Comparison of computer-controlled versus conventional local anesthesia delivery systems: a randomized clinical trial

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Authors: Vinesa Gill, Shahid Islam, Muhammad Ali, Jiand Malik Baloch, Talha Tanveer, Azam Muhammad Aliuddin, Aiman Zehra, Abubakar Sheikh
Cited by: 0
References: 20

Abstract

BACKGROUND: Pain perception during dental procedures is a common cause of patient anxiety. The aim of this study was to compare the pain perception during anesthetic injection and patient preference between a conventional local anesthesia technique and a computer-controlled local anesthesia delivery (CCLAD) system. METHODS: A randomized, crossover clinical trial was conducted with 40 patients who received both conventional and computerized local anesthesia using the SOGA Smart II device. A 2% lidocaine with epinephrine (1.8 ml, 1:100,000) was used for both techniques. In maxilla, infiltration technique was used and in mandible, Inferior Alveolar Nerve Block was administered. The pain during injection was assessed using a Visual Analogue Scale (VAS). Statistical analysis was performed using paired t-tests. RESULTS: The mean VAS score for conventional anesthesia was 4.20 ± 1.16, and for the CCLAD system was 2.23 ± 1.23. The difference was statistically significant (p < 0.001). No gender-based differences in VAS scores were observed. The majority of patients expressed a preference for the computerized system. CONCLUSION: The SOGA Smart II CCLAD system significantly reduces pain perception compared to conventional techniques. Most patients favored the electronic delivery method, suggesting its potential role as a patient-centered approach to reducing injection-related discomfort in selected clinical settings. TRIAL REGISTRATION: Trial was registered retrospectively with the registration number: TCTR20250517004, dated 17th May, 2025.

Fields of Study & Subjects

Dental Anxiety and Anesthesia Techniques Anesthesia and Pain Management Dental Radiography and Imaging

Publication details

Journal / source
BMC Oral Health
Volume
26
Issue
1
Publication date
17 February 2026
Language
EN