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Published on: January 13, 2023
Prediction of wound healing status following dental extraction using Adapted-University of Connecticut osteonecrosis
Isti R Suryani1,2, Sohaib Shujaat1,3, Minh T That1
1Department of Imaging & Pathology, OMFS IMPATH Research Group, Faculty of Medicine, KU Leuven & Oral and Maxillofacial Surgery University Hospitals Leuven Leuven Belgium.
Background And Aims:
There is a scarcity of evidence concerning the use of a prognostic instrument for predicting normal healing, delayed healing, and medication-related osteonecrosis of the jaw (MRONJ) occurrence following tooth extraction in medically compromised patients. The present study aimed to predict healing outcomes following tooth extraction in medically compromised patients using an Adapted-University of Connecticut osteonecrosis numerical scale (A-UCONNS).
Methods:
The digital medical records of medically compromised patients were reviewed, who underwent tooth extraction. The A-UCONNS parameters included the initial pathological condition, dental procedures, comorbidities (smoking habits, type and duration of medication, and type of intervention), and administered antiresorptive (AR) medications. Each parameter was assigned a different weight, and the scores were then accumulated and classified into three categories: minimal risk (less than 10), moderate risk (10-15), and significant risk (16 or more). The patient's healing status was categorized as normal healing, delayed healing, or MRONJ.
Results:
A total of 353 male patients (mean age: 67.4 years) were recruited from a pool of 3977 patients, where 12.46% of patients had delayed wound healing, and 18.69% developed MRONJ. The median A-UCONNS scores for MRONJ were higher based on initial pathology, comorbidity, and AR drugs compared to normal or delayed healing. In addition, a significant relationship existed between A-UCONNS and healing outcomes (p < 0.05), with a unit increase in A-UCONNS associated with 1.347 times higher odds of experiencing MRONJ compared to normal healing. In contrast, a low score was linked to an increased likelihood of normal wound healing.
Conclusion:
The A-UCONNS could act as a promising tool for predicting wound healing outcomes. It can provide clinicians the ability to pinpoint patients at high risk and allow tailoring of patient-specific strategies for improving healing outcomes following tooth extraction.
