{"id":10898,"date":"2025-07-30T16:01:37","date_gmt":"2025-07-30T16:01:37","guid":{"rendered":"https:\/\/nurs.essaybishops.com\/types-of-grafts-in-dentistry\/"},"modified":"2025-07-30T16:01:37","modified_gmt":"2025-07-30T16:01:37","slug":"types-of-grafts-in-dentistry","status":"publish","type":"post","link":"https:\/\/www.colapapers.com\/nursing\/types-of-grafts-in-dentistry\/","title":{"rendered":"Types of Grafts in Dentistry"},"content":{"rendered":"
\n

TYPES OF GRAFTS:<\/strong><\/p>\n

Osseointegrated <\/del>implants can be combined with the following <\/ins><\/p>\n

types of graft: inlay, saddle, veneer, onlay (partial or full arch), and maxillary sinus grafts. (Triplett & Schow, 1996)<\/p>\n

The mucoperiosteal flap should be designed to adequately expose the underlying residual ridge, maintain a broad base for vascular support, and allow tension-free primary closure. A midcrestal incision is usually preferred because it maximizes the vascularity to the margins of the mucoperiosteal flaps and minimizes ischemia created by the vasculature traversing dense,<\/del> keratinized tissue at the crest of the ridge. Labial vertical releasing incisions are made as needed to improve access. All grafts must be well adapted to the<\/ins> recipient site with no or minimal space betveen<\/del>between<\/ins> graft and residual bone. Hence, usually graft shaping and adaptation is unavoidable. The g<\/ins>G<\/del>raft is<\/ins> positioned to its best adaptation to the underlying alveolus. A good fixation with titanium screws must be achieved to prevent the<\/del> graft movement. Any movement of the graft increases<\/ins> the chance of soft tissues ingrowth between the graft and the<\/ins> recipient site, and<\/ins> thus the<\/del> failure of the graft is likely. All voids or defects should be filled with particulate cancellous bone and marrow to provide good contour and eliminate dead space. A primary, tension-free closure must be achieved to prevent wound breakdown and graft exposure. A barrier membrane and filler graft may be used, if desired.<\/p>\n

Inlay Grafts<\/strong><\/p>\n

Small osseous defects at the alveolar crest can be inlaid with an autologous graft to restore the contour and volume of bone necessary to place an<\/del> the<\/ins> <\/ins>implant and allow for a proper emergence profile.<\/p>\n

The defect is usually exposed through a crestal incision that is<\/ins> extended around the necks of one or two adjacent teeth on either side of the defect. A vertical releasing incision is made if necessary. A barrier membrane may be used to protect these areas during healing.<\/p>\n

Saddle Graft<\/strong><\/p>\n

<\/a>Indicated where both horizontal and vertical ridge augmentation[S1]<\/a>, this type of graft is also of considerable value. A<\/ins>a<\/del>utogenous bone stabilized with rigid fixation to restore anatomic height and width is an excellent solution to this problem. A saddle of bone is obtained from the anterior-inferior border of the mandible (ipsilateral site) and secured in position from the buccal or crestal aspect with 1.5\u2013<\/del>mm titanium screws with a minimum of 2 screws to achieve stable graft fixation.<\/p>\n

Veneer Graft<\/p>\n

A veneer graft is preferred where there is only a<\/ins> horizontal bone defect o<\/ins>f<\/ins> less than 4 <\/del>mm. T<\/del><\/p>\n

Onlay Graft<\/p>\n

The design of onlay grafts can be segmental or arch in shape.<\/p>\n

Both the height and width of an atrophic ridge can be achieved with onlay grafts. <\/a>Following<\/del> I<\/ins>i<\/del>ndications include the following<\/ins>[S2]<\/a>: inadequate residual alveolar ridge height and width to support a functional prosthesis, contour defects that compromise implant support, function, or a<\/ins>esthetics, and segmental alveolar bone loss.<\/p>\n

\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014-<\/p>\n

Procedures aimed at increasing the volume of attached mucosa (free soft tissue grafts, pedicle soft <\/ins><\/p>\n

tissue grafts, and surgical extension of the vestibulum) have been recommended in areas of movable <\/ins><\/p>\n

mucosa. <\/ins><\/a>75,77,102\u2013111 [S3]<\/a>(Esposito, Hirsch, Lekholm, & Thomsen, 1999)<\/p>\n

There was<\/del>It has also been<\/ins> also<\/del> stated that cancellous grafts are<\/ins> more successful because of cortical plate (\u201c<\/del>Buchman 1999 Cancelous Bone stucture.pdf,\u201d<\/del> n.d.)<\/p>\n

Results:<\/p>\n

    \n
  1. A p<\/ins>P<\/del>ositive correlation outcome was found between age and missing teeth found in both groups A and B in the<\/ins> applied multiple regression analysis (SPSS)<\/li>\n<\/ol>\n

    Group A analysis for correlation between the patients age and number of teeth missing outcome:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
    \n

    Correlations<\/strong><\/p>\n<\/td>\n<\/tr>\n

    \u00a0<\/td>\n\n

    Patients age<\/p>\n<\/td>\n

    		\n

    Number of Teeth<\/p>\n<\/td>\n<\/tr>\n

    \n

    Patients age<\/p>\n<\/td>\n

    		\n

    Pearson Correlation<\/p>\n<\/td>\n

    		\n

    1<\/p>\n<\/td>\n

    		\n

    .326**<\/sup><\/p>\n<\/td>\n<\/tr>\n

    \n

    Sig. (2-tailed)<\/p>\n<\/td>\n

    		\u00a0<\/td>\n\n

    .000<\/p>\n<\/td>\n<\/tr>\n

    \n

    N<\/p>\n<\/td>\n

    		\n

    120<\/p>\n<\/td>\n

    		\n

    111<\/p>\n<\/td>\n<\/tr>\n

    \n

    Number of Teeth<\/p>\n<\/td>\n

    		\n

    Pearson Correlation<\/p>\n<\/td>\n

    		\n

    .326**<\/sup><\/p>\n<\/td>\n

    		\n

    1<\/p>\n<\/td>\n<\/tr>\n

    \n

    Sig. (2-tailed)<\/p>\n<\/td>\n

    		\n

    .000<\/p>\n<\/td>\n

    		\u00a0<\/td>\n<\/tr>\n
    \n

    N<\/p>\n<\/td>\n

    		\n

    111<\/p>\n<\/td>\n

    		\n

    111<\/p>\n<\/td>\n<\/tr>\n

    \n

    **. Correlation is significant at the 0.01 level (2-tailed).<\/p>\n<\/td>\n<\/tr>\n

    \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Group B outcome:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
    \n

    Correlations<\/strong><\/p>\n<\/td>\n<\/tr>\n

    \u00a0<\/td>\n\n

    Patients age<\/p>\n<\/td>\n

    		\n

    Number of Teeth<\/p>\n<\/td>\n<\/tr>\n

    \n

    Patients age<\/p>\n<\/td>\n

    		\n

    Pearson Correlation<\/p>\n<\/td>\n

    		\n

    1<\/p>\n<\/td>\n

    		\n

    .465**<\/sup><\/p>\n<\/td>\n<\/tr>\n

    \n

    Sig. (2-tailed)<\/p>\n<\/td>\n

    		\u00a0<\/td>\n\n

    .004<\/p>\n<\/td>\n<\/tr>\n

    \n

    N<\/p>\n<\/td>\n

    		\n

    41<\/p>\n<\/td>\n

    		\n

    37<\/p>\n<\/td>\n<\/tr>\n

    \n

    Number of Teeth<\/p>\n<\/td>\n

    		\n

    Pearson Correlation<\/p>\n<\/td>\n

    		\n

    .465**<\/sup><\/p>\n<\/td>\n

    		\n

    1<\/p>\n<\/td>\n<\/tr>\n

    \n

    Sig. (2-tailed)<\/p>\n<\/td>\n

    		\n

    .004<\/p>\n<\/td>\n

    		\u00a0<\/td>\n<\/tr>\n
    \n

    N<\/p>\n<\/td>\n

    		\n

    37<\/p>\n<\/td>\n

    		\n

    37<\/p>\n<\/td>\n<\/tr>\n

    \n

    **. Correlation is significant at the 0.01 level (2-tailed).<\/p>\n<\/td>\n<\/tr>\n

    \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
      \n
    1. A p<\/ins>P<\/del>ositive correlation was<\/ins> found between age and bone volume harvested in Group A. However, the correlation in Group B was non\u2013<\/ins> <\/del>significant.<\/li>\n<\/ol>\n

      Group A multiple regression analysis output:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
      \n

      Correlations<\/strong><\/p>\n<\/td>\n<\/tr>\n

      \u00a0<\/td>\n\n

      Patients age<\/p>\n<\/td>\n

      		\n

      Bone graft volume<\/p>\n<\/td>\n<\/tr>\n

      \n

      Patients age<\/p>\n<\/td>\n

      		\n

      Pearson Correlation<\/p>\n<\/td>\n

      		\n

      1<\/p>\n<\/td>\n

      		\n

      .244**<\/sup><\/p>\n<\/td>\n<\/tr>\n

      \n

      Sig. (2-tailed)<\/p>\n<\/td>\n

      		\u00a0<\/td>\n\n

      .007<\/p>\n<\/td>\n<\/tr>\n

      \n

      N<\/p>\n<\/td>\n

      		\n

      120<\/p>\n<\/td>\n

      		\n

      120<\/p>\n<\/td>\n<\/tr>\n

      \n

      Bone graft volume<\/p>\n<\/td>\n

      		\n

      Pearson Correlation<\/p>\n<\/td>\n

      		\n

      .244**<\/sup><\/p>\n<\/td>\n

      		\n

      1<\/p>\n<\/td>\n<\/tr>\n

      \n

      Sig. (2-tailed)<\/p>\n<\/td>\n

      		\n

      .007<\/p>\n<\/td>\n

      		\u00a0<\/td>\n<\/tr>\n
      \n

      N<\/p>\n<\/td>\n

      		\n

      120<\/p>\n<\/td>\n

      		\n

      120<\/p>\n<\/td>\n<\/tr>\n

      \n

      **. Correlation is significant at the 0.01 level (2-tailed).<\/p>\n<\/td>\n<\/tr>\n

      \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      Group B SPSS multiple regression analysis output:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n
      \n

      Correlations<\/strong><\/p>\n<\/td>\n<\/tr>\n

      \u00a0<\/td>\n\n

      Patients age<\/p>\n<\/td>\n

      		\n

      Bone graft volume<\/p>\n<\/td>\n<\/tr>\n

      \n

      Patients age<\/p>\n<\/td>\n

      		\n

      Pearson Correlation<\/p>\n<\/td>\n

      		\n

      1<\/p>\n<\/td>\n

      		\n

      .203<\/p>\n<\/td>\n<\/tr>\n

      \n

      Sig. (2-tailed)<\/p>\n<\/td>\n

      		\u00a0<\/td>\n\n

      .203<\/p>\n<\/td>\n<\/tr>\n

      \n

      N<\/p>\n<\/td>\n

      		\n

      41<\/p>\n<\/td>\n

      		\n

      41<\/p>\n<\/td>\n<\/tr>\n

      \n

      Bone graft volume<\/p>\n<\/td>\n

      		\n

      Pearson Correlation<\/p>\n<\/td>\n

      		\n

      .203<\/p>\n<\/td>\n

      		\n

      1<\/p>\n<\/td>\n<\/tr>\n

      \n

      Sig. (2-tailed)<\/p>\n<\/td>\n

      		\n

      .203<\/p>\n<\/td>\n

      		\u00a0<\/td>\n<\/tr>\n
      \n

      N<\/p>\n<\/td>\n

      		\n

      41<\/p>\n<\/td>\n

      		\n

      41<\/p>\n<\/td>\n<\/tr>\n

      \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
        \n
      1. The distribution for harvested overall bone volumes was found to be normal in both groups A and B and a significant correlation was found between clinitian<\/del>clinician<\/ins> A and clinitian<\/del>clinician<\/ins> B and their harvested bone volumes.<\/li>\n<\/ol>\n

        Distribution analysis output. Histogram:<\/p>\n

        \"\"<\/p>\n

        Multiple regression analysis output for Clinitian<\/del>Clinician<\/ins> A<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
        \n

        ANOVA<\/strong>a<\/sup><\/strong><\/p>\n<\/td>\n<\/tr>\n

        \n

        Model<\/p>\n<\/td>\n

        		\n

        Sum of Squares<\/p>\n<\/td>\n

        		\n

        df<\/p>\n<\/td>\n

        		\n

        Mean Square<\/p>\n<\/td>\n

        		\n

        F<\/p>\n<\/td>\n

        		\n

        Sig.<\/p>\n<\/td>\n<\/tr>\n

        \n

        1<\/p>\n<\/td>\n

        		\n

        Regression<\/p>\n<\/td>\n

        		\n

        9317266.326<\/p>\n<\/td>\n

        		\n

        1<\/p>\n<\/td>\n

        		\n

        9317266.326<\/p>\n<\/td>\n

        		\n

        31.994<\/p>\n<\/td>\n

        		\n

        .000b<\/sup><\/p>\n<\/td>\n<\/tr>\n

        \n

        Residual<\/p>\n<\/td>\n

        		\n

        42518278.360<\/p>\n<\/td>\n

        		\n

        146<\/p>\n<\/td>\n

        		\n

        291221.085<\/p>\n<\/td>\n

        		\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
        \n

        Total<\/p>\n<\/td>\n

        		\n

        51835544.685<\/p>\n<\/td>\n

        		\n

        147<\/p>\n<\/td>\n

        		\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
        \n

        2<\/p>\n<\/td>\n

        		\n

        Regression<\/p>\n<\/td>\n

        		\n

        16022829.759<\/p>\n<\/td>\n

        		\n

        2<\/p>\n<\/td>\n

        		\n

        8011414.879<\/p>\n<\/td>\n

        		\n

        32.437<\/p>\n<\/td>\n

        		\n

        .000c<\/sup><\/p>\n<\/td>\n<\/tr>\n

        \n

        Residual<\/p>\n<\/td>\n

        		\n

        35812714.927<\/p>\n<\/td>\n

        		\n

        145<\/p>\n<\/td>\n

        		\n

        246984.241<\/p>\n<\/td>\n

        		\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
        \n

        Total<\/p>\n<\/td>\n

        		\n

        51835544.685<\/p>\n<\/td>\n

        		\n

        147<\/p>\n<\/td>\n

        		\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
        \n

        a. Dependent Variable: Bone graft volume<\/p>\n<\/td>\n<\/tr>\n

        \n

        b. Predictors: (Constant), Number of Teeth<\/p>\n<\/td>\n<\/tr>\n

        \n

        c. Predictors: (Constant), Number of Teeth, Procedure Performer<\/p>\n<\/td>\n<\/tr>\n

        \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
          \n
        1. Association between a<\/ins> patient\u2019s gender and performed clinicians A and<\/ins>s<\/del> B found to be not statistically significant applying SPSS multiple regression analysis.<\/li>\n<\/ol>\n

          The SPSS output for multiple regression analysis:<\/p>\n\n\n\n\n\n\n\n
          \n

          Group Statistics<\/strong><\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\n

          Procedure Performer<\/p>\n<\/td>\n

          		\n

          N<\/p>\n<\/td>\n

          		\n

          Mean<\/p>\n<\/td>\n

          		\n

          Std. Deviation<\/p>\n<\/td>\n

          		\n

          Std. Error Mean<\/p>\n<\/td>\n<\/tr>\n

          \n

          Patients age<\/p>\n<\/td>\n

          		\n

          AP<\/p>\n<\/td>\n

          		\n

          41<\/p>\n<\/td>\n

          		\n

          38.85<\/p>\n<\/td>\n

          		\n

          11.599<\/p>\n<\/td>\n

          		\n

          1.811<\/p>\n<\/td>\n<\/tr>\n

          \n

          SG<\/p>\n<\/td>\n

          		\n

          120<\/p>\n<\/td>\n

          		\n

          39.05<\/p>\n<\/td>\n

          		\n

          11.876<\/p>\n<\/td>\n

          		\n

          1.084<\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n
          \n

          Case Processing Summary<\/strong><\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\n

          Cases<\/p>\n<\/td>\n<\/tr>\n

          \n

          Valid<\/p>\n<\/td>\n

          		\n

          Missing<\/p>\n<\/td>\n

          		\n

          Total<\/p>\n<\/td>\n<\/tr>\n

          \n

          N<\/p>\n<\/td>\n

          		\n

          Percent<\/p>\n<\/td>\n

          		\n

          N<\/p>\n<\/td>\n

          		\n

          Percent<\/p>\n<\/td>\n

          		\n

          N<\/p>\n<\/td>\n

          		\n

          Percent<\/p>\n<\/td>\n<\/tr>\n

          \n

          Procedure Performer * Patients Gender<\/p>\n<\/td>\n

          		\n

          161<\/p>\n<\/td>\n

          		\n

          100.0%<\/p>\n<\/td>\n

          		\n

          0<\/p>\n<\/td>\n

          		\n

          0.0%<\/p>\n<\/td>\n

          		\n

          161<\/p>\n<\/td>\n

          		\n

          100.0%<\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n
          \n

          Procedure Performer * Patients Gender Cross<\/strong> <\/ins>tabulation<\/strong><\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\n

          Patients Gender<\/p>\n<\/td>\n

          		\n

          Total<\/p>\n<\/td>\n<\/tr>\n

          \n

          Male<\/p>\n<\/td>\n

          		\n

          Female<\/p>\n<\/td>\n<\/tr>\n

          \n

          Procedure Performer<\/p>\n<\/td>\n

          		\n

          AP<\/p>\n<\/td>\n

          		\n

          Count<\/p>\n<\/td>\n

          		\n

          8<\/p>\n<\/td>\n

          		\n

          33<\/p>\n<\/td>\n

          		\n

          41<\/p>\n<\/td>\n<\/tr>\n

          \n

          Expected Count<\/p>\n<\/td>\n

          		\n

          10.7<\/p>\n<\/td>\n

          		\n

          30.3<\/p>\n<\/td>\n

          		\n

          41.0<\/p>\n<\/td>\n<\/tr>\n

          \n

          SG<\/p>\n<\/td>\n

          		\n

          Count<\/p>\n<\/td>\n

          		\n

          34<\/p>\n<\/td>\n

          		\n

          86<\/p>\n<\/td>\n

          		\n

          120<\/p>\n<\/td>\n<\/tr>\n

          \n

          Expected Count<\/p>\n<\/td>\n

          		\n

          31.3<\/p>\n<\/td>\n

          		\n

          88.7<\/p>\n<\/td>\n

          		\n

          120.0<\/p>\n<\/td>\n<\/tr>\n

          \n

          Total<\/p>\n<\/td>\n

          		\n

          Count<\/p>\n<\/td>\n

          		\n

          42<\/p>\n<\/td>\n

          		\n

          119<\/p>\n<\/td>\n

          		\n

          161<\/p>\n<\/td>\n<\/tr>\n

          \n

          Expected Count<\/p>\n<\/td>\n

          		\n

          42.0<\/p>\n<\/td>\n

          		\n

          119.0<\/p>\n<\/td>\n

          		\n

          161.0<\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
          \n

          Chi-Square Tests<\/strong><\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\n

          Value<\/p>\n<\/td>\n

          		\n

          df<\/p>\n<\/td>\n

          		\n

          Asymp. Sig. (2-sided)<\/p>\n<\/td>\n

          		\n

          Exact Sig. (2-sided)<\/p>\n<\/td>\n

          		\n

          Exact Sig. (1-sided)<\/p>\n<\/td>\n<\/tr>\n

          \n

          Pearson Chi-Square<\/p>\n<\/td>\n

          		\n

          1.233a<\/sup><\/p>\n<\/td>\n

          		\n

          1<\/p>\n<\/td>\n

          		\n

          .267<\/p>\n<\/td>\n

          		\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
          \n

          Continuity Correctionb<\/sup><\/p>\n<\/td>\n

          		\n

          .818<\/p>\n<\/td>\n

          		\n

          1<\/p>\n<\/td>\n

          		\n

          .366<\/p>\n<\/td>\n

          		\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
          \n

          Likelihood Ratio<\/p>\n<\/td>\n

          		\n

          1.286<\/p>\n<\/td>\n

          		\n

          1<\/p>\n<\/td>\n

          		\n

          .257<\/p>\n<\/td>\n

          		\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
          \n

          Fisher\u2019s Exact Test<\/p>\n<\/td>\n

          		\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\n

          .309<\/p>\n<\/td>\n

          		\n

          .184<\/p>\n<\/td>\n<\/tr>\n

          \n

          Linear-by-Linear Association<\/p>\n<\/td>\n

          		\n

          1.226<\/p>\n<\/td>\n

          		\n

          1<\/p>\n<\/td>\n

          		\n

          .268<\/p>\n<\/td>\n

          		\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
          \n

          N of Valid Cases<\/p>\n<\/td>\n

          		\n

          161<\/p>\n<\/td>\n

          		\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
          \n

          a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 10.70.<\/p>\n<\/td>\n<\/tr>\n

          \n

          b. Computed only for a 2\u00d72 table<\/p>\n<\/td>\n<\/tr>\n

          \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
            \n
          1. The<\/ins> A<\/del>a<\/ins>ssociation between a<\/ins> patient\u2019s age and clinitians<\/del>clinicians<\/ins> A and B was also not statistically significant <\/ins>(\u201cRes<\/ins>z<\/del>ults,\u201d n.d.). P value was more than 0.05. So the hypothesis that there is no difference between patients<\/del>patient\u2019s<\/ins> age and performed clinitian<\/del>clinician<\/ins> A and B harvested bone volumes <\/ins> \u2013<\/del>can <\/del>not be<\/ins> rejected<\/ins> the<\/del> hypothesis<\/del>.<\/li>\n<\/ol>\n
              \n
            1. Nominal variables (number of teeth) were not equally distributed. So, a nonparametric Kruskal-Wallis Test was applied to test the hypothesis<\/ins>hypostasis<\/del> that there was<\/ins>is<\/del> no difference between the number of teeth missing and harvested bone volumes in group A and B. The hypothesis was<\/ins>h<\/del>ypostasis<\/del> rejected in Group A because the P value was less than 0.05. However, there was no difference in a<\/del> G<\/ins>g<\/del>roup B (p value more than 0.05)<\/li>\n<\/ol>\n

              Number of teeth and harvested bone volumes distribution for Group A<\/p>\n

              \"\"<\/p>\n

              Kruskal-Wallis hypothesis testing output:<\/p>\n\n\n\n\n\n\n\n\n\n\n
              \n

              Ranks<\/strong><\/p>\n<\/td>\n<\/tr>\n

              \u00a0<\/td>\n\n

              Number of Teeth<\/p>\n<\/td>\n

              		\n

              N<\/p>\n<\/td>\n

              		\n

              Mean Rank<\/p>\n<\/td>\n<\/tr>\n

              \n

              Bone graft volume<\/p>\n<\/td>\n

              		\n

              One tooth<\/p>\n<\/td>\n

              		\n

              22<\/p>\n<\/td>\n

              		\n

              40.95<\/p>\n<\/td>\n<\/tr>\n

              \n

              Two teeth<\/p>\n<\/td>\n

              		\n

              38<\/p>\n<\/td>\n

              		\n

              43.41<\/p>\n<\/td>\n<\/tr>\n

              \n

              Three teeth<\/p>\n<\/td>\n

              		\n

              30<\/p>\n<\/td>\n

              		\n

              68.45<\/p>\n<\/td>\n<\/tr>\n

              \n

              Four and more teeth<\/p>\n<\/td>\n

              		\n

              21<\/p>\n<\/td>\n

              		\n

              76.76<\/p>\n<\/td>\n<\/tr>\n

              \n

              Total<\/p>\n<\/td>\n

              		\n

              111<\/p>\n<\/td>\n

              		\u00a0<\/td>\n<\/tr>\n
              \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n
              \n

              Test Statistics<\/strong>a,b<\/sup><\/strong><\/p>\n<\/td>\n<\/tr>\n

              \u00a0<\/td>\n\n

              Bone graft volume<\/p>\n<\/td>\n<\/tr>\n

              \n

              Chi-Square<\/p>\n<\/td>\n

              		\n

              23.851<\/p>\n<\/td>\n<\/tr>\n

              \n

              df<\/p>\n<\/td>\n

              		\n

              3<\/p>\n<\/td>\n<\/tr>\n

              \n

              Asymp. Sig.<\/p>\n<\/td>\n

              		\n

              .000<\/p>\n<\/td>\n<\/tr>\n

              \n

              a. Kruskal Wallis Test<\/p>\n<\/td>\n<\/tr>\n

              \n

              b. Grouping Variable: Number of Teeth<\/p>\n<\/td>\n<\/tr>\n

              \u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              SPSS output for Kruskal-Wallis Test Group B:<\/p>\n\n\n\n\n\n\n\n\n\n\n
              \n

              Ranks<\/strong><\/p>\n<\/td>\n<\/tr>\n

              \u00a0<\/td>\n\n

              Number of Teeth<\/p>\n<\/td>\n

              		\n

              N<\/p>\n<\/td>\n

              		\n

              Mean Rank<\/p>\n<\/td>\n<\/tr>\n

              \n

              Bone graft volume<\/p>\n<\/td>\n

              		\n

              One tooth<\/p>\n<\/td>\n

              		\n

              11<\/p>\n<\/td>\n

              		\n

              14.59<\/p>\n<\/td>\n<\/tr>\n

              \n

              Two teeth<\/p>\n<\/td>\n

              		\n

              11<\/p>\n<\/td>\n

              		\n

              19.45<\/p>\n<\/td>\n<\/tr>\n

              \n

              Three teeth<\/p>\n<\/td>\n

              		\n

              11<\/p>\n<\/td>\n

              		\n

              20.27<\/p>\n<\/td>\n<\/tr>\n

              \n

              Four and more teeth<\/p>\n<\/td>\n

              		\n

              4<\/p>\n<\/td>\n

              		\n

              26.38<\/p>\n<\/td>\n<\/tr>\n

              \n

              Total<\/p>\n<\/td>\n

              		\n

              37<\/p>\n<\/td>\n

              		\u00a0<\/td>\n<\/tr>\n
              \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n
              \n

              Test Statistics<\/strong>a,b<\/sup><\/strong><\/p>\n<\/td>\n<\/tr>\n

              \u00a0<\/td>\n\n

              Bone graft volume<\/p>\n<\/td>\n<\/tr>\n

              \n

              Chi-Square<\/p>\n<\/td>\n

              		\n

              3.855<\/p>\n<\/td>\n<\/tr>\n

              \n

              df<\/p>\n<\/td>\n

              		\n

              3<\/p>\n<\/td>\n<\/tr>\n

              \n

              Asymp. Sig.<\/p>\n<\/td>\n

              		\n

              .278<\/p>\n<\/td>\n<\/tr>\n

              \n

              a. Kruskal Wallis Test<\/p>\n<\/td>\n<\/tr>\n

              \n

              b. Grouping Variable: Number of Teeth<\/p>\n<\/td>\n<\/tr>\n

              \u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
                \n
              1. A bone volume\u2019s<\/del> distribution was tested by drawing a histogram to <\/a>determent<\/del> determine a<\/ins> parametric or non <\/del>parametric test was needed<\/ins> to apply<\/del>in order<\/ins> to test the hypothesis[S4]<\/a>. The data was not equally distributed in both groups A and B. Hence, the non <\/del>parametric Mann-Whitney test was applied to test the null hypothesis of<\/ins> if<\/del> <\/del>whether<\/ins> there is<\/del> was<\/ins> no<\/del> any<\/ins> difference in harvested bone volumes and the<\/ins> performance of<\/ins> the<\/ins>ed<\/del> clinicians. The P value was less than 0.05, so the<\/ins> null hypothesis was rejected and there is<\/del> was<\/ins> a significant difference between c<\/ins>c<\/del>linician A\u2019s<\/ins> and clinician\u2019s<\/ins> B performances.<\/li>\n<\/ol>\n

                Clinitian<\/del>Clinician<\/ins> A and B harvested bone volumes distributions:<\/p>\n\n\n\n
                \n

                \"\"<\/p>\n<\/td>\n

                		\n

                \"\"<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n
                \n

                Descriptive Statistics<\/strong><\/p>\n<\/td>\n<\/tr>\n

                \u00a0<\/td>\n\n

                N<\/p>\n<\/td>\n

                		\n

                Mean<\/p>\n<\/td>\n

                		\n

                Std. Deviation<\/p>\n<\/td>\n

                		\n

                Minimum<\/p>\n<\/td>\n

                		\n

                Maximum<\/p>\n<\/td>\n<\/tr>\n

                \n

                Bone graft volume<\/p>\n<\/td>\n

                		\n

                161<\/p>\n<\/td>\n

                		\n

                1121.5017<\/p>\n<\/td>\n

                		\n

                622.04168<\/p>\n<\/td>\n

                		\n

                80.00<\/p>\n<\/td>\n

                		\n

                3380.00<\/p>\n<\/td>\n<\/tr>\n

                \n

                Procedure Performer<\/p>\n<\/td>\n

                		\n

                161<\/p>\n<\/td>\n

                		\n

                1.75<\/p>\n<\/td>\n

                		\n

                .437<\/p>\n<\/td>\n

                		\n

                1<\/p>\n<\/td>\n

                		\n

                2<\/p>\n<\/td>\n<\/tr>\n

                \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                SPSS output Mann-Whitney Test<\/p>\n\n\n\n\n\n\n\n\n
                \n

                Ranks<\/strong><\/p>\n<\/td>\n<\/tr>\n

                \u00a0<\/td>\n\n

                Procedure Performer<\/p>\n<\/td>\n

                		\n

                N<\/p>\n<\/td>\n

                		\n

                Mean Rank<\/p>\n<\/td>\n

                		\n

                Sum of Ranks<\/p>\n<\/td>\n<\/tr>\n

                \n

                Bone graft volume<\/p>\n<\/td>\n

                		\n

                AP<\/p>\n<\/td>\n

                		\n

                41<\/p>\n<\/td>\n

                		\n

                46.89<\/p>\n<\/td>\n

                		\n

                1922.50<\/p>\n<\/td>\n<\/tr>\n

                \n

                SG<\/p>\n<\/td>\n

                		\n

                120<\/p>\n<\/td>\n

                		\n

                92.65<\/p>\n<\/td>\n

                		\n

                11118.50<\/p>\n<\/td>\n<\/tr>\n

                \n

                Total<\/p>\n<\/td>\n

                		\n

                161<\/p>\n<\/td>\n

                		\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
                \u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n
                \n

                Test Statistics<\/strong>a<\/sup><\/strong><\/p>\n<\/td>\n<\/tr>\n

                \u00a0<\/td>\n\n

                Bone graft volume<\/p>\n<\/td>\n<\/tr>\n

                \n

                Mann-Whitney U<\/p>\n<\/td>\n

                		\n

                1061.500<\/p>\n<\/td>\n<\/tr>\n

                \n

                Wilcoxon W<\/p>\n<\/td>\n

                		\n

                1922.500<\/p>\n<\/td>\n<\/tr>\n

                \n

                Z<\/p>\n<\/td>\n

                		\n

                -5.427<\/p>\n<\/td>\n<\/tr>\n

                \n

                Asymp. Sig. (2-tailed)<\/p>\n<\/td>\n

                		\n

                .000<\/p>\n<\/td>\n<\/tr>\n

                \n

                a. Grouping Variable: Procedure Performer<\/p>\n<\/td>\n<\/tr>\n

                \u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                Conclusions:<\/strong><\/p>\n

                A mandibular ramus donor site can provide sufficient autologous bone volume to restore dentoalveolar defects prior to dental implantation.<\/p>\n

                P<\/ins>The p<\/del>ositive correlations were found between a<\/ins> patient\u2019<\/ins>s age and missing teeth, between clinicians A and B and their harvested bone volumes, and<\/ins> between harvested bone volume and a<\/ins> patient\u2019<\/ins>s age in a<\/del> group A but this was<\/ins> not significant in Group B.<\/ins>,<\/del> B<\/ins>b<\/del>etween a<\/ins> patient\u2019<\/ins>s age and gender in both groups A and B there was no significant correlation based on the<\/ins> multiple regression analysis outcome SPSS.<\/p>\n

                To conclude, with <\/ins> the<\/del>an<\/ins> <\/del>increasing<\/del>e<\/ins> i<\/ins>n<\/ins> age there were a higher number of teeth missing in both groups A and B. Although,<\/del> the diameter of bone reconstruction were<\/del> w<\/ins>as<\/ins> greater because of a<\/del> more missing teeth, the harvested volumes were greater only in the<\/del> Group A harvested by c<\/ins>C<\/del>linician A (p<0.05). Moreover, there is<\/del> was<\/ins> a significant difference between clinicians A and B and their harvested bone graft volumes in<\/ins> Group A and B (p<0.05). Overall, the harvested bone volume from ascending mandibular ramus depends on the person who<\/ins> operates<\/ins>or<\/del>.<\/p>\n

                <\/a>In<\/ins> a<\/ins>A<\/del>dditionally<\/del> to mandibular,<\/ins> ascending ramus bone can be harvested at<\/ins> intraoral sites and<\/ins> can be considered incrementally to the<\/ins> performed procedure, [S5]<\/a>such as the contralateral ramus site, chin, and maxillary tuberosity,<\/ins> where<\/del> wh<\/ins>en<\/ins> <\/ins>greater bone volumes are required. Moreover, the<\/del> bone materials can be also<\/ins> added too, increase the further<\/del> if the bone volume is yet<\/del> not yet<\/ins> sufficient. And finally, based on the literature review findings, the majority of iliac crest bone graft can be successfully replaced with ascending ramus bone grafts as the studies revealed that<\/ins> the harvested bone grafts are not significantly greater.<\/p>\n

                The outcome of implant therapy has been summarized in several recent reviews (Cochran 1996, Esposito et al. 1998, Fritz 1996, Fiorellini et al. 1998, Gotfredsen 1999, <\/ins>Mericske-Stern 1999, Van Steenberge et al. 1999) and evaluations are often reported in success and survival rates. The interpretation of the results, however, relies on the concept that different investigators use similar criteria for implant success and survival. Variations in study design and study period, and an improper definition of the selection of patients are factors that may further affect the interpretation of the<\/ins> data.<\/p>\n

                First, autologous bone grafts of various types to different locations can be successfully used to improve the ability to place endosseous implants. Complications that lead to failure can be minimized with experience and adherence to t<\/ins>he<\/ins> basic surgical principles of rigid fixation and tension-free primary closure of the soft tissue flaps. Second, most of the grafting failures are associated with infection or exposure of the graft to the oral cavity because of mucosal flap dehiscence. Early loading of grafts with a transitional prosthesis is also a potential cause of graft compromise or failure. Third, the successful placement of endosseous implants in autologous grafts is more predictable when they are placed secondarily after bone graft consolidation; and<\/ins>.<\/del> f<\/ins>F<\/del>ourth, whether placed immediately with the bone graft, or secondarily, failure of individual implants does not imply failure of the bone graft.<\/p>\n

                Frenuloplasty, Frenectomy, Vestibuloplasty Technique (Liposky, 1983) o<\/ins>O<\/del>r Mandibular Anterior Ridge Extension: Modification of the Kazanjian (Al-Mahdy Al-Belasy, 1997), Vestibule and floor-of-mouth extension procedures, Soft-tissue grafts (full thickness or connective)<\/p>\n

                Although COHRANE stated that autologous is not in favour, this statement needs to be taken<\/del> considered<\/ins> very carefuly<\/del>carefully<\/ins> because the outcome does not measure all aspects in convensional<\/del>conventional<\/ins> terms<\/ins> of success. As stated before,<\/ins> a simple<\/del> implants<\/del> survival is no longer a single preferable outcome today. Cohrane agrees that there is little<\/del>are few<\/ins> randomized controlled trials and for most that are conducted today are at<\/del> a high risk of bias <\/ins>remains<\/ins>.<\/p>\n

                Further <\/del>more, bone augmentation, such<\/ins> as syntetic<\/del>synthetic<\/ins> bone materials,<\/ins> provide a<\/ins> poorer outcome rather<\/del> tha<\/ins>e<\/del>n animal retrieved bone materials. However, because of culture<\/del> cultur<\/ins>al<\/ins> <\/ins>or religious reasons animal products may not be accepted for a<\/del> certain<\/ins> groups<\/ins> of patient and therefore<\/ins> autologous bone grafts are then is<\/del>remain<\/ins> <\/del>a single o<\/ins>a<\/del>ption to augment the<\/del> alveolar crest defects.<\/p>\n

                Ae<\/ins>E<\/del>sthetics and harmony in dental implant placement was well described by Belser et al.,<\/del> 1998. Buccal bone thickness has to<\/del>should<\/ins> be a minimum of 2mm and ideally 3mm from the implant buccal surface.<\/p>\n

                1<\/p>\n\n

                [S1]<\/a>Not sure about this. Does it relate to the heading i.e. \u2018Saddle graft is Indicated where both horizontal and vertical ridge augmentation\u2026\u2019<\/p>\n

                [S2]<\/a>Please check I haven\u2019t changed the meaning<\/p>\n

                [S3]<\/a>Are these page numbers? Should it be (Esposito, Hirsch, Lekholm, & Thomsen, 1999 75,77, 102\u2013111)<\/p>\n

                [S4]<\/a>Please check \u00ef\u0081\u0160<\/p>\n

                [S5]<\/a>Please check this one. I\u2019ve read it many times and am a little confused \u00ef\u0081\u0160<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

                TYPES OF GRAFTS: Osseointegrated implants can be combined with the following types of graft: inlay, saddle, veneer, onlay (partial or full arch), and maxillary sinus grafts. (Triplett & Schow, 1996) The mucoperiosteal flap should be designed to adequately expose the underlying residual ridge, maintain a broad base for vascular support, and allow tension-free primary closure. […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2469,90,3568,3178,3567],"tags":[3573,3569,3570,1998,3572,2490,3574,3571],"class_list":["post-10898","post","type-post","status-publish","format-standard","hentry","category-health-care-essays","category-healthcare","category-nurscribe","category-nursing-discussion-post-example-essay","category-us","tag-healthcare-essay-service","tag-help-with-nursing-discussion-board","tag-i-need-help-writing-a-nursing-essay","tag-nursing-paper","tag-nursing-study-bay","tag-online-nursing-papers","tag-research-essay-pro-writers","tag-superior-nursing-papers"],"_links":{"self":[{"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/posts\/10898","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/comments?post=10898"}],"version-history":[{"count":0,"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/posts\/10898\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/media?parent=10898"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/categories?post=10898"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.colapapers.com\/nursing\/wp-json\/wp\/v2\/tags?post=10898"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}