The aim of the present study was to investigate the impact of oral diseases, socioeconomic status, and family environmental factors on changes in the perception of oral health-related quality of life (OHRQoL) in adolescents. A prospective cohort study was conducted in Juiz de Fora, Minas Gerais, Brazil, with a sample of 286 twelve-year-old adolescents from public and private schools, selected by means of multistage random sampling. The adolescents were clinically examined for dental caries experience (number of decayed, missing, and filled teeth -DMFT index), presence of bleeding, and orthodontic treatment needs. They were asked to complete the Brazilian version of the Child Perceptions Questionnaire ). In addition, parents answered a questionnaire about their socioeconomic status and family environmental characteristics. After 3 years, the adolescents were contacted again to participate in the research. Logistic regression models, with explanatory variables assessed both individually and jointly, were used to determine which independent variables impacted longitudinally on OHRQoL. The final result demonstrated that only DMFT explained part of the response variability in CPQ 11-14 scores. In conclusion, caries experience was an important predictor of OHRQoL in adolescents followed up for 3 years.
In applications of survival analysis, the failure rate function may frequently present a unimodal shape. In such cases, the log-normal and log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the odd log-logistic Weibull distribution is proposed for modelling data with a decreasing, increasing, unimodal and bathtub failure rate function as an alternative to the log-Weibull regression model. For censored data, we consider a classic method to estimate the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes and censoring percentages, various simulations are performed. In addition, the empirical distribution of some modified residuals is determined and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the new regression model applied to censored data. We analyse a real data set using the log-odd log-logistic Weibull regression model.
The objectives of this study were to evaluate the occurrence of microorganisms, the antimicrobial susceptibility profile, and the presence of multidrug resistant (MDR) bacteria in the urine of clinically healthy dogs and dogs with cystitis. The urine was collected through cystocentesis. Subsequently, culture and antimicrobial susceptibility tests were performed. The isolates were classified based on their resistance profile, to evaluate the presence of MDR bacteria. Statistical analyses were performed using the chi-squared or Fisher’s exact tests. Bacterial isolates were present in 24.39% of the dogs in the control group, and 60.27% of the dogs in the cystitis group. The cystitis group was associated with a higher risk of bacterial isolates than the control group (odds ratio = 7.5; 95% confidence interval = 2.81–22.40). The main isolates were Staphylococcus spp., Escherichia coli, Proteus spp., and Enterobacter spp. in both groups. A high percentage of isolates were resistant to ampicillin in both groups. The lowest resistance presented by the isolates in both groups was to meropenem. Only the resistance to quinolones was different between the groups. The proportions of MDR isolates were 70% (7/10) and 65.91% (29/44) in the control and cystitis groups, respectively. The results showed the presence of MDR bacteria in the urine of both the healthy dogs, and the dogs with cystitis. The drug resistance was high, reinforcing the importance of establishing an effective treatment approach against urinary tract infections in pets, to minimize the spread of bacterial resistance and its impact on public health.
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