Patient attendance in a recall program after prosthodontic rehabilitation: a 5-year follow-up

Int J Prosthodont. 2012 Sep-Oct;25(5):491-6.

Abstract

Purpose: This study evaluated the recall attendance and maintenance for a patient population after prosthodontic treatment in undergraduate student courses.

Materials and methods: Four hundred ninety-three patients who received fixed restorations (FRs; crowns or fixed partial dentures) or removable partial dentures (RPDs; conical crown-retained or precision attachment-retained dental prostheses) were included in a recall program. The number of patients attending regularly scheduled follow-up visits every 6 months was recorded. On the basis of the complexity of the performed treatment, all follow-up interventions were assigned to the categories minimal, moderate, or extensive.

Results: After 60 months, a cumulative follow-up attendance rate between 63% (RPD) and 74% (FR) was evident and not gender related. Altogether, 399 patients (193 FR, 206 RPD) regularly attended the follow-up visits. Between 61.9% (RPD) and 93.8% (FR) of these patients did not need any extensive treatment; however, only 19.2% (RPD) to 85.6% (FR) did not need any moderate or extensive treatment between follow-up visits.

Conclusions: Patients treated with FRs showed a higher recall attendance than patients treated with RPDs. Further, patients with RPDs needed more extensive and moderate treatments than patients with FRs. This difference should be taken into consideration during prosthetic planning and patient consultation.

Publication types

  • Comparative Study

MeSH terms

  • Aged
  • Crowns*
  • Databases, Factual
  • Denture Design
  • Denture Retention / instrumentation
  • Denture, Partial, Fixed*
  • Denture, Partial, Removable*
  • Female
  • Follow-Up Studies
  • Humans
  • Kaplan-Meier Estimate
  • Lost to Follow-Up*
  • Male
  • Middle Aged
  • Office Visits
  • Patient Compliance / statistics & numerical data
  • Patient Dropouts / statistics & numerical data*
  • Proportional Hazards Models
  • Statistics, Nonparametric