METHODS: Retrospective data from clinical worksheets given to participants during two implant courses held between the periods of 2013 to 2014 were evaluated. A total of 61 implants were considered based on the inclusion criteria. The effects of parameters such as implant diameter, implant length, age, gender, implant location and osteotomy protocol on ISQ values were analyzed.
RESULTS: Mean ISQ value for all implants was 67.21±9.13. Age of patients (P=0.016) and location of implants (P=0.041) had a significant linear relationship with the ISQ values. Within the age limit of the patients in this study, it was found that an increase in one year of patient's age results in 0.20 decrease in ISQ value (95% CI: -0.36, -0.04). However, placing an implant in the posterior maxilla may negatively affect the ISQ with a likely decrease in primary stability by 6.76 ISQ value (95% CI: -13.22, -0.30).
CONCLUSIONS: The results suggest that the mean ISQ achieved by the participants were comparable with the range reported for this particular type of implants. The patient's age and location of implants were elucidated as the determinant factors of primary implant stability.
MATERIALS AND METHODS: An auricular prosthesis, a complete denture, and anterior and posterior crowns were constructed using conventional methods and laser scanned to create computerized 3D meshes. The meshes were optimized independently by four computer-aided design software (Meshmixer, Meshlab, Blender, and SculptGL) to 100%, 90%, 75%, 50%, and 25% levels of original file size. Upon optimization, the following parameters were virtually evaluated and compared; mesh vertices, file size, mesh surface area (SA), mesh volume (V), interpoint discrepancies (geometric similarity based on virtual point overlapping), and spatial similarity (volumetric similarity based on shape overlapping). The influence of software and optimization on surface area and volume of each prosthesis was evaluated independently using multiple linear regression.
RESULTS: There were clear observable differences in vertices, file size, surface area, and volume. The choice of software significantly influenced the overall virtual parameters of auricular prosthesis [SA: F(4,15) = 12.93, R2 = 0.67, p < 0.001. V: F(4,15) = 9.33, R2 = 0.64, p < 0.001] and complete denture [SA: F(4,15) = 10.81, R2 = 0.67, p < 0.001. V: F(4,15) = 3.50, R2 = 0.34, p = 0.030] across optimization levels. Interpoint discrepancies were however limited to <0.1mm and volumetric similarity was >97%.
CONCLUSION: Open-source mesh optimization of smaller dental prostheses in this study produced minimal loss of geometric and volumetric details. SculptGL models were most influenced by the amount of optimization performed.
METHODS: Forty direct impressions of a mandibular reference model fitted with six dental implants and multibase abutments were made using VPES and PE, and implant casts were poured (N = 20). The VPES and PE groups were split into four subgroups of five each, based on splinting type: (a) no splinting; (b) bite registration polyether; (c) bite registration addition silicone; and (d) autopolymerizing acrylic resin. The accuracy of implant-abutment replica positions was calculated on the experimental casts, in terms of interimplant distances in the x, y, and z-axes, using a coordinate measuring machine; values were compared with those measured on the reference model. Data were analyzed using non-parametrical Kruskal-Wallis and Mann-Whitney tests at α = .05.
RESULTS: The differences between the two impression materials, VPES and PE, regardless of splinting type, were not statistically significant (P>.05). Non-splinting and splinting groups were also not significantly different for both PE and VPES (P>.05).
CONCLUSIONS: The accuracy of VPES impression material seemed comparable with PE for multi-implant abutment-level impressions. Splinting had no effect on the accuracy of implant impressions.
MATERIALS AND METHODS: Twenty-one patients with implants were included in this study and implants were assessed by resonance frequency analysis (RFA). Bone levels of the implants were assessed by measuring mesial and distal bone levels from the periapical radiograph, and soft tissue was assessed from probing depth using a periodontal probe. Implants were assessed for stability and probing depth at pre-loading, at 3 months and 6 months post-loading. RFA and probing depth were statistically compared from different time points. Correlation of probing depth and marginal bone loss with implant stability was also determined.
RESULTS: The average change in implant stability quotient (ISQ) measurements from pre-loading to 6 months post-loading was found to be statistically significant (p <0.005). The average probing depth reduced from 1.767 mm at pre-loading to 1.671 mm at post-loading 3 months, and 1.600 mm at post-loading 6 months. At 6 months of function, radiographic examination yielded 0.786 mm mesial bone loss and 0.8 mm distal bone loss. It was found to be statistically significant (p <0.005) but within an acceptable range. No significant correlation was found between implant stability and bone loss; and implant stability and probing depth.
CONCLUSION: The study revealed an increasing trend in implant stability values with the time that indicates successful osseointegration. Increasing mean values for mesial and distal bone loss were also found.
CLINICAL SIGNIFICANCE: The success of dental implants is highly dependent on the quality of bone and implant-bone interface, i.e., osseointegration. The most important factors that influence the survival rate of an implant is initial stability. The present study found the changes in the peri-implant hard and soft tissues and implant stability. This article, while being a prospective study, may show the evidence of successful osseointegration by increasing trend in implant stability (RFA) values with time which can help to the clinician in the long-term management of implants.
MATERIALS AND METHODS: Sixmaster dies were duplicated from the prepared maxillary first premolar tooth using nonprecious metal alloy (Wiron 99). Ten copings of 0.6 mm thickness were fabricated from each type of ceramic, for a total of thirty copings. Two master dies were used for each group, and each of them was used to lute five copings. All groups were cemented with resin luting cement Panavia F according to manufacturer's instructions and received a static load of 5 kg during cementation. After 24 hours of distilled water storage at 37 degrees C, the copings were vertically compressed using a universal testing machine at a crosshead speed of 1 mm/min.
RESULTS: The results of the present study showed the following mean loads at fracture: Turkom-Cera (2184 +/- 164 N), In-Ceram (2042 +/- 200 N), and Procera AllCeram (1954 +/- 211 N). ANOVA and Scheffe's post hoc test showed that the mean load at fracture of Turkom-Cera was significantly different from Procera AllCeram (p < 0.05). Scheffe's post hoc test showed no significant difference between the mean load at fracture of Turkom-Cera and In-Ceram or between the mean load at fracture of In-Ceram and Procera AllCeram.
CONCLUSION: Because Turkom-Cera demonstrated equal to or higher loads at fracture than currently accepted all-ceramic materials, it would seem to be acceptable for fabrication of anterior and posterior ceramic crowns.