Effect of Radiocapitellar Joint Over/Under Stuffing on Elbow Joint Contact Pressure.

PURPOSE: Comminuted radial head fractures are commonly treated by surgical resection or replacement with a prosthesis. A potential problem with radial head replacement is overlengthening of the radial neck ("overstuffing" of the radial head), which has been shown to affect both ulnohumeral kinematics and radiocapitellar pressures. We hypothesized that an overstuffed radial head prosthesis increases capitellar pressure and reduces coronoid pressure. METHODS: Seven human cadaveric elbows were prepared on a custom-designed apparatus simulating stabilizing muscle loads, and passively flexed from 0° to 90° under gravity valgus torque while joint contact pressures were measured. Each elbow was tested sequentially with different neck lengths, starting with the intact specimen followed by insertion of understuffed (-2 mm), standard-height (0 mm), and overstuffed (+2 mm) radial head prostheses in neutral forearm rotation, 40° pronation, and 40° supination positions, respectively. RESULTS: Capitellar mean contact pressures significantly increased after insertion of an overstuffed radial head prosthesis. In valgus position with neutral forearm rotation, capitellar mean contact pressure on the joint with an intact radial head averaged 227 ± 70 kPa. Insertion of understuffed, standard-height, and overstuffed radial head prostheses changed the mean contact pressures to 152 ± 76 kPa, 212 ± 68 kPa, and 491 ± 168 kPa, respectively. The overstuffed radial head group had significantly lower whole coronoid mean contact pressures (153 ± 56 kPa) compared with the intact (390 ± 138 kPa) and standard-height (376 ± 191 kPa) radial head groups. CONCLUSIONS: An increase in radial prosthesis height significantly increases capitellar contact pressures and reduces coronoid contact pressures. CLINICAL RELEVANCE: Restoration of the anatomic radial head height is critical when performing radial head arthroplasty to maintain normal joint biomechanics. Elevated capitellar contact pressures can potentially lead to pain and early degenerative changes.

Development of machine learning model for diagnostic disease prediction based on laboratory tests.

The use of deep learning and machine learning (ML) in medical science is increasing, particularly in the visual, audio, and language data fields. We aimed to build a new optimized ensemble model by blending a DNN (deep neural network) model with two ML models for disease prediction using laboratory test results. 86 attributes (laboratory tests) were selected from datasets based on value counts, clinical importance-related features, and missing values. We collected sample datasets on 5145 cases, including 326,686 laboratory test results. We investigated a total of 39 specific diseases based on the International Classification of Diseases, 10th revision (ICD-10) codes. These datasets were used to construct light gradient boosting machine (LightGBM) and extreme gradient boosting (XGBoost) ML models and a DNN model using TensorFlow. The optimized ensemble model achieved an F1-score of 81% and prediction accuracy of 92% for the five most common diseases. The deep learning and ML models showed differences in predictive power and disease classification patterns. We used a confusion matrix and analyzed feature importance using the SHAP value method. Our new ML model achieved high efficiency of disease prediction through classification of diseases. This study will be useful in the prediction and diagnosis of diseases.

Component fracture after total elbow arthroplasty.

BACKGROUND: Ulnar or humeral component stem fractures after total elbow arthroplasty (TEA) are serious complications. We hypothesized that TEA stem component fractures are fatigue fractures that result from periarticular osteolysis caused by bushing wear, which leads to a region of unsupported stem adjacent to a region where the stem is well-fixed. METHODS: A review of 2637 primary and revision TEA cases from 1972 to 2016 revealed that 47 operations in 46 patients were complicated by or performed to deal with component stem fractures. Bushing wear was graded according to percentage loss of polyethylene thickness and metal wear. RESULTS: In the 39 cases in which bushing wear was able to be quantitated, it was severe in 34, moderate in 2, and mild in 3. Radiographs at final follow-up were available in 47 cases. All 47 cases showed evidence of periarticular osteolysis, which was in zone 1 in 17, in zones 1 and 2 in 29, and diffuse in 1. The length of the well-fixed stem, expressed as a percentage of total stem length, averaged 63% (range, 29%-86%). Stem fractures most often (27 of 47 cases) occurred at the junction between the well-fixed stem and unsupported stem. The median distance between the site of stem fracture and the unsupported-well-fixed stem junction was 0 mm (interquartile range, 0-5 mm). CONCLUSION: On the basis of our findings, a component stem fracture after TEA seems to occur by fatigue failure at or near the junction between an unsupported stem and well-fixed stem. This area of unsupported stem occurs as a result of osteolysis caused by bushing wear. The solution for component fractures requires a solution for bushing wear.

Distal clavicle fractures: A new classification system.

INTRODUCTION: Existing various classification systems for distal clavicle fractures have low interobserver and intraobserver reliability and provide limited information for treatment decision. The objective of this study was to determine interobserver and intraobserver reliability of the new classification system and the associated treatment choice for distal clavicle fractures. HYPOTHESIS: The new classification system has good reliability. METHODS: Eight observers including 4 experienced shoulder specialists and 4 orthopedic fellows independently reviewed routine plain radiographs of 74 patients with distal clavicle fractures. They were asked to determine the fracture type according to the new classification system and the treatment choice for each case through web-based survey. Images from each case were randomly presented to the observers in 2 rounds 4 weeks apart. Reliability was assessed on the basis of Fleiss κ values. RESULTS: Interobserver and intraobserver reliability of the classification system were moderate (κ=0.434) and substantial (κ=0.644), respectively. Interobserver and intraobserver reliability of the treatment choice were moderate (κ=0.593) and substantial (κ=0.698), respectively. There were no significant differences in the level of reliability between experienced shoulder specialists and orthopedic fellows for any κ values (all p>0.05). CONCLUSION: Our study demonstrated moderate interobserver and substantial intraobserver reliability of the new classification system and the associated treatment choice for distal clavicle fractures. We believe that our novel classification system will help physicians to choose treatment and implants. LEVEL OF EVIDENCE: III, Cohort study, Diagnosis study.

ErmineJ: tool for functional analysis of gene expression data sets.

BACKGROUND: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories. The most common method for such analysis uses the hypergeometric distribution (or a related technique) to look for "over-representation" of groups among genes selected as being differentially expressed or otherwise of interest based on a gene-by-gene analysis. However, this method suffers from some limitations, and biologist-friendly tools that implement alternatives have not been reported. RESULTS: We introduce ErmineJ, a multiplatform user-friendly stand-alone software tool for the analysis of functionally-relevant sets of genes in the context of microarray gene expression data. ErmineJ implements multiple algorithms for gene set analysis, including over-representation and resampling-based methods that focus on gene scores or correlation of gene expression profiles. In addition to a graphical user interface, ErmineJ has a command line interface and an application programming interface that can be used to automate analyses. The graphical user interface includes tools for creating and modifying gene sets, visualizing the Gene Ontology as a table or tree, and visualizing gene expression data. ErmineJ comes with a complete user manual, and is open-source software licensed under the Gnu Public License. CONCLUSION: The availability of multiple analysis algorithms, together with a rich feature set and simple graphical interface, should make ErmineJ a useful addition to the biologist's informatics toolbox. ErmineJ is available from http://microarray.cu.genome.org.

Coexpression analysis of human genes across many microarray data sets.

We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function.