Abstract
PURPOSE: To assess the diagnostic performance of the InflammaDry test in diagnosing dry eye disease (DED) using different diagnostic criteria and across varying severities.
METHODS: A retrospective study was conducted on 1,515 patients. Subjects were categorized into three groups: Group (1) DED based on Dry Eye Workshop-II (DEWS-II): Ocular Surface Disease Index (OSDI) ≥ 13 and at least one abnormal clinical sign (non-invasive tear break-up time [NIBUT] < 10 s, osmolarity > 308 mOsm/L, or corneal/conjunctival staining). Group (2) DED based on criteria used in prior clinical trials: OSDI > 13, Schirmer < 10 mm in 5 min, NIBUT < 10 s, and keratoconjunctival staining. Group (3) Healthy controls: OSDI ≤ 7, NIBUT ≥ 10 s, Schirmer ≥ 10 mm, and no keratoconjunctival staining. DED severity was classified using the ODISSEY European Consensus Group's definitions into severe and non-severe. Sensitivity, specificity, and predictive values were calculated for both criteria.
RESULTS: 1,363 patients were included in Group 1, 401 in Group 2, and 152 in Group 3. Sensitivity was 81.30% in the population diagnosed using previous clinical trial criteria but decreased to 69.99% when applying the DEWS-II criteria. Specificity was 38.16% in both groups, with 409/467 false negatives respectively.
CONCLUSION: InflammaDry shows good sensitivity in detecting DED in highly symptomatic cases with multiple clinical signs, but its performance decreases when broader criteria like DEWS-II are used. While valuable for detecting inflammation, routine use for DED diagnosis may lead to false negatives, especially in milder cases.
| Translated title of the contribution | Rendimiento real del test inflammadry en el diagnóstico del ojo seco: un análisis de 1.515 pacientes |
|---|---|
| Original language | English (US) |
| Pages (from-to) | 1623-1631 |
| Number of pages | 9 |
| Journal | Graefe's Archive for Clinical and Experimental Ophthalmology |
| Volume | 263 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jan 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Ophthalmology
- Sensory Systems
- Cellular and Molecular Neuroscience
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