Abstract
Selecting an appropriate vital pulp therapy (VPT) for primary teeth with reversible pulpitis can sometimes be confusing for clinicians. Encouragingly, continuous developments in capping materials with bioactive properties help the selection of less-invasive treatments. This non-randomized clinical trial aimed to assess the clinical and radiographic success rates of indirect pulp treatment (IPT), direct pulp capping (DPC), partial pulpotomy (PP) and pulpotomy in primary molars utilizing TheraCal PT over a 12-month period. Different inclusion criteria were assigned for each treatment to assess the eligibility of each treatment type for specific clinical scenarios. Additionally, the association of tooth survival with some variables was assessed. The trial was registered at clinicaltrials.gov (NCT04167943) on 19 November 2019. Primary molars (n = 216) with caries extending into the inner dentin third or quarter were included. Selective caries removal was employed in IPT. Non-selective caries removal was employed in other groups, and treatment was decided according to pulp exposure characteristics, whereby the most conservative treatment was selected for the least clinically detectable pulp inflammation. Cox regression was performed to assess the effects of different variables on tooth survival using p ˂ 0.05 for detecting statistical significance. The 12-month combined clinical and radiographic success rates for IPT, DPC, PP and pulpotomy were 93.87%, 80.4%, 42.6% and 96.15%, respectively. Proximal surface involvement, provoked pain and first primary molars were associated with increased odds of treatment failure. According to the specified inclusion criteria, IPT, DPC and pulpotomy using TheraCal PT demonstrated acceptable results, while PP was associated with poor treatment outcomes. The odds of failure increased with proximal surface involvement, provoked pain and first primary molars. These results provide insights into different scenarios when managing deep carious lesions in primary teeth. The effects of clinical predictors on treatment outcomes may guide clinicians in case selection.
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