A Machine Learning Trainable Model to Assess the Accuracy of Probabilistic Record Linkage

Record linkage (RL) is the process of identifying and linking data that relates to the same physical entity across multiple heterogeneous data sources. Deterministic linkage methods rely on the presence of common uniquely identifying attributes across all sources while probabilistic approaches use non-unique attributes and calculates similarity indexes for pair wise comparisons. A key component of record linkage is accuracy assessment — the process of manually verifying and validating matched pairs to further refine linkage parameters and increase its overall effectiveness. This process however is time-consuming and impractical when applied to large administrative data sources where millions of records must be linked. Additionally, it is potentially biased as the gold standard used is often the reviewer’s intuition. In this paper, we present an approach for assessing and refining the accuracy of probabilistic linkage based on different supervised machine learning methods (decision trees, naïve Bayes, logistic regression, random forest, linear support vector machines and gradient boosted trees). We used data sets extracted from huge Brazilian socioeconomic and public health care data sources. These models were evaluated using receiver operating characteristic plots, sensitivity, specificity and positive predictive values collected from a 10-fold cross-validation method. Results show that logistic regression outperforms other classifiers and enables the creation of a generalized, very accurate model to validate linkage results

Efficacy of a Solution Composed by Verbascoside, Polyvinylpyrrolidone (PVP) and Sodium Hyaluronate in the Treatment of Chemotherapy-induced Oral Mucositis in Children With Acute Lymphoblastic Leukemia

Summary: The aim of this study was to assess the efficacy of a solution composed by verbascoside, polyvinylpyrrolidone, and sodium hyaluronate (Mucosyte) in the treatment of chemotherapy- induced oral mucositi (OM). Patients between 5 and 18 years receiving chemotherapy for acute lymphoblastic leukemia and with OM grade 1 or 2 were randomized in group A (treated with Mucosyte, 3 mouthwashes/d per 8d) and group B (treated with placebo, ie, an inert water-based solution, 3 mouthwashes/d per 8 d). The OM scoring was performed at day 1 (diagnosis of OM- T0), after 3 days of treatment (T1), and at day 8 (T2). Pain was evaluated through the visual analog scale with the same timing of OM measurement. A total of 56 patients were included (28 patients per group). Group A experienced a statistically significant decline of OM at T2 (P=0.0038); a statistically significant difference in pain reduction between 2 groups both at T1 and at T2 (P < 0.005) was observed. The use of Mucosyte mouthwashes in children with chemotherapy-induced OM may be recommended as supportive therapy

Assessing Strength of Evidence of Appropriate Use Criteria for Diagnostic Imaging Examinations

Objective For health information technology tools to fully inform evidence-based decisions, recommendations must be reliably assessed for quality and strength of evidence. We aimed to create an annotation framework for grading recommendations regarding appropriate use of diagnostic imaging examinations. Methods The annotation framework was created by an expert panel (clinicians in three medical specialties, medical librarians, and biomedical scientists) who developed a process for achieving consensus in assessing recommendations, and evaluated by measuring agreement in grading the strength of evidence for 120 empirically selected recommendations using the Oxford Levels of Evidence. Results Eighty-two percent of recommendations were assigned to Level 5 (expert opinion). Inter-annotator agreement was 0.70 on initial grading (κ = 0.35, 95% CI, 0.23-0.48). After systematic discussion utilizing the annotation framework, agreement increased significantly to 0.97 (κ = 0.88, 95% CI, 0.77-0.99). Conclusions A novel annotation framework was effective for grading the strength of evidence supporting appropriate use criteria for diagnostic imaging exams

The Contrasting Effect of Macromolecular Crowding on Amyloid Fibril Formation

Amyloid fibrils associated with neurodegenerative diseases can be considered biologically relevant failures of cellular quality control mechanisms. It is known that in vivo human Tau protein, human prion protein, and human copper, zinc superoxide dismutase (SOD1) have the tendency to form fibril deposits in a variety of tissues and they are associated with different neurodegenerative diseases, while rabbit prion protein and hen egg white lysozyme do not readily form fibrils and are unlikely to cause neurodegenerative diseases. In this study, we have investigated the contrasting effect of macromolecular crowding on fibril formation of different proteins.As revealed by assays based on thioflavin T binding and turbidity, human Tau fragments, when phosphorylated by glycogen synthase kinase-3β, do not form filaments in the absence of a crowding agent but do form fibrils in the presence of a crowding agent, and the presence of a strong crowding agent dramatically promotes amyloid fibril formation of human prion protein and its two pathogenic mutants E196K and D178N. Such an enhancing effect of macromolecular crowding on fibril formation is also observed for a pathological human SOD1 mutant A4V. On the other hand, rabbit prion protein and hen lysozyme do not form amyloid fibrils when a crowding agent at 300 g/l is used but do form fibrils in the absence of a crowding agent. Furthermore, aggregation of these two proteins is remarkably inhibited by Ficoll 70 and dextran 70 at 200 g/l.We suggest that proteins associated with neurodegenerative diseases are more likely to form amyloid fibrils under crowded conditions than in dilute solutions. By contrast, some of the proteins that are not neurodegenerative disease-associated are unlikely to misfold in crowded physiological environments. A possible explanation for the contrasting effect of macromolecular crowding on these two sets of proteins (amyloidogenic proteins and non-amyloidogenic proteins) has been proposed