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A Prospective Study: Artificial Intelligence-Assisted Screening and Diagnosis of Ptosis and Evaluation of Levator Palpebrae Superioris Muscle Strength

A Prospective Study: Artificial Intelligence-Assisted Screening and Diagnosis of Ptosis and Evaluation of Levator Palpebrae Superioris Muscle Strength

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500112450
Enrollment
Unknown
Registered
2025-11-14
Start date
2025-12-01
Completion date
Unknown
Last updated
2025-11-17

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

Conditions

ptosis

Interventions

Gold Standard:The gold standard for grading the severity of ptosis in this study was formulated with reference to expert consensuses such as the Expert Consensus on the Diagnosis and Treatment of Ptos
Index test:Facial videos captured by smartphones was used for qualitative and quantitative assessment of ptosis. The intelligent quantitative evaluation and ophthalmopathy screening/diagnosis model fo

Sponsors

The Zhongshan Ophthalmic Center,Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
3 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. No restriction on gender; aged 3–80 years. 2. Patients requiring clinical measurement of palpebral fissure height and levator palpebrae superioris muscle strength. 3. The informed consent form has been signed by the individuals or their guardian; 4. Patients diagnosed with ptosis by clinical outpatient doctors after manual measurement of MRD1 and LF using a ruler. 5. Normal subjects confirmed to be free of ptosis by clinical outpatient doctors after manual measurement of MRD1 and LF using a ruler.

Exclusion criteria

Exclusion criteria: 1. Unable to cooperate with the examination; 2. Video quality does not meet clinical requirements; 3. The informed consent form has not been signed by the individuals or their guardian;

Design outcomes

Primary

MeasureTime frame
Area Under the Curve (AUC) of the artificial intelligence (AI)-based ptosis diagnosis model;

Secondary

MeasureTime frame
Sensitivity of the artificial intelligence (AI)-based ptosis diagnosis model;Negative Predictive Value (NPV) of the AI-based ptosis diagnosis model;Negative Likelihood Ratio (N-LR) of the AI-based ptosis diagnosis model;Accuracy of the AI-based ptosis diagnosis model;Confusion Matrix of the AI-based ptosis diagnosis model;Specificity of the AI-based ptosis diagnosis model;Positive Likelihood Ratio (P-LR) of the AI-based ptosis diagnosis model;Positive Predictive Value (PPV) of the AI-based ptosis diagnosis model;

Countries

China

Contacts

Public ContactHaotian Lin

The Zhongshan Ophthalmic Center,Sun Yat-sen University

linht5@mail.sysu.edu.cn+86 20 6661 8931

Outcome results

None listed

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