The Effects of Sterilization Procedures on the Cutting Efficiency of Endodontic Instruments: A Systematic Review and Network Meta-Analysis

Abstract

Sterilization processes guarantee the sterility of dental instruments but can negatively affect instrument features by altering their physical and mechanical properties. The endodontic instrumentation can undergo a series of alterations, ranging from corrosion to variation in the cutting angle and then changes in the torsional properties and torsional fatigue resistance. This systematic literature review and meta-analysis aims to investigate alterations to the cutting efficiency of endodontic instruments that are induced by procedures for their disinfection and sterilization. Methodologies adopted for this investigation follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. The following were used as search terms on PubMed and Scopus: "endodontic sterilization", "endodontic autoclave", "cyclic fatigue", "torsional", "cutting efficiency", "sterilization", "surface characteristics", and "corrosion". At the end of the selection process, 36 articles were identified, and seven of them are included in this systematic review. The results of a meta-analysis conducted for the use of 10 autoclaving cycles shows a standardized mean difference (SMD) of 0.80 with a p-value equal to 0.04 with respect to effect on cutting efficiency. The network meta-analysis, through direct and indirect comparison between the different autoclave cycles (0, 1, 5, 10, and 15 cycles), revealed that treatment involving 15 autoclave cycles produced the most robust results in terms of having the greatest effects in terms of altered cutting efficiency with a probability of 57.7% and a SUCRA (surface under the cumulative ranking) of 80%. The alterations in the effects on cutting efficiency appear to be triggered after five cycles of sterilization by heat (autoclave). In conclusion, the meta-analysis of the data indicates that the autoclave sterilization protocol must not be repeated more than five times to preserve cutting efficiency. Within the limitations of this review, we can therefore establish that sterilization by autoclaving alone results in steel and NiTi instruments becoming less efficient in cutting after five cycles, as measured by a reduction in cutting efficiency.

Keywords: autoclave; cutting efficiency; endodontic; mechanical property; network meta-analysis; sterilization.

Figure 1

Flow chart of the different phases of the systematic review.

Figure 2

Funnel plot. The visual analysis highlights the heterogeneity between the studies (I² = 65%). The source of the heterogeneity between the data of different studies is indicated with the orange arrow. The study, in fact, is placed outside the funnel. SE: standard error; SMD: standardized mean difference.

Figure 3

Forest plot showing a significant reduction in the cutting depth after 10 sterilization cycles by autoclaving compared to 0 cycles. The reduction in cutting efficiency was, on average, 0.80 μm higher in the test than in the control group. Legend: Tau² = residual heterogeneity; Chi² = chi-squared test; df = degrees of freedom; I² = Higgins heterogeneity index; CI = confidence intervals; p = p-value; SD = standard deviation. The graph for each study shows the first author, date of publication, mean, standard deviation, and number of samples for the 2 groups (0 or 10 autoclave cycles). Furthermore, the standardized mean difference with associated confidence intervals and the weight expressed as a percentage of the total effect are reported.

Figure 4

Sensitivity analysis. (A) excluded Schafer (NiTi Kfile) 2002: SMD = 0.45 CI [−0.01, 0.91], p-value = 0.06, I² = 0%. (B) excluded Schafer (NiTi Kfile PVD) 2002: SMD = 0.99 CI [−0.05, 2.02], p-value = 0.06, I² = 72%. A sensitivity analysis was performed by repeating the primary meta-analysis, including and excluding the data alternately to clarify whether the results are robust with respect to the decisions made in the review process. The sensitivity analysis, in this case, shows that the obtained results and conclusions were not influenced by the decision to include or exclude any studies; in fact, the final effect in favor of 0 cycles does not change. However, the heterogeneity of the study changed from I² = 65% (Figure 3) to I² = 72% (Figure 4B) and up to I² = 0% (Figure 4A).

Figure 5

Network geometry. The size of the 5 nodes, one for each treatment, indicates the number of studies included in the corresponding nodes, while the thickness of the lines connecting 2 nodes indicates the amount of relevant data (0 (control), 1, 5, 10, and 15 cycles).

Figure 6

All direct and mixed comparisons. The pooled effect of a treatment in the comparison set (also called “pooled within design”) and the pooled overall effect (also called “pooled overall”) are marked in blue and red, respectively. The black squares in the center of the lines represent the estimate of the effect of a single study, and the black lines represent its confidence intervals. (A = 0 cycles (control), B = 1 cycles, C = 5 cycles, D = 10 cycles, and E = 15 cycles). The figure shows all the possible comparisons that emerged from the network analysis = 5 vs. 0 (Schafer -NiTi Kfile 2022, Schafer -NiTi Kfile PVD 2002), 5 vs. 1 (Morrison et al. 1989), 10 vs. 0 (Schafer -NiTi Kfile 2022, Schafer -NiTi Kfile PVD 2002, Neal et al. 1983), 10 vs. 1 (Morrison et al. 1989), 10 vs. 5 (Schafer -NiTi Kfile 2022, Schafer -NiTi Kfile PVD 2002, Morrison et al. 1989), 15 vs. 1 (Morrison et al. 1989), 15 vs. 10 (Morrison et al. 1989), and 15 vs. 5 (Morrison et al. 1989).

Figure 7

Results of the network rank test. Graphical ranking ((A) = 0 cycles (control), (B) = 1 cycles, (C) = 5 cycles, (D) = 10 cycles, (E) = 15 cycles); SUCRA: surface under the cumulative ranking. The higher the SUCRA value, the greater the probability that the cycles will cause an alteration in the cutting efficiency.