This large multicenter study validates the Bacterial Meningitis Score prediction rule in the era of conjugate pneumococcal vaccine as an accurate decision support tool. The risk of bacterial meningitis is very low (0.1%) in patients with none of the criteria. The Bacterial Meningitis Score may be helpful to guide clinical decision making for the management of children presenting to emergency departments with CSF pleocytosis.

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In patients with bacterial meningitis, antibiotic pretreatment is associated with higher cerebrospinal fluid glucose levels and lower cerebrospinal fluid protein levels, although pretreatment does not modify cerebrospinal fluid white blood cell count or absolute neutrophil count results.

Abstract-Recent studies show that concept-based approaches to opinion mining perform better than more canonical methods based on keyword spotting or word co-occurrence frequencies. SenticNet 1.0 is one of the most widely used publicly available resources for concept-based opinion mining. It gives polarity scores for a large number of single-and multi-word common sense concepts. However, developing high-quality opinion mining and sentiment analysis systems also requires affective information associated with the concepts. In this work, we present a methodology for enriching SenticNet concepts with affective information by assigning to them an emotion label. The created resource is freely available for academic use.

Coronavirus Disease (COVID19) is a fast-spreading infectious disease that is currently causing a healthcare crisis around the world. Due to the current limitations of the reverse transcription-polymerase chain reaction (RT-PCR) based tests for detecting COVID19, recently radiology imaging based ideas have been proposed by various works. In this work, various Deep CNN based approaches are explored for detecting the presence of COVID19 from chest CT images. A decision fusion based approach is also proposed, which combines predictions from multiple individual models, to produce a final prediction. Experimental results show that the proposed decision fusion based approach is able to achieve above 86% results across all the performance metrics under consideration, with average AUROC and F1-Score being 0.883 and 0.867, respectively. The experimental observations suggest the potential applicability of such Deep CNN based approach in real diagnostic scenarios, which could be of very high utility in terms of achieving fast testing for COVID19.

Lean principles implemented by one hospital service line improved patient discharge times enhanced patient ED throughput, and reduced ED boarding times.

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B-type natriuretic peptide levels were markedly elevated at presentation in the acute care setting for all patients in this cohort of children with newly diagnosed congenital or acquired heart disease. B-type natriuretic peptide levels from noncardiac patients were significantly lower, with no overlap to the cardiac disease group. B-type natriuretic peptide level can be useful as a diagnostic marker to aid in the recognition of pediatric critical heart disease in the acute care setting.