Notes

Mycoplasma pneumoniae Seroprevalence and also Overall IgE Levels within People using Juvenile Idiopathic Joint disease.
This year less than 200 National Library of Medicine indexers expect to index 1 million articles, and this would not be possible without the assistance of the Medical Text Indexer (MTI) system. MTI is an automated indexing system that provides MeSH main heading/subheading pair recommendations to assist indexers with their heavy workload. Over the years, a lot of research effort has focused on improving main heading prediction performance, but automated fine-grained indexing with main heading/subheading pairs has received much less attention. This work revisits the subheading attachment problem, and demonstrates very significant performance improvements using modern Convolutional Neural Network classifiers. The best performing method is shown to outperform the current MTI implementation with a 3.7% absolute improvement in precision, and a 27.6% absolute improvement in recall. We also conducted a manual review of false positive predictions, and 70% were found to be acceptable indexing.Brigham and Women's Hospital (BWH) has received funding from the Centers for Medicare and Medicaid Services (CMS) to design and implement an electronic clinical quality measure (eCQM) assessing the rate of prolonged opioid prescribing practices following Total Hip Arthroplasty (THA) and Total Knee Arthroplasty (TKA). Utilizing an existing guideline, 'prolonged prescribing' has been defined as opioid prescriptions that exceed 42 days (6 weeks) following surgery. This measure was tested on 12,803 Partners' Healthcare (PHS) patients. Findings demonstrated that after 42 days, meeting the criteria for 'prolonged prescribing' as defined by the proposed measure, 3.7% of THA patients and 12.1% of TKA patients were still receiving opioids. With a better understanding of how specific clinician group post-operative prescribing practices compare with their peers and incorporating monetary incentives through the MIPS participation pathway of the Quality Payment Program (QPP), this measure will motivate orthopedic practices to improve their prescribing patterns, ultimately driving evidence-based quality improvement.The DESIREE project has developed a platform offering several complementary therapeutic decision support systems (DSSs) to improve care quality for breast cancer patients. A first assessment of the system was carried out in close-to-real tumor boards (TBs). Fourteen TB sessions were organized corresponding to a total of 125 exploitable decisions previously made without the system and re-played with the system after a washout period in three pilot sites. Results show an overestimation of declared compliance with guidelines when not using the system as compared to measured compliance with the recommendations issued from the guideline-based DSS of DESIREE. After using the system, measured compliance rate of decisions with guidelines was significantly improved from 74.4% to 89.6%. Most of the changes in decisions when using the guideline-based DSS were associated with non-compliant decisions that became compliant. Qualitative analysis and interviews showed that despite maturity issues, clinicians found DESIREE DSSs innovative and promising.Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan if possible. In addition to automatic vital sign monitoring, epilepsy patients need manual monitoring by trained personnel, a task that is very difficult to be performed continuously for each patient. Moreover, epileptic manifestations are highly personalized even within the same type of epilepsy. In this work we assess two machine learning methods, dictionary learning and an autoencoder based on long short-term memory (LSTM) cells, on the task of personalized epileptic event detection in videos, with a set of features that were specifically developed with an emphasis on high motion sensitivity. According to the strengths of each method we have selected different types of epilepsy, one with convulsive behaviour and one with very subtle motion. MLN2238 manufacturer The results on five clinical patients show a highly promising ability of both methods to detect the epileptic events as anomalies deviating from the stable/normal patient status.Emergency Medical Services (EMS) are an essential component of health systems and are critical to the provision of pediatric emergency care. Challenges in this setting include fast pace, need for advanced teamwork, situational awareness and limited resources. The purpose of this study was to identify human factors-related obstacles during care delivery by EMS teams that could lead to inefficiencies and patient safety issues. We examined video recordings of 24 simulations of EMS teams (paramedics and EMTs) who were providing care to pediatric patients. Two reviewers documented a total of 262 efficiency and patient safety issues in 4.25 hours of videos. These issues were grouped into 28 categories. Reviewers also documented 19 decision support opportunities. These issues and decision support opportunities can inform the design of clinical decision support systems that can improve EMS related patient outcomes.Multi-center observational studies require recognition and reconciliation of differences in patient representations arising from underlying populations, disparate coding practices and specifics of data capture. This leads to different granularity or detail of concepts representing the clinical facts. For researchers studying certain populations of interest, it is important to ensure that concepts at the right level are used for the definition of these populations. We studied the granularity of concepts within 22 data sources in the OHDSI network and calculated a composite granularity score for each dataset. Three alternative SNOMED-based approaches for such score showed consistency in classifying data sources into three levels of granularity (low, moderate and high), which correlated with the provenance of data and country of origin. However, they performed unsatisfactorily in ordering data sources within these groups and showed inconsistency for small data sources. Further studies on examining approaches to data source granularity are needed.
Read More: https://www.selleckchem.com/products/MLN-2238.html