NOST was type 4>type 1>type 3>type 2. In dry-eye screening, the NOST was normal > short-BUT > short BUT with SPK. The NOST displayed a sensitivity 0.87, specificity 0.80, and AUC 0.88 for diagnosing short BUT with SPK.

Conclusion

NOST models are useful in differentiating tear film characteristics and screening dry-eyes. It alleviates the discomfort and inconvenience encountered during conventional dry-eye diagnosis.

中文翻译：

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用于泪膜特性和干眼病评估的标准化眼表温度模型。

目的

为不同的泪膜特性构建标准化的眼表温度（NOST）模型，并评估其在干眼筛查中的潜力。

方法

我们纳入了227例患者的227例右眼。根据荧光素泪膜破裂时间（FTBUT）和Schirmer测试结果，将泪膜特性分为四种类型，即类型1：FTBUT> 5和Schirmer> 5；类型2：FTBUT≤5，Schirmer> 5；类型3：FTBUT≤5和Schirmer≤5; 和type4：FTBUT> 5，Schirmer≤5。眼表温度由视频热成像仪测量。根据4秒钟眨眼间隔中每帧的视频计算中央角膜的平均温度。我们首先针对每种撕裂特性构建了单独的NOST模型。当OSDI≥23，FTBUT≤5且Schirmer> 5 mm时，TFBUT短的患者被纳入进一步分析。根据是否存在角膜荧光素染色，将其分为短BUT和SPK亚组。

结果

每种泪膜类型都有不同的NOST模型。眨眼后3 s，NOST的顺序为4型> 1型> 3型> 2型。在干眼筛查中，NOST正常>短BUT>短BUT SPK。NOST对SPK短BUT的诊断灵敏度为0.87，特异性为0.80，AUC为0.88。

结论

NOST模型可用于区分泪膜特性和检查干眼症。它减轻了传统干眼症诊断过程中遇到的不适和不便。