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Prediction of periapical status and tooth extraction
L-L Kirkevang1,2, D Ørstavik2, G Bahrami3
1Section of Oral Radiology, Department of Dentistry, Health, Aarhus University, Aarhus, Denmark.
International Endodontic Journal
|November 19, 2015
Summary
The Periapical Index (PAI) score is the strongest predictor of periapical status and tooth extraction. A high baseline PAI score increases the risk of poor outcomes, highlighting the need for separate analyses for root-filled and non-root-filled teeth.
Area of Science:
- Dentistry
- Oral health research
- Radiographic assessment
Background:
- Periapical status significantly impacts overall oral health.
- Predicting periapical lesions and tooth extraction is crucial for treatment planning.
- The Periapical Index (PAI) is a standardized tool for assessing periapical lesions.
Purpose of the Study:
- To identify and analyze risk factors for predicting periapical status.
- To evaluate the Periapical Index (PAI) as a predictive tool for periapical status and extraction.
- To compare predictive factors for root-filled versus non-root-filled teeth.
Main Methods:
- Longitudinal study with 330 participants undergoing radiographic surveys over 5 years.
- Assessment of person-level (age, gender, smoking) and tooth-level (PAI, caries, bone level) variables.
- Ordered logistic regression analyses were performed separately for root-filled and non-root-filled teeth.
Main Results:
- Baseline Periapical Index (PAI) score was the most significant predictor for both periapical status and extraction (P < 0.0001).
- Non-root-filled teeth generally showed better outcomes than root-filled teeth.
- Other factors significantly influenced outcomes in non-root-filled teeth, with greater risk estimate variations.
Conclusions:
- The full-scale Periapical Index (PAI) is the strongest predictor of periapical status and extraction.
- Higher baseline PAI scores correlate with an increased risk of adverse outcomes.
- Separate analyses for root-filled and non-root-filled teeth are essential for accurate risk factor identification.
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