Feasibility study of a single-blind randomised controlled trial of an occupational therapy intervention.

BACKGROUND Several factors facilitate or hinder efficacy research in occupational therapy. Strategies are needed, therefore, to support the successful implementation of trials. AIM To assess the feasibility of conducting a randomised controlled trial (RCT). The main feasibility objectives of this study were to assess the process, resources, management, and scientific basis of a trial RCT. MATERIAL AND METHODS A total of 10 occupational therapists, between the ages of 30 and 55 (M 43.4; SD 8.3) with seven to 26 years' (M 14.3; SD 6.1) experience, participated in this study. Qualitative data collected included minutes of meetings, reports, and field notes. The data were analysed based on the principles of content analysis, using feasibility objectives as the main categories. RESULTS Data analysis revealed strengths in relation to retention and inclusion criteria of participants, the study protocol, study organisation, and the competence of researchers. Weaknesses were found related to recruitment, randomisation, data collection, time for training and communication, commitment, and design. CONCLUSION The findings indicated that there are several factors which had a considerable impact on the implementation of an RCT in practice. However, it was useful to assess methods and procedures of the trial RCT as a basis to refine research plans.

Small-diameter titanium grade IV and titanium-zirconium implants in edentulous mandibles: five-year results from a double-blind, randomized controlled trial.

BACKGROUND The aim of this study was to compare the 5-year survival and success rates of 3.3 mm dental implants either made from titanium-zirconium (TiZr) alloy or from Grade IV titanium (Ti Grade IV) in mandibular implant-based removable overdentures. METHODS The core study had a follow-up period of 36 months and was designed as a randomized, controlled, double-blind, split-mouth multicenter clinical trial. Patients with edentulous mandibles received two Straumann Bone Level implants (diameter 3.3 mm, SLActive®), one of TiZr (test) and one of Ti Grade IV (control), in the interforaminal region. This follow-up study recruited patients from the core study and evaluated the plaque and sulcus bleeding indices, radiographic crestal bone level, as well as implant survival and success 60 months after implant placement. RESULTS Of the 91 patients who initially received implants, 75 completed the 36 month follow-up and 49 were available for the 60 month examination. Two patients were excluded so that a total of 47 patients with an average age of 72 ± 8 years were analysed. The characteristics and 36-month performance of the present study cohort did not differ from the non-included initial participants (p > 0.05). In the period since the 36-month follow-up examination, no implant was lost. The cumulative implant survival rate was 98.9 % for the TiZr group and 97.8 % for the Ti Grade IV group. Crestal bone level changes at 60 months were not different in the test and control group (TiZr -0.60 ± 0.69 mm and Ti Grade IV -0.61 ± 0.83 mm; p = 0.96). The cumulative implant success rate after 60 months was 95.8 and 92.6 % for TiZr and Ti Grade IV, respectively. CONCLUSIONS After 60 months, the positive outcomes of the 36 month results for TiZr and Ti Grade IV implants were confirmed, with no significant differences with regard to crestal bone level change, clinical parameters and survival or success rates. TiZr implants performed equally well compared to conventional Ti Grade IV 3.3 mm diameter-reduced implants for mandibular removable overdentures. TRIAL REGISTRATION Registered on www.clinicaltrials.gov: NCT01878331.

Small-diameter titanium Grade IV and titanium-zirconium implants in edentulous mandibles: three-year results from a double-blind, randomized controlled trial

OBJECTIVE The aim of this study was to compare crestal bone-level changes, soft tissue parameters and implant success and survival between small-diameter implants made of titanium/zirconium (TiZr) alloy or of Grade IV titanium (Ti) in edentulous mandibles restored with removable overdentures. MATERIALS AND METHODS This was a randomized, controlled, double-blind, split-mouth multicenter clinical trial. Patients with edentulous mandibles received two Straumann bone-level implants (diameter 3.3 mm), one of Ti Grade IV (control) and one of TiZr (test), in the interforaminal region. Implants were loaded after 6-8 weeks and removable Locator-retained overdentures were placed within 2 weeks of loading. Modified plaque and sulcus bleeding indices, radiographic bone level, and implant survival and success were evaluated up to 36 months. RESULTS Of 91 treated patients, 75 completed the three-year follow-up. Three implants were lost (two control and one test implant). The survival rates were 98.7% and 97.3%, and the mean marginal bone level change was -0.78 ± 0.75 and -0.60 ± 0.71 mm for TiZr and Ti Grade IV implants. Most patients had a plaque score of 0 or 1 (54% for test and 51.7% for control), and a sulcus bleeding score of 0 (46.1% for test and 44.9% for control). No significant differences were found between the two implant types for bone-level change, soft tissue parameters, survival and success. CONCLUSIONS After 36 months, similar outcomes were found between Ti Grade IV and TiZr implants. The results confirm that the results seen at 12 months continue over time.

A Logarithmic Image Prior for Blind Deconvolution

Blind Deconvolution consists in the estimation of a sharp image and a blur kernel from an observed blurry image. Because the blur model admits several solutions it is necessary to devise an image prior that favors the true blur kernel and sharp image. Many successful image priors enforce the sparsity of the sharp image gradients. Ideally the L0 “norm” is the best choice for promoting sparsity, but because it is computationally intractable, some methods have used a logarithmic approximation. In this work we also study a logarithmic image prior. We show empirically how well the prior suits the blind deconvolution problem. Our analysis confirms experimentally the hypothesis that a prior should not necessarily model natural image statistics to correctly estimate the blur kernel. Furthermore, we show that a simple Maximum a Posteriori formulation is enough to achieve state of the art results. To minimize such formulation we devise two iterative minimization algorithms that cope with the non-convexity of the logarithmic prior: one obtained via the primal-dual approach and one via majorization-minimization.

Bilayer Blind Deconvolution with the Light Field Camera

In this paper we propose a solution to blind deconvolution of a scene with two layers (foreground/background). We show that the reconstruction of the support of these two layers from a single image of a conventional camera is not possible. As a solution we propose to use a light field camera. We demonstrate that a single light field image captured with a Lytro camera can be successfully deblurred. More specifically, we consider the case of space-varying motion blur, where the blur magnitude depends on the depth changes in the scene. Our method employs a layered model that handles occlusions and partial transparencies due to both motion blur and out of focus blur of the plenoptic camera. We reconstruct each layer support, the corresponding sharp textures, and motion blurs via an optimization scheme. The performance of our algorithm is demonstrated on synthetic as well as real light field images.

A Clearer Picture of Total Variation Blind Deconvolution

Blind deconvolution is the problem of recovering a sharp image and a blur kernel from a noisy blurry image. Recently, there has been a significant effort on understanding the basic mechanisms to solve blind deconvolution. While this effort resulted in the deployment of effective algorithms, the theoretical findings generated contrasting views on why these approaches worked. On the one hand, one could observe experimentally that alternating energy minimization algorithms converge to the desired solution. On the other hand, it has been shown that such alternating minimization algorithms should fail to converge and one should instead use a so-called Variational Bayes approach. To clarify this conundrum, recent work showed that a good image and blur prior is instead what makes a blind deconvolution algorithm work. Unfortunately, this analysis did not apply to algorithms based on total variation regularization. In this manuscript, we provide both analysis and experiments to get a clearer picture of blind deconvolution. Our analysis reveals the very reason why an algorithm based on total variation works. We also introduce an implementation of this algorithm and show that, in spite of its extreme simplicity, it is very robust and achieves a performance comparable to the top performing algorithms.