Prevention of Periprosthetic Joint Infection in Total Hip and Knee Replacement: One European Consensus

Periprosthetic joint infection (PJI) is a devastating complication in total hip and knee replacement. Its prevention is key to decrease the incidence and avoid some consequences that seriously impact patients and health systems. In view of the variety of recommendations and guidelines, we decided to conduct an expert, peer-reviewed European consensus analysis about the pre-, intra-, and postoperative prevention of PJI. A multinational group of practicing orthopedic experts developed a series of 47 consensus statements in 6 main groups of intervention, and a 2-stage Delphi approach was launched with a threshold for agreement at 75% and for very high agreement at more than 90%. A total of 306 orthopedic surgeon responses were gathered from 9 countries. Consensus was reached for 42/47 statements, 31/47 of which achieved a very high consensus. Many preoperative actions gathered strong consensus, although areas like the use of alcoholic chlorhexidine or the timing of hair removal did not attain strong consensus, despite available evidence. Intra- and postoperative actions showed more variability regarding incise drapes, skin suturing techniques, and wound follow-up. This study confirms an important consensus among orthopedic surgeons across Europe in many areas well known to contribute to the prevention of PJI; however, there are still grounds for improvement.

Mining Early Life Risk and Resiliency Factors and Their Influences in Human Populations from PubMed: A Machine Learning Approach to Discover DOHaD Evidence

The Developmental Origins of Health and Disease (DOHaD) framework aims to understand how early life exposures shape lifecycle health. To date, no comprehensive list of these exposures and their interactions has been developed, which limits our ability to predict trajectories of risk and resiliency in humans. To address this gap, we developed a model that uses text-mining, machine learning, and natural language processing approaches to automate search, data extraction, and content analysis from DOHaD-related research articles available in PubMed. Our first model captured 2469 articles, which were subsequently categorised into topics based on word frequencies within the titles and abstracts. A manual screening validated 848 of these as relevant, which were used to develop a revised model that finally captured 2098 articles that largely fell under the most prominently researched domains related to our specific DOHaD focus. The articles were clustered according to latent topic extraction, and 23 experts in the field independently labelled the perceived topics. Consensus analysis on this labelling yielded mostly from fair to substantial agreement, which demonstrates that automated models can be developed to successfully retrieve and classify research literature, as a first step to gather evidence related to DOHaD risk and resilience factors that influence later life human health.

Using cultural consensus analysis to measure diversity in social-ecological knowledge for inclusive climate adaptation planning

Climate adaptation is context specific and inclusion of diverse forms of knowledge is crucial for developing resilient social-ecological systems. Emphasis on local inclusion is increasing, yet participatory approaches often fall short of facilitating meaningful engagement of diverse forms of knowledge. A central challenge is the lack of a comprehensive and comparative understanding of the social-ecological knowledge that various stakeholders use to inform adaptation decisions. We employed cultural consensus analysis to quantitatively measure and compare social-ecological knowledge within and across three stakeholder groups - government employees, researchers, and local residents in rural coastal Maryland. The results show that 1) local residents placed more emphasis on addressing socio-economic and cultural changes than researchers and government employees, and 2) that the greatest variation in social-ecological knowledge was found among local residents. These insights yielded by cultural consensus analysis are beneficial for facilitating more inclusive adaptation planning for resilient social-ecological systems.

Distribution Linguistic Fuzzy Group Decision Making Based on Consistency and Consensus Analysis

The development of distribution linguistic provides a new research idea for linguistic information group decision-making (GDM) problems, which is more flexible and convenient for experts to express their opinions. However, in the process of using distribution linguistic fuzzy preference relations (DLFPRs) to solve linguistic information GDM problems, there are few studies that pay attention to both internal consistency adjustment and external consensus of experts. Therefore, this study proposes a fresh decision support model based on consistency adjustment algorithm and consensus adjustment algorithm to solve GDM problems with distribution linguistic data. Firstly, we review the concept of DLFPRs to describe the fuzzy linguistic evaluation information, and then we present the multiplicative consistency of DLFPRs and a new consistency measurement method based on the distance, and investigate the consistency adjustment algorithm to ameliorate the consistency level of DLFPRs. Subsequently, the consensus degree measurement is carried out, and a new consensus degree calculation method is put forward. At the same time, the consensus degree adjustment is taken the expert cost into account to make it reach the predetermined level. Finally, a distribution linguistic fuzzy group decision making (DLFGDM) method is designed to integrate the evaluation linguistic elements and obtain the final evaluation information. A case of the evaluation of China’s state-owned enterprise equity incentive model is provided, and the validity and superiority of the proposed method are performed by comparative analysis.

Improvement of the Catalytic Ability of a Thermostable and Acidophilic β-Mannanase Using a Consensus Sequence Design Strategy

In order to improve the catalytic efficiency of a thermostable and acidophilic β-mannanase (ManAK; derived from marine Aspergillus kawachii IFO 4308), three mutants were designed by amino acid sequence consensus analysis with a second β-mannanase (ManCbs), which also belongs to the glycoside hydrolase family 5 (GH5) and has excellent catalytic efficiency. Three mutants were constructed and their biochemical characteristics were measured after heterologous expression in Pichia pastoris. The results revealed that the kcat/Km values of the three recombinant mannanases ManAKC292V, ManAKL293V, and ManAKL294H were enhanced by 303.0, 280.4, and 210.1%, respectively. Furthermore, ManAKL293V showed greater thermostability than ManAK, retaining 36.5% of the initial enzyme activity after incubation at 80°C for 5min. This study therefore provides a rational design strategy based on consensus sequence analysis to develop industrially valuable β-mannanase for future applications in marine aquafeed.

Giving patients a voice in Health Technology Assessment decision-making in Greece: a patient advocacy group consensus analysis

Objective This analysis aimed to assess patient advocacy groups’ (PAGs) perspectives on patients’ and PAGs’ potential role in Health Technology Assessment (HTA) decision-making in Greece. Methods In total, 22 representatives of PAGs participated in a consensus panel meeting. Participants’ views were elicited via a consensus panel meeting, through a televoting procedure, based on a structured questionnaire with close-ended questions. Voting was anonymous, to avoid the influence of the dominant personality. After voting, the results were presented to the participants and televoting was repeated to achieve consensus. Key findings The majority of participants (94.8%) believe that valid information on the developments regarding HTA in Greece is not conveyed to them by the official national regulatory sources. Key sources of valid information on developments regarding HTA were: conferences (95.2%), international PAGs (85.7%) and HTA experts/scientists (76.2%). About 76.2% of participants evaluated PAGs’ competence to participate in policy-making concerning HTA scheme formation as moderate or higher. Regarding patients’ effective participation in HTA decision-making, greater importance (points 4 and 5 on a 5-point scale) was given to their education on treatment effects in terms of quality of life (100.0%), basic principles of health economics and pharmaceutical policy (95.5%) and ethical aspects of HTA (95.0%). About 55.0% strongly agree that patients should formally express their opinion on HTA issues, while 72.7% believe that patients’ opinions on HTA issues should be expressed through participation in the process and right to vote. Conclusions The participation of patients in HTA decision-making is an issue not only of justice but also of essence. For a productive participation, PAGs training is essential.