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The Development of an Artificial Intelligence Based Dry Eye Risk Prediction Model Incorporating Diabetes-Related Factors Utilizing Online Database

The Development of an Artificial Intelligence Based Dry Eye Risk Prediction Model Incorporating Diabetes-Related Factors Utilizing Online Database

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500097355
Enrollment
Unknown
Registered
2025-02-18
Start date
2025-01-06
Completion date
Unknown
Last updated
2025-02-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Dry eye

Interventions

Gold Standard:(1) If there are one of the subjective symptoms such as eye dryness, foreign body sensation, burning sensation, fatigue, discomfort, eye redness, and vision fluctuations, the Chinese Dry
At the same time, patients with FBUT=7 points or OSDI>=13 points
at the same time, patients with FBUT>5 s and 5 mm/5 min and = 5 points) can diagnose dry eye.
Index test:The validation of clinical patient data was conducted using a dry eye disease risk prediction model constructed with six machine learning algorithms based on RStudio (2024.09.0+375), includ

Sponsors

Xi'an Jiaotong University Second Affiliated Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
20 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.Age between 20-80; 2.Possess sufficient cognitive ability to give informed consent.

Exclusion criteria

Exclusion criteria: 1.Refractive interstitial clouding affects fundus imaging quality; 2.History of eye surgeries; 3.Wearers of corneal contact lenses within 1 year; 4.Patients with pterygium, conjunctivitis, tear duct obstruction and other diseases of the cornea, eyelids and lacrimal apparatus.

Design outcomes

Primary

MeasureTime frame
Area Under the Receiver Operating Characteristic Curve, AUC;Sensitivity;

Secondary

MeasureTime frame
False Negative Rate, FNR;False Positive Rate, FPR;Accuracy rate;Positive Predictive Value, PPV;Specificity;Negative Predictive Value, NPV;

Countries

China

Contacts

Public ContactZhang Xiaohui

Xi'an Jiaotong University Second Affiliated Hospital

tonyzxh0324@163.com+86 29 87679449

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026