The effect of the interproximal contour of single external hexagon implant restorations on the prevalence of peri-implantitis: A retrospective study.

PURPOSE: The objective of this retrospective study was to evaluate the effect of the interproximal contour of single external hexagon implant restorations on the prevalence of peri-implantitis. MATERIAL AND METHODS: Records of 96 patients and 148 external hexagon (EH) implants with time in function ranging from 1 to 17 years were included in the study. The most recent clinical and radiographic data were collected from records and the prevalence of peri-implantitis was defined according to the 2017 World Workshop on the Classification of Periodontal and Peri-implant Diseases and Conditions. Marginal bone level (MBL), emergence angle (EA), emergence profile (EP), and crown/implant platform horizontal ratio (CIHR) were obtained from periapical radiographs. Dichotomous variables at the patient- and implant level were compared with association tests. Mann-Whitney U-Test was performed to compare continuous quantitative values between the studied groups. Binomial logistic regression was conducted to identify risk indicators associated with the peri-implantitis event at the patient- and implant level, with the significance level set at 5% for all tests. RESULTS: Nineteen patients (19.2%) and 24 implants (16.2%) with a mean time in function of 5.0 ± 4.7 years were classified as having peri-implantitis. No statistically significant differences concerning gender, mean age, implant location in the jaw, or time in function were observed between patients with or without peri-implantitis (p > 0.05). Of 24 implants with peri-implantitis 10 (41.7%) displayed EA ≤ 30° (16.4%) while 14 (58.3%) presented EA > 30° with no statistical difference between the groups (p > 0.05). No statistically significant associations were identified between EA, EP, or CIHR and the prevalence of peri-implantitis. CONCLUSION: The findings seem to indicate that the EA, EP, and CIHR of single restorations over external hexagon implants are not associated with the presence of peri-implantitis. However, prospective studies with larger samples are required to better ascertain such an association in the long term.

A new cure rate regression framework for bivariate data based on the Chen distribution.

The present study introduces a new multivariate mixture cure rate model based on the Chen probability distribution to model recurrent event data in the presence of cure fraction. In this context, we provide an alternative for the use of some usual modeling approaches as the semiparametric Cox proportional hazards model commonly used in lifetime data analysis, considering a new bivariate parametric model to be used in the data analysis of bivariate lifetime data assuming a mixture structure for the bivariate data in presence of covariates, censored data and cure fraction. Under a Bayesian setting, the proposed methodology was considered to analyze two real medical datasets from a retrospective cohort study related to leukemia and diabetic retinopathy diseases. The model validation process was addressed by using the Cox-Snell residuals, which allowed us to identify the suitability of the new proposed mixture cure rate model.

Accurate estimation for extra-Poisson variability assuming random effect models.

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.

Victims of road accidents with serious injuries and dependence on some individual, climatic and infrastructure factors on federal highways in Brazil.

Road or urban traffic accidents in Brazil have a large presence in external causes of mortality. The main goal of this study is to discover significant factors in the incidence of accidents on Brazilian highways based on a database with information on each person injured on federal highways in Brazil reported by the Federal Highway Police. Some factors are considered in the study as cause of the accident, type of accident, stage of the day, weather condition, highway type, highway facility, age of the victim, gender of the victim and type of vehicle. From the obtained results of chi-square tests and logistic regression models, it was observed statistical dependence (p < 0.05) of the occurrence of injured people with serious injuries and the factors cause of the accident, type of accident, day, highway type and vehicle type. Considering the dead victims, the covariates age, time of day, highway type, highway facility, gender and type of vehicle showed significance (p < 0.05). These results are of great interest for authorities to increase road enforcement, improve highway facilities and target the production of vehicles with better safety standards.

Mixture and nonmixture cure fraction models assuming discrete lifetimes: Application to a pelvic sarcoma dataset.

Different cure fraction models have been used in the analysis of lifetime data in presence of cured patients. This paper considers mixture and nonmixture models based on discrete Weibull distribution to model recurrent event data in presence of a cure fraction. The novelty of this study is the use of a discrete lifetime distribution in place of usual existing continuous lifetime distributions for lifetime data in presence of cured fraction, censored data, and covariates. In the verification of the fit of the proposed model it is proposed the use of randomized quantile residuals. An extensive simulation study is considered to evaluate the properties of the estimates of the parameters related to the proposed model. As an illustration of the proposed methodology, it is considered an application considering a medical dataset related to lifetimes in a retrospective cohort study conducted by Puchner et al. (2017) that consists of 147 consecutive cases with surgical treatment of a sarcoma of the pelvis between the years of 1980 and 2012.