Validating cephalometric angular reconstruction for determining vertical dimension in edentulous patients
Year: 2025
Type: article
Abstract: BACKGROUND: Accurate vertical dimension of rest (VDR) is critical in complete denture fabrication. Along with conventional phonetic and electromyographic (EMG) methods; cephalometric angular reconstruction (CAR) has recently been proposed as a reliable approach that minimizes reliance on patient dexterity. This in-vivo study aimed to determine the effectiveness of the CAR method by comparing it with conventional and electromyographic methods in determining VDR in edentulous subjects. MATERIALS AND METHODS: Twenty completely edentulous patients were enrolled. For each patient, VDR was measured using phonetic, CAR, and EMG methods. Data were analyzed with SPSS version 23 using one-way ANOVA and independent t-tests. A sample size of 20 provided 80% power with an effect size of 0.8 at a significance level of 0.05. One month after denture insertion, patient satisfaction was assessed with a structured questionnaire. RESULTS: The mean VDR (cm) was 5.36 ± 0.61 for the conventional method, 5.35 ± 0.74 for CAR, and 5.64 ± 0.62 for EMG. Although the EMG method yielded slightly higher values, independent t-tests revealed no statistically significant differences between conventional and CAR (p = 0.962), conventional and EMG (p = 0.181), or CAR and EMG (p = 0.167). Patient satisfaction scores indicated favorable outcomes across all groups. CONCLUSION: There was no statistically significant difference among the three methods, confirming that CAR can serve as a viable alternative to conventional and EMG approaches. CLINICAL IMPLICATIONS: The CAR method may be particularly useful for patients with neuromuscular issues, psychological challenges, or limited cooperation during traditional VDR recording.
Source: BMC Oral Health
Authors: Aishwarya Mahajan, Vivek Vivek, Anuj K. Shukla, Chandana Nair, Mudita Chaturvedi, Ghazala Suleman, Tushar Vitthalrao Bhagat, Mohammed A. Al-Qarni, Nishant K., Vishwanath Gurumurthy, Saurabh Chaturvedi
Language: English
Subfield: Orthodontics
Field: Dentistry
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,190
Award: G606277293
OpenAlex ID: W4415383269
