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BackgroundPredictive modeling promises to improve our understanding of what variables influence patient satisfaction after total knee arthroplasty (TKA). The purpose of this article was to systematically review the relevant literature using predictive models of clinical outcomes after TKA. The aim was to identify the predictor strategies used for systematic data collection with the highest likelihood of success in predicting clinical outcomes.MethodsA Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol systematic review was conducted using 3 databases (MEDLINE, EMBASE, and PubMed) to identify all clinical studies that had used predictive models or that assessed predictive features for outcomes after TKA between 1996 and 2020. The ROBINS-I tool was used to evaluate the quality of the studies and the risk of bias.ResultsA total of 75 studies were identified of which 48 met our inclusion criteria. Preoperative predictive factors strongly associated with postoperative clinical outcomes were knee pain, knee-specific Patient-Reported Outcome Measure (PROM) scores, and mental health scores. Demographic characteristics, pre-existing comorbidities, and knee alignment had an inconsistent association with outcomes. The outcome measures that correlated best with the predictive models were improvement of PROM scores, pain scores, and patient satisfaction.ConclusionsSeveral algorithms, based on PROM improvement, patient satisfaction, or pain after TKA, have been developed to improve decision-making regarding both indications for surgery and surgical strategy. Functional features such as preoperative pain and PROM scores were highly predictive for clinical outcomes after TKA. Some variables such as demographics data or knee alignment were less strongly correlated with TKA outcomes.Level of evidenceSystematic review - Level III.

Background: The lack of proven efficacy of new healthcare interventions represents a problem for health systems globally. It is partly related to suboptimal implementation processes, leading to poor adoption of new interventions. Activation of Stratification Strategies and Results of the interventions on frail patients of Healthcare Services (ASSEHS) EU project (N° 2013 12 04) aims to study current existing health Risk Stratification (RS) strategies and tools on frail elderly patients. This paper aims at identifying variables that make the implementation of population RS tools feasible in different healthcare services.Methods: Two different methods have been used to identify the key elements in stratification implementation; i) a Scoping Review, in order to search and gather scientific evidence and ii) Semi-structured interviews with six key experts that had been actively involved in the design and/or implementation of RS strategies. It aims to focus the implementation construct on real-life contextual understandings, multi-level perspectives, and cultural influences.Results: A Feasibility Framework has been drawn. Two dimensions impact the feasibility of RS: (i) Planning, deployment and change management and (ii) Care intervention. The former comprises communication, training and mutual learning, multidisciplinarity of the team, clinicians' engagement, operational plan and ICT display and functionalities. The latter includes case finding and selection of the target population, pathway definition and quality improvement process.Conclusions: The Feasibility Framework provides a list of key elements that should be considered for an effective implementation of population risk stratification interventions. It helps to identify, plan and consider relevant elements to ensure a proper RS implementation. [ABSTRACT FROM AUTHOR]

The aim of the study was to investigate conditioned electroencephalography (EEG) responses to factually correct and incorrect statements in order to enable binary communication by means of a brain-computer interface (BCI). In two experiments with healthy participants true and false statements (serving as conditioned stimuli, CSs) were paired with two different tones which served as unconditioned stimuli (USs). The features of the USs were varied and tested for their effectiveness to elicit differentiable conditioned reactions (CRs). After acquisition of the CRs, these CRs to true and false statements were classified offline using a radial basis function kernel support vector machine. A mean single-trial classification accuracy of 50.5% was achieved for differentiating conditioned "yes" versus "no" thinking and mean accuracies of 65.4% for classification of "yes" and 68.8% for "no" thinking (both relative to baseline) were found using the best US. Analysis of the area under the curve of the conditioned EEG responses revealed significant differences between conditioned "yes" and "no" answers. Even though improvements are necessary, these first results indicate that the semantic conditioning paradigm could be a useful basis for further research regarding BCI communication in patients in the complete locked-in state. [ABSTRACT FROM AUTHOR]

Introduction: Classical neutral mechanical alignment in total knee arthroplasty (TKA) has been a standard paradigm, while more recently, other alignment schemas, such as kinematic, individualized, and functional, have been explored. This study aimed to investigate the effect of three-dimensional (3D) computed tomography (CT)-based surgical robotics inputs on a classically trained surgeon's TKA component positions and alignment targets over time., Materials and Methods: Data from 1,394 consecutive robotically-assisted TKAs by a single surgeon from 2016 to 2020 were analyzed. Metrics collected included pre-balance planned implant component positions, final planned implant component positions after soft tissue balancing, and constitutional alignment from CT scans. Joint line obliquity was plotted against the arithmetic hip-knee angle (aHKA) using coronal plane alignment of the knee (CPAK). Three categories of alignment strategy were defined: true mechanical alignment (tMA), adjusted mechanical alignment (aMA), and no mechanical alignment (noMA)., Results: A shift to overall varus component positioning was observed over the years. Joint line obliquity according to CPAK showed a wider spread in later years, and the distribution of tibial and femoral coronal alignment angles expanded over time., Conclusion: The study revealed a change in alignment targets and final positioning of components away from neutral biomechanical axes in a large volume of TKAs by a single, classically trained surgeon over five years of using a robotic arm-assisted TKA system with CT-based planning. The most dominant factor for this change was the use of 3D CT planning, allowing the surgeon to assess patient-specific anatomy and plan accordingly. Outcome data is needed to determine if this change in behavior and surgical technique was beneficial. In summary, using a CT scan-based robotically assisted technique led to a gradual and complete shift from tMA to predominantly a non-mechanically aligned philosophy in TKA.