Download Evidence-Based Implant Dentistry by Oreste Iocca (eds.) PDF

By Oreste Iocca (eds.)

This ebook covers all points of implant dentistry, proposing up to date details that displays the top point of clinical facts as offered within the really good literature. one of the subject matters addressed through professional authors are the analysis of ordinary enamel as opposed to implant restorations, bone reaction to implant therapy, placement and loading time, implant layout and size, platform layout, implant abutments, prosthodontic therapy, reconstructive surgical procedure, and periimplantitis.

The volume of information on hand for the clinician operating within the box of implantology is very large and consistently expanding. the duty of final abreast of the newest facts and making use of it successfully in scientific perform is extra hindered through the truth that many clinical papers make contradictory claims and include methodological flaws and biases that generate confusion and absence of reliability. by contrast historical past, Evidence-Based Implant Dentistry will serve the reader as a liable and scientifically supported advisor to present implant therapy and key concerns within the box.

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Example text

Regarding the implant-supported FDP [28], common reported complications include prosthetic fracture, abutment or screw loosening, abutment or screw fracture, metal framework fracture (Fig. 7). Implant fracture is a rare but possible complication (Fig. 11). 12), ranges of 89–95 % and 80–95 % of survival are found for single crowns and fixed dental prostheses respectively. Be careful that Prostheses Survival are reported in this case.

5 %. In conclusion, results of this meta-analysis show that there does not seem to exist a difference in marginal bone level change after at least 1 year of follow-up. Also, high heterogeneity between studies is evident. 1 Network Meta-analysis A network meta-analysis is a method of conducting multiple treatment comparisons. For example, we can have a set of studies comparing treatment A versus treatment B and another set of studies comparing treatment A versus treatment C but no studies directly comparing treatment B versus treatment C.

Here is enough to say that increasing the sample size, increases the power. 80. This would mean that the probability of rejecting the null hypothesis given that it is not true is 80 %. With the p-value we quantify the strength of evidence against the null hypothesis and in favor of the alternative. The p-value is defined as the probability of observing the data at least as favorable to the alternative hypothesis. If we conduct a one-sided hypothesis test, for example, we can formulate the test in this way: -2 -1 0 1 2 3 We set a normal probing depth around implants to be around 4 mm; now we have a sample of implant patients treated with a smooth collar, and we assume that this may contribute to reduced probing depth after 1 year; in this case, we set a negative one-sided hypothesis test in this way (it is negative because we want to check for a value less than the hypothesis; if we would check for a value greater than the hypothesis, we would say that it is a positive test).

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