PERSONALISED RETENTION PLANS: TAILORING RETAINERS THROUGH ADVANCED DIAGNOSTIC METHODS
Orthodontic relapse is a prevalent issue, and it is frequently caused by uniform retention prescriptions that disregard individual risk factors. Despite the advancement of computerized diagnostics, individualization of retainer form and wearing duration is not widely used. This research evaluates a new diagnostic-directed strategy for tailoring retention regimens based on patient-specific anatomic and biomechanical risk factors. To compare the efficacy of individually created retention plans based on sophisticated diagnostics to typical retainer plans in maintaining post-treatment orthodontic stability. 80 patients aged 14-30 years who had completed fixed appliance treatment were randomly assigned to either the tailored or standard retention groups. To stratify the risk of recurrence, the customized group had digital intraoral scanning, Cone-Beam Computed Tomography imaging (CBCT), and 3D cephalometric analysis. Retention plans (type retainer and wear schedule) were also tailored. The control group received a conventional Hawley or Vacuum Formed Retainer (VFR) with the same wear orders. Little's Irregularity Index (LII), cephalometric changes, compliance, and satisfaction were all measured at 6 and 12 months. The personalized group had significantly reduced LII at both time intervals (T1: 1.12 +/- 0.38 mm; T2: 1.36 +/- 0.42 mm) compared to the control group (T1: 1.84 +/- 0.61 mm; T2: 2.24 +/- 0.73 mm; p < 0.001). There were also higher compliance and satisfaction ratings. The risk of relapse model demonstrated strong predictive validity (AUC = 0.87). Using diagnostics to customize orthodontic retention improves post-treatment stability, compliance, and recurrence. This procedure is clinically feasible and should be regarded as a future standard for orthodontic retention treatments.
Authors
- Dr Abhishek Sinha
Institutions
- Magadh University (IN)
- Mathrusri Ramabai Ambedkar Dental College & Hospital (IN)
Publication Details
- Published
- 2024-12-12
- DOI
- https://doi.org/10.53555/2cgz0974
- Primary Topic
- Software Engineering Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00