Aim The aim of the study was to evaluate the prevalence of periodontitis in dentate people between 2011 and 2020. Materials and Methods PUBMED, Web of Science, and LILACS were searched up to and including December 2021. Epidemiological studies reporting the prevalence of periodontitis conducted between 2011 and 2020 were eligible for inclusion in this review. Studies were grouped according to the case definition of confidence as confident (Centers for Disease Control [CDC] AAP 2012; CDC/AAP 2007; and Armitage 1999) and non‐confident (community periodontal index of 3 or 4, periodontal pocket depth >4 mm, and clinical attachment level ≥1 mm). Random effects meta‐analyses with double arcsine transformation were conducted. Sensitivity subgroup and meta‐regression analyses explored the effect of confounding variables on the overall estimates. Results A total 55 studies were included. The results showed a significant difference, with confident case definitions (61.6%) reporting nearly twice the prevalence as non‐confident classifications (38.5%). Estimates using confident periodontal case definitions showed a pooled prevalence of periodontitis of 61.6%, comprising 17 different countries. Estimates reporting using the CDC/AAP 2012 case definition presented the highest estimate (68.1%) and the CDC/AAP 2007 presented the lowest (48.8%). Age was a relevant confounding variable, as older participants (≥65 years) had the highest pooled estimate (79.3%). Conclusion Between 2011 and 2020, periodontitis in dentate adults was estimated to be around 62% and severe periodontitis 23.6%. These results show an unusually high prevalence of periodontitis compared to the previous estimates from 1990 to 2010.

In this paper a model to assess the efficiency of project management by a Portuguese company responsible for the electricity distribution is proposed. The main objectives of the model is to assist the company in three areas: Assess the efficiency of twenty five Operational Areas developing remote control projects of the distribution network, making more transparent the benefits of an integrated project management methodology; identify possible actions to improve the efficiency of those Operational Areas; and prepare the company to use the model for evaluating the efficiency of other projects. Data envelopment analysis is used to assess the ability of this utility in converting inputs into outputs upon remote control projects in the distribution network during a period of time. The most important findings of this study regard the identification of inefficient Operational Areas, further showing how much the Operational Areas should reduce their resources usage and which Operational Areas are performing at best level, setting the best practices to be benchmarked.