An algorithm as a diagnostic tool for central ocular motor disorders, also to diagnose rare disorders.

ABSTRACT:

Background

Recently an increasing number of digital tools to aid clinical work have been published. This study's aim was to create an algorithm which can assist physicians as a "digital expert" with the differential diagnosis of central ocular motor disorders, in particular in rare diseases.

Results

The algorithm's input consists of a maximum of 60 neurological and oculomotor signs and symptoms. The output is a list of the most probable diagnoses out of 14 alternatives and the most likely topographical anatomical localizations out of eight alternatives. Positive points are given for disease-associated symptoms, negative points for symptoms unlikely to occur with a disease. The accuracy of the algorithm was evaluated using the two diagnoses and two brain zones with the highest scores. In a first step, a dataset of 102 patients (56 males, 48.0?±?22?yrs) with various central ocular motor disorders and underlying diseases, with a particular focus on rare diseases, was used as the basis for developing the algorithm iteratively. In a second step, the algorithm was validated with a dataset of 104 patients (59 males, 46.0?±?23?yrs). For 12/14 diseases, the algorithm showed a sensitivity of between 80 and 100% and the specificity of 9/14 diseases was between 82 and 95% (e.g., 100% sensitivity and 75.5% specificity for Niemann Pick type C, and 80% specificity and 91.5% sensitivity for Gaucher's disease). In terms of a topographic anatomical diagnosis, the sensitivity was between 77 and 100% for 4/8 brain zones, and the specificity of 5/8 zones ranged between 79 and 99%.

Conclusion

This algorithm using our knowledge of the functional anatomy of the ocular motor system and possible underlying diseases is a useful tool, in particular for the diagnosis of rare diseases associated with typical central ocular motor disorders, which are often overlooked.

SUBMITTER: Kraus L 

PROVIDER: S-EPMC6688379 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature