A Case of Rheumatoid Arthritis with Unilateral Knee Synovial Hypertrophy in Hemiplegia

A 64-year-old woman suffering right hemiplegia came in with pain and swelling on her left knee, general weakness and poor oral intake for 2 months. On physical examination we were able to palpate a mass with irregular margin around the left suprapatellar area. From the results of the magnetic resonance imaging (MRI), synovial proliferative disease, infectious arthritis, or gouty arthritis was suspected. We performed a blood laboratory test to detect rheumatologic diseases, knee joint aspiration, and bone scan for differential diagnosis, and were able to diagnose rheumatoid arthritis (RA) from the results of blood laboratory, physical examination, and bone scan. Consequently, we started medications for controlling RA. Herein, we report a case of rheumatoid arthritis with unilateral knee synovial hypertrophy in hemiplegia. If a right hemiplegic patient has recurrent pain on the left knee and synovial hypertrophy, and fails to respond to treatment for osteoarthritis, early detection by evaluation for rheumatic disease is crucial to prevent severe sequelae influencing rehabilitation of hemiplegia

Racial Disparities in Access to DBS: Results of a Real-World U.S. Claims Data Analysis

INTRODUCTION: Deep brain stimulation (DBS) is an effective and standard-of-care therapy for Parkinson\u27s Disease and other movement disorders when symptoms are inadequately controlled with conventional medications. It requires expert care for patient selection, surgical targeting, and therapy titration. Despite the known benefits, racial/ethnic disparities in access have been reported. Technological advancements with smartphone-enabled devices may influence racial disparities. Real-world evidence investigations can shed further light on barriers to access and demographic disparities for DBS patients. METHODS: A retrospective cross-sectional study was performed using Medicare claims linked with manufacturer patient data tracking to analyze 3,869 patients who received DBS. Patients were divided into two categories: traditional omnidirectional DBS systems with dedicated proprietary controllers ( traditional ; RESULTS: A significant disparity in DBS utilization was evident. White individuals comprised 91.4 and 89.9% of traditional and smartphone-enabled DBS groups, respectively. Non-White patients were significantly more likely to live closer to implanting facilities compared with White patients. CONCLUSION: There is great racial disparity in utilization of DBS therapy. Smartphone-enabled systems did not significantly impact racial disparities in receiving DBS. Minoritized patients were more likely to live closer to their implanting facility than White patients. Further research is warranted to identify barriers to access for minoritized patients to receive DBS. Technological advancements should consider the racial discrepancy of DBS utilization in future developments

Machine learning-based clinical decision support for infection risk prediction

BackgroundHealthcare-associated infection (HAI) remains a significant risk for hospitalized patients and a challenging burden for the healthcare system. This study presents a clinical decision support tool that can be used in clinical workflows to proactively engage secondary assessments of pre-symptomatic and at-risk infection patients, thereby enabling earlier diagnosis and treatment.MethodsThis study applies machine learning, specifically ensemble-based boosted decision trees, on large retrospective hospital datasets to develop an infection risk score that predicts infection before obvious symptoms present. We extracted a stratified machine learning dataset of 36,782 healthcare-associated infection patients. The model leveraged vital signs, laboratory measurements and demographics to predict HAI before clinical suspicion, defined as the order of a microbiology test or administration of antibiotics.ResultsOur best performing infection risk model achieves a cross-validated AUC of 0.88 at 1 h before clinical suspicion and maintains an AUC >0.85 for 48 h before suspicion by aggregating information across demographics and a set of 163 vital signs and laboratory measurements. A second model trained on a reduced feature space comprising demographics and the 36 most frequently measured vital signs and laboratory measurements can still achieve an AUC of 0.86 at 1 h before clinical suspicion. These results compare favorably against using temperature alone and clinical rules such as the quick sequential organ failure assessment (qSOFA) score. Along with the performance results, we also provide an analysis of model interpretability via feature importance rankings.ConclusionThe predictive model aggregates information from multiple physiological parameters such as vital signs and laboratory measurements to provide a continuous risk score of infection that can be deployed in hospitals to provide advance warning of patient deterioration

Racial disparities in access to DBS: results of a real-world U.S. claims data analysis

IntroductionDeep brain stimulation (DBS) is an effective and standard-of-care therapy for Parkinson’s Disease and other movement disorders when symptoms are inadequately controlled with conventional medications. It requires expert care for patient selection, surgical targeting, and therapy titration. Despite the known benefits, racial/ethnic disparities in access have been reported. Technological advancements with smartphone-enabled devices may influence racial disparities. Real-world evidence investigations can shed further light on barriers to access and demographic disparities for DBS patients.MethodsA retrospective cross-sectional study was performed using Medicare claims linked with manufacturer patient data tracking to analyze 3,869 patients who received DBS. Patients were divided into two categories: traditional omnidirectional DBS systems with dedicated proprietary controllers (“traditional”; n = 3,256) and directional DBS systems with smart controllers (“smartphone-enabled”; n = 613). Demographics including age, sex, and self-identified race/ethnicity were compared. Categorical demographics, including race/ethnicity and distance from implanting facility, were analyzed for the entire population.ResultsA significant disparity in DBS utilization was evident. White individuals comprised 91.4 and 89.9% of traditional and smartphone-enabled DBS groups, respectively. Non-White patients were significantly more likely to live closer to implanting facilities compared with White patients.ConclusionThere is great racial disparity in utilization of DBS therapy. Smartphone-enabled systems did not significantly impact racial disparities in receiving DBS. Minoritized patients were more likely to live closer to their implanting facility than White patients. Further research is warranted to identify barriers to access for minoritized patients to receive DBS. Technological advancements should consider the racial discrepancy of DBS utilization in future developments

Curettage of benign bone tumors without grafts gives sufficient bone strength: A case-series of 78 patients

Background and purpose The defect that results after curettage of a bone tumor is usually filled in the same way. We report the outcome in patients with benign bone tumors that were treated with curettage but no filling

Skeletal Plasmacytoma: Progression of disease and impact of local treatment; an analysis of SEER database

<p>Abstract</p> <p>Background</p> <p>Previous reports suggest an as yet unidentifiable subset of patients with plasmacytoma will progress to myeloma. The current study sought to establish the risk of developing myeloma and determine the prognostic factors affecting the progression of disease.</p> <p>Methods</p> <p>Patients with plasmacytoma diagnosed between 1973 and 2005 were identified in the SEER database(1164 patients). Patient demographics and clinical characteristics, treatment(s), cause of death, and survival were extracted. Kaplan-Meier, log-rank, and Cox regression were used to analyze prognostic factors.</p> <p>Results</p> <p>The five year survival among patients initially diagnosed with plasmacytoma that later progressed to multiple myeloma and those initially diagnosed with multiple myeloma were almost identical (25% and 23%; respectively). Five year survival for patients with plasmacytoma that did not progress to multiple myeloma was significantly better (72%). Age > 60 years was the only factor that correlated with progression of disease (p = 0.027).</p> <p>Discussion</p> <p>Plasmacytoma consists of two cohorts of patients with different overall survival; those patients that do not progress to systemic disease and those that develop myeloma. Age > 60 years is associated with disease progression. Identifying patients with systemic disease early in the treatment will permit aggressive and novel treatment strategies to be implemented.</p