Endodontic Retreatment

2

Review clinical trials related to Endodontic Retreatment. Use filters to narrow results by trial status, phase, treatment, biological sex and sponsor.

Condition / disease
Location
Status: Not yet recruiting

Cryotherapy, PGE2, NGF Levels and Pain After Endodontic Retreatment

This prospective, randomized, controlled, single-blind, parallel-group clinical trial evaluates whether intracanal cryotherapy reduces postoperative pain and inflammatory biomarker levels following single-visit endodontic retreatment of teeth with asymptomatic apical periodontitis. A total of 100 patients (18-65 years, systemically healthy, ASA I-II) requiring non-surgical retreatment of a single-rooted mandibular premolar tooth will be randomly assigned via computer-generated randomization to one of two equal groups (n=50 each): a cryotherapy group, receiving intracanal final irrigation with sterile saline cooled to 2.5°C for 5 minutes, and a control group, receiving the same irrigation protocol with saline at room temperature (20-22°C). Salivary nerve growth factor (NGF) and gingival crevicular fluid (GCF) prostaglandin E2 (PGE2) levels will be measured by ELISA at baseline (T0), 24 hours (T1), and 72 hours (T2). Postoperative pain will be assessed using a visual analog scale (VAS, 0-100 mm) at 6, 12, 24, 48, and 72 hours and on day 7, with the 24-hour VAS score as the primary comparison point. Rescue analgesic (paracetamol) consumption will also be recorded and compared between groups. The study aims to determine whether intracanal cryotherapy lowers postoperative pain and biomarker levels compared to standard-temperature irrigation, and to evaluate the correlation between PGE2/NGF levels and pain intensity.

Participants needed: 100
Trial details
Age: 18-65Biological sex: AllType: InterventionalSponsor: Alanya Alaaddin Keykubat UniversityUpdated: Jul 29, 2026Locations: 1
Eligibility criteria

Age 18-65 years, systemically healthy individuals (ASA I-II) [+4]

Pregnancy or lactation [+10]

Status: Not yet recruiting

Development and Validation of a Deep Learning Model to Predict Endodontic Retreatment Difficulty From Periapical Radiographs

The aim of this study is to develop and evaluate an artificial intelligence-based model capable of analyzing periapical radiographs of maxillary and mandibular molars to predict the difficulty level of non-surgical root canal retreatment. By integrating deep learning techniques with routinely acquired periapical radiographs, this study aims to enhance diagnostic support, improve clinical decision-making, and facilitate appropriate case selection or referral in endodontic practice.

Participants needed: 123
Trial details
Biological sex: AllType: InterventionalSponsor: Cairo UniversityUpdated: May 28, 2026
Eligibility criteria

Not listed