Individual Analysis
Evaluate one participant using symptom and clinical sign data.
Individual AnalysisDECODE
Evaluate dry eye symptom-sign discordance for an individual participant or an anonymized batch dataset.
DECODE (Dry Eye COncordance and Discordance Evaluator) is a proof-of-concept framework designed to quantify the relationship between dry eye symptoms and clinical signs.
DECODE transforms symptom questionnaires and clinical signs to a common 0-to-1 severity scale, where 0 represents lower severity and 1 represents greater severity. Discordance is then calculated:
Discordance = normalized symptom severity − normalized sign severity
Positive values indicate symptom-predominant discordance (symptoms are more severe than signs), while negative values indicate sign-predominant discordance (signs are more severe than symptoms). Values closer to zero indicate greater symptom–sign concordance.
DECODE provides results at three complementary levels:
By default, DECODE uses the mean of the available normalized symptom questionnaires and clinical signs to calculate overall discordance. Users may alternatively select the worst approach, in which the most severe available normalized symptom score and the most severe available normalized clinical sign are used.
When data from both eyes are available, DECODE uses the mean of both eyes by default. Users may alternatively select the worst eye approach. Eye-specific results can also be displayed separately when desired.
The calculation method selected by the user is recorded in the final report to facilitate transparency and reproducibility.
DECODE does not require every clinical measurement to be available. To calculate overall discordance, at least one symptom questionnaire and either TBUT or NIBUT must be entered. OSDI-6 is the recommended symptom questionnaire, according to DEWS-III. Additional available signs are incorporated into the corresponding overall, domain-specific, and sign-specific calculations.
Missing measurements are not treated as zero and are excluded from the corresponding calculations.
DECODE can be used to evaluate an individual patient or to process an anonymous research dataset using the DECODE data template. In batch analysis, the same calculation rules are applied consistently across all eligible participants.
DECODE is currently a pilot, proof-of-concept framework and has not yet been clinically validated as the optimal method for measuring symptom–sign discordance. The best approaches for combining measurements, selecting mean versus worst values, handling bilateral data, and interpreting the magnitude of discordance require validation in independent cohorts.
When using DECODE for research or publications, users should report the measurements included and the calculation settings used.
Patient names are not stored.
Evaluate one participant using symptom and clinical sign data.
Individual AnalysisAnalyze multiple anonymized participants using CSV or XLSX.
Batch Analysis