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NCT07889895

AI Prediction of PIVC-Related Phlebitis

Sponsor: Kutahya Health Sciences University

View on ClinicalTrials.gov

Summary

This study aims to develop and validate multimodal AI-based prediction models for peripheral intravenous catheter (PIVC)-related phlebitis by integrating demographic, clinical, catheter-related, and phlebitis image data. The models will be evaluated for their ability to accurately predict phlebitis risk, with the goal of facilitating early identification, timely intervention, and improved patient safety.

Official title: Predicting Peripheral Intravenous Catheter-Related Phlebitis With AI-Based Models.

Key Details

Gender

All

Age Range

18 Years - 85 Years

Study Type

OBSERVATIONAL

Enrollment

461

Start Date

2025-07-15

Completion Date

2026-09-13

Last Updated

2026-10-22

Healthy Volunteers

No

Interventions

OTHER

Artificial Intelligence-Based Phlebitis Detection Model

An artificial intelligence-based model will be developed and evaluated to detect or predict phlebitis using clinical images. The model's performance will be assessed using image-based data.

Locations (2)

Kutahya Health Sciences University

Kütahya, Kütahya, Turkey (Türkiye)

Kutahya Health Sciences University

Merkez, Kütahya, Turkey (Türkiye)