We Þtted an exact logistic regression model using age group and family history of glaucoma as predictor variables. The parameter estimates for family history and the interaction term were not signiÞcantly different from zero (p > 0.5 for both parameters).

7.4Discussion

A screening examination of ÒhealthyÓ feeling subjects was successfully performed to identify glaucoma at an early stage. The screening was purely focused on the morphology of the optic nerve head. We used a telemedical approach with non-mydriatic fundus cameras.

The telemedical evaluation has had a good reliability with an intraobserver reliability of 0.884 and an interobserver reliability of 0.740.

In the presented study, the appearance of the optic nerve head was evaluated by monoscopic fundus images of 45¡ acquired by telemedical approach using expert assessment. Stereoscopic fundus images would allow more reliable results, but a stereoscopic fundus camera was not applicable as we intended to avoid pharmacological dilatation of the pupil.

Several articles in the literature discussed the prevalence of different forms of glaucoma and glaucomatous optic nerve atrophy [15]. Among Caucasians, open-angle glaucoma (OAG) was the most common form, which led to a comparison of the prevalences of OAG among Caucasians from other studies with the prevalence of glaucoma disease obtained by our study. A meta-analysis of several studies on prevalence of OAG was given by the Eye Diseases Prevalence Research Group [16]. Prevalences of OAG among Whites reported in this meta-analysis are listed in Table 7.2. These prevalences were estimated from pooled data of the Baltimore Eye Survey [17], the Blue Mountains Eye Study [18], the Beaver Dam Study [19], the Rotterdam Study [3], and the Melbourne Visual Impairment Project [6].

A full diagnosis of open-angle glaucoma requires an evaluation of the optic nerve head and visual Þeld testing. In the mentioned studies, the diagnosis of OAG was based on optic nerve appearance and visual Þeld defects. Therefore,

Fig 7.3 The logistic regression model illustrating the inßuence of age on the prevalence of glaucomatous optic nerve atrophy for women

we emphasize that the reported prevalences of OAG are not comparable to our results, which can serve as estimates of the prevalences of glaucomatous atrophy of the optic nerve head, the main sign of OAG. Furthermore, we point out that our selection process differs from the mentioned studies, and we admit that selection on a Þrst-come, Þrst-serve basis leaves room for unknown bias.

Age is a well-known risk factor for glaucoma. We conÞrmed this with our results, which show that the risk of glaucomatous optic nerve atrophy arises with age (see Fig. 7.2).

Two logistic regression models illustrate the inßuence of age on prevalence of glaucomatous optic nerve atrophy separated for women and men. Figure 7.3 shows the logistic regression model of women. In consideration of the small number of cases, we computed the exact logistic regression (p <0.01 in both cases). The exactness of Þt of the logistic regression model is illustrated by a moving average with bandwidth of 5 years. Prevalence of OAG in the meta-analysis [16] was higher than that of glaucomatous optic nerve atrophy. Although this is especially true for women, we could not verify a statistically signiÞcant difference between men and women with respect to the prevalence of glaucomatous optic nerve atrophy.

Compared with other recent studies, our study has a high number of participants (9,602 participants; Rotterdam Study: n = 6,281; Melbourne

Visual Impairment Project: n = 3,265; and Reykjavik Eye Study: n = 1,045).

Telemedical evaluation after standardized recording of retinal images allowed a fast and efÞcient screening procedure allowing high-volume screening. Furthermore, physicians are independent of examination time and place, as results are made available to them in a fast and reliable way via secure Internet.

The data of our tele-glaucoma study allow the comparison of the prevalence of glaucomatous optic nerve atrophy among a working population in Germany with the prevalence of OAG among Caucasian populations reported in other studies. The data in our study do not necessarily reßect the true prevalence of glaucoma in Germany. We found a prevalence of glaucomatous optic nerve head atrophy of about 0.36% in our study population.

The medical goal to decrease the incidence of blindness caused by glaucoma by early detection and examination of persons suffering from glaucomatous optic nerve atrophy can be attained by telemedical screening examinations of color images of the retina and the papilla. Ophthalmologic diagnosis of images of the papilla via telemedical techniques is a simple examination method, which allows the identiÞcation of persons with raised glaucoma risk by combination of standardized analysis of the optic nerve head with collection of anamnestic data. The application of modern telemedical communication technology allows examination of more than 100 persons per day and ensures continuous quality control of all medical steps.

7.5Perspectives

In our study, the evaluation of fundus images to diagnose glaucomatous optic nerve atrophy was strongly standardized. The results were based purely on the appearance of the optic nerve head using standardized criteria. Nevertheless, the evaluation is open to subjective bias. To alleviate this drawback in future works, the usage of automated pattern recognition techniques is appropriate. Our group [20] proposed a novel pattern recognition approach to glaucoma detection

Fig. 7.5 Receiver operating characteristic (ROC) curves for detecting glaucoma by an automated procedure

True positive rate

False positive rate

On a sample set consisting of 575 fundus images, Þvefold cross validation leads to a classiÞcation accuracy of 80%. The resulting area under the ROC curve (AUC) of 88% is competitive with the established topography-based glaucoma probability score of confocal scanning laser tomography, which is 87% (see Fig. 7.5).

The novel Glaucoma Risk Index (GRI) enabled a reliable detection performance based on relatively low-cost color fundus images which is comparable to more expensive traditional methods. Thus, this automated approach might lead to a Þrst, objective, low-cost glaucoma diagnosis followed by more elaborate clinical examinations only if necessary.

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