"Device landing zone" calcification, assessed by MSCT, as a predictive factor for pacemaker implantation after TAVI

After trans-catheter aortic valve implantation (TAVI), the need for postinterventional pacemaker (PM) implantation can occur in as many as 10-50% of cases, but it is not yet clear, how this need can be predicted. The aim of this study was to assess the possible predictive factors of post TAVI PM implantation based on Computed Tomography (CT) measured aortic valve calcification and its distribution.

An insulin infusion advisory system based on autotuning nonlinear model-predictive control

This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.

Appropriateness of reporting statistical results in orthodontics: the dominance of P values over confidence intervals

The purpose of this study was to search the orthodontic literature and determine the frequency of reporting of confidence intervals (CIs) in orthodontic journals with an impact factor. The six latest issues of the American Journal of Orthodontics and Dentofacial Orthopedics, the European Journal of Orthodontics, and the Angle Orthodontist were hand searched and the reporting of CIs, P values, and implementation of univariate or multivariate statistical analyses were recorded. Additionally, studies were classified according to the type/design as cross-sectional, case-control, cohort, and clinical trials, and according to the subject of the study as growth/genetics, behaviour/psychology, diagnosis/treatment, and biomaterials/biomechanics. The data were analyzed using descriptive statistics followed by univariate examination of statistical associations, logistic regression, and multivariate modelling. CI reporting was very limited and was recorded in only 6 per cent of the included published studies. CI reporting was independent of journal, study area, and design. Studies that used multivariate statistical analyses had a higher probability of reporting CIs compared with those using univariate statistical analyses. Misunderstanding of the use of P values and CIs may have important implications in implementation of research findings in clinical practice.

Predictive ability of a modified Örebro Musculoskeletal Pain Questionnaire in an acute/subacute low back pain working population

The original 'Örebro Musculoskeletal Pain Questionnaire' (original-ÖMPQ) has been shown to have limitations in practicality, factor structure, face and content validity. This study addressed these concerns by modifying its content producing the 'Örebro Musculoskeletal Screening Questionnaire' (ÖMSQ). The ÖMSQ and original-ÖMPQ were tested concurrently in acute/subacute low back pain working populations (pilot n = 44, main n = 106). The ÖMSQ showed improved face and content validity, which broadened potential application, and improved practicality with two-thirds less missing responses. High reliability (0.975, p < 0.05, ICC: 2.1), criterion validity (Spearman's r = 0.97) and internal consistency (α = 0.84) were achieved, as were predictive ability cut-off scores from ROC curves (112-120 ÖMSQ-points), statistically different ÖMSQ scores (p < 0.001) for each outcome trait, and a strong correlation with recovery time (Spearman's, r = 0.71). The six-component factor structure reflected the constructs originally proposed. The ÖMSQ can be substituted for the original-ÖMPQ in this population. Further research will assess its applicability in broader populations.

Identification, discrimination, and selective adaptation of simultaneous musical intervals

Four experiments investigated perception of major and minor thirds whose component tones were sounded simultaneously. Effects akin to categorical perception of speech sounds were found. In the first experiment, musicians demonstrated relatively sharp category boundaries in identification and peaks near the boundary in discrimination tasks of an interval continuum where the bottom note was always an F and the top note varied from A to A flat in seven equal logarithmic steps. Nonmusicians showed these effects only to a small extent. The musicians showed higher than predicted discrimination performance overall, and reaction time increases at category boundaries. In the second experiment, musicians failed to consistently identify or discriminate thirds which varied in absolute pitch, but retained the proper interval ratio. In the last two experiments, using selective adaptation, consistent shifts were found in both identification and discrimination, similar to those found in speech experiments. Manipulations of adapting and test showed that the mechanism underlying the effect appears to be centrally mediated and confined to a frequency-specific level. A multistage model of interval perception, where the first stages deal only with specific pitches may account for the results.

Concurrent and predictive validation of a novel robotic surgery simulator: a prospective, randomized study

We evaluated the concurrent and predictive validity of a novel robotic surgery simulator in a prospective, randomized study.

Model Predictive Control for Vehicle Stabilization at the Limits of Handling

Recent developments in vehicle steering systems offer new opportunities to measure the steering torque and reliably estimate the vehicle sideslip and the tire-road friction coefficient. This paper presents an approach to vehicle stabilization that leverages these estimates to define state boundaries that exclude unstable vehicle dynamics and utilizes a model predictive envelope controller to bound the vehicle motion within this stable region of the state space. This approach provides a large operating region accessible by the driver and smooth interventions at the stability boundaries. Experimental results obtained with a steer-by-wire vehicle and a proof of envelope invariance demonstrate the efficacy of the envelope controller in controlling the vehicle at the limits of handling.