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Purpose Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Material and methods Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Results Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P

PurposeWe aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders.MethodsWe used Arksey and O’Malley’s scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases.ResultsOur search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings.ConclusionsCDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

Purpose Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Material and methods Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Results Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P

Objective This pilot study aimed to inform future research evaluating the effectiveness of Platelet Rich Plasma (PRP) injection for tendinopathy. Design Randomized control trial (RCT) and synchronous observational cohort studies. For the RCT, consecutive consenting patients treated at an academic sports medicine clinic were randomly assigned to either a PRP or placebo control group. Setting The Glen Sather Sport Medicine Clinic, Edmonton, Canada. Patients The RCT included 9 participants with rotator cuff tendinopathy. The cohort study included 178 participants with a variety of tendinopathies. Interventions Patients receiving PRP were injected with 4 ml of platelets into the supraspinatus and/or infraspinatus, while patients in the placebo group were injected with 4ml of saline. All participants undertook a 3-month standardized, home-based, daily exercise program. Main Outcome Measures Participants in the RCT were re-evaluated 3, and 6 months post-injection. Change scores before and after injection on pain, disability and MRI-documented pathology outcomes were compared. In the cohort study, pain and disability were measured at 1, 2 and 3 months post-injection. Results For the RCT, 7 participants received PRP and 2 received placebo injections. Patients receiving PRP reported clinically important improvements in pain (>1.5/10 on VAS), disability (>15 point DASH change), and tendon pathology while those receiving placebo injections did not. In the observational cohort, statistically and clinically significant improvements in pain and disability were observed. Conclusion This pilot study provides information for planning future studies of PRP effectiveness. Preliminary results indicate intratendinous, ultrasound-guided PRP injection may lead to improvements in pain, function, and MRI-documented tendon pathology. Trial Registration Controlled-Trials.com ISRCTN68341698

Background: Limited data exist on the outcomes of patients who cross over to alternative strategies of rate and rhythm control for atrial fibrillation (AF). We investigated the reasons for crossover to alternative treatment strategies and its impact on mortality in patients who were enrolled in the