Short-term and long-term success and survival rates of implants supporting single-unit and multiunit fixed prostheses: A systematic review and meta-analysis

Comparative Evaluation of Tear Strength and Tensile Strength of Different Types of Gingival Mask Materials: An In Vitro Study

INTRODUCTION

The implant-supported prosthetic treatment strategy is commonly chosen in modern dentistry to address tooth loss caused by a variety of conditions or dental defects. To achieve healthy and natural-looking results in implant dentistry, it is essential to replicate the peri-implant soft tissue. The gingival tissue that surrounds implants is quite accurately replicated by gingival masks. They facilitate more accurate prosthesis restoration design, enhance periodontal health, and promote oral cleanliness. Furthermore, gingival masks allow for the accurate observation of superstructure seating on implant analogs, which is essential for creating superstructures that fit perfectly.

AIM AND OBJECTIVE

 To evaluate the change in tear strength and tensile strength of three different gingival mask materials (esthetic mask auto mix, Gi-Mask and Gingifast Rigid) available in the market at various time intervals.

MATERIALS AND METHODS

Total of 540 specimens were fabricated with 180 samples of each group. Changes in tensile strength and tear strength of three different gingival mask materials (esthetic mask auto mix, Gi-Mask and Gingifast Rigid) at intervals of one day, three days, and seven days were measured by a universal testing machine. Statistical analysis was done using one-way ANOVA and Tukey Post Hoc test. We also performed correlation and regression analyses on tear and tensile strength.

RESULTS

The null hypothesis, which is supported by these data, claims that there is no discernible variation in the tear strength and tensile strength of three distinct materials across various time intervals. Thus, the null hypothesis was rejected, and it was concluded that there was a significant change in the tear strength and tensile strength of these gingival mask materials at different time intervals. Esthetic mask auto mix has a high tear strength compared to Gi-Mask and gingifast rigid. Gi-Mask has the least tear strength among all three. Tensile strength decreases as time increases, but the Esthetic mask auto mix has high strength compared to Gi-Mask and gingifast rigid.

CONCLUSION

Selecting the right material for gingival masks is essential, taking into account the clinical scenario and the articulation time. Time influences gingival mask materials' tear strength and tensile strength, which impacts their performance and durability. Esthetic mask auto mix has a high tear and tensile strength compared to Gi-Mask and gingifast rigid.

Deep learning-designed implant-supported posterior crowns: Assessing time efficiency, tooth morphology, emergence profile, occlusion, and proximal contacts

OBJECTIVES

To compare implant supported crowns (ISCs) designed using deep learning (DL) software with those designed by a technician using conventional computer-aided design software.

METHODS

Twenty resin-based partially edentulous casts (maxillary and mandibular) used for fabricating ISCs were evaluated retrospectively. ISCs were designed using a DL-based method with no modification of the as-generated outcome (DB), a DL-based method with further optimization by a dental technician (DM), and a conventional computer-aided design method by a technician (NC). Time efficiency, crown contour, occlusal table area, cusp angle, cusp height, emergence profile angle, occlusal contacts, and proximal contacts were compared among groups. Depending on the distribution of measured data, various statistical methods were used for comparative analyses with a significance level of 0.05.

RESULTS

ISCs in the DB group showed a significantly higher efficiency than those in the DM and NC groups (P ≤ 0.001). ISCs in the DM group exhibited significantly smaller volume deviations than those in the DB group when superimposed on ISCs in the NC group (DB-NC vs. DM-NC pairs, P ≤ 0.008). Except for the number and intensity of occlusal contacts (P ≤ 0.004), ISCs in the DB and DM groups had occlusal table areas, cusp angles, cusp heights, proximal contact intensities, and emergence profile angles similar to those in the NC group (P ≥ 0.157).

CONCLUSIONS

A DL-based method can be beneficial for designing posterior ISCs in terms of time efficiency, occlusal table area, cusp angle, cusp height, proximal contact, and emergence profile, similar to the conventional human-based method.

CLINICAL SIGNIFICANCE

A deep learning-based design method can achieve clinically acceptable functional properties of posterior ISCs. However, further optimization by a technician could improve specific outcomes, such as the crown contour or emergence profile angle.

Effect of implant type on the stability of cantilever fixed dental prostheses: An in vitro study

OBJECTIVES

To simulate the replacement of a premolar with an implant-supported cantilever fixed dental prosthesis (ICFDP) and how the fracture load is affected by implant type, positioning within the zirconia blank, and aging protocol.

MATERIALS AND METHODS

Seventy-two ICFDPs were designed either within the enamel- or dentin layer of a 4Y-PSZ blank for bone-level and tissue-level titanium-zirconium implants. Fracture load was obtained on the cantilever at baseline (no aging) or after aging in a chewing simulator with the load applied within the implant axis (axial aging) or on the cantilever (12 groups with n = 6). A three-way ANOVA was applied (α = .05).

RESULTS

A three-way ANOVA revealed a significant effect on fracture load values of implant type (p = .006) and aging (p < .001) but not for the position within the zirconia blank (p = .847). Fracture load values significantly increased from baseline bone level (608 ± 118 N) and tissue level (880 ± 293 N) when the implants were aged axially, with higher values for tissue level (1065 ± 182 N) than bone level (797 ± 113 N) (p < .001). However, when the force was applied to the cantilever, fracture load values decreased significantly for tissue-level (493 ± 70 N), while values for bone-level implants remained stable (690 ± 135 N).

CONCLUSIONS

For ICFDPs, the use of bone-level implants is reasonable as catastrophic failures are likely to be restricted to the restoration, whereas with tissue-level implants, the transmucosal portion of the implant is susceptible to deformation, making repair more difficult.