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Assessment of associations of people with pimples over face

Evaluating associations and metabolic parameters in adult acne and exploration of deep learning techniques for acne grading: A cross-sectional study - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/08/092570
Enrollment
150
Registered
2025-08-07
Start date
Unknown
Completion date
Unknown
Last updated
2025-08-18

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

Conditions

Health Condition 1: L700- Acne vulgaris

Interventions

Intervention1: Nil: Nil

Sponsors

Dr Ishita Bansal
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: All consulting adult patients of age more than 25 years of Acne vulgaris, who visit the dermatology outpatient/inpatient department at KMC, Manipal

Exclusion criteria

Exclusion criteria: 1)Clinical diagnosis of rosacea which can mimic acne 2)Acneiform eruptions 3)Drug induced acne 4)Truncal acne without any face lesions

Design outcomes

Primary

MeasureTime frame
1. To study the clinical types and associations of adult acne 2. To grade acne based on modified Global Acne Grading SystemTimepoint: Baseline—

Secondary

MeasureTime frame
1. To integrate Artificial intelligence methods of machine learning / deep learning in acne grading 2. To correlate acne with visceral adiposity index and Insulin resistance in a subset of study subjectsTimepoint: 2 years—

Countries

India

Contacts

Public ContactDr Ishita Bansal

Kasturba Medical College, MAHE, Manipal

ishib99@gmail.com9711942808

Outcome results

None listed

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