Towards a Model to Address the Interplay Between IoT Applications and Users in Complex Heterogeneous Contexts

Internet of Things (IoT) is now pervasive in most business and Public Administration processes. Along with the dizzying development of technological solutions, in recent years new methodological approaches are emerging with the objective of abstracting IoT functionalities, in order to manage them as resources in project management methodologies. A critical aspect is the representation of the knowledge grasped from the data acquired by IoT devices, since different types of users interact with such data with different goals. In order to transform them in knowledge, data have to be organized in a proper way and meaningfully provided in an IoT application specific for that type of user. In this paper, we propose the Knowledge Stratification Model that technical experts can take into account when developing an IoT application. The model, which organizes the knowledge elements in three layers, aims to identify the data produced by IoT devices and integrate them into business processes, thus making them meaningful for the user. A semantic approach, based on three subsets of ontologies specific for each model layer, is proposed to represent domain knowledge and to solve the technological and user interaction semantic issues characterizing complex and heterogeneous contexts as Smart City

Breast MRI Using a High-Relaxivity Contrast Agent: An Overview

OBJECTIVE. The purpose of this article is to review the use of gadobenate dimeglumine, a high-relaxivity gadolinium-based contrast material, for breast MRI. CONCLUSION. Thanks to its high relaxivity, gadobenate dimeglumine offers valuable advantages in terms of lesion conspicuity, detection rate, and sensitivity for malignant breast lesions. However, a higher enhancement of benign lesions should be taken into account to avoid reduced specificity

Comparison between two different techniques for peri-implant soft tissue augmentation: Porcine dermal matrix graft vs. tenting screw

The thickness of the soft tissues around dental implants is crucial for both the preservation of the marginal bone and esthetic profile. Many authors have showed the thickened soft tissues favor a better peri-implant bone stability, however different thickening techniques can be used for this aim

Impact on the recall rate of digital breast tomosynthesis as an adjunct to digital mammography in the screening setting. A double reading experience and review of the literature

OBJECTIVES:To estimate the impact on recall rate (RR) of digital breast tomosynthesis (DBT) associated with digital mammography (DM+DBT), compared to DM alone, evaluate the impact of double reading (DR) and review the literature. METHODS: Ethics committees approved this multicenter study. Patients gave informed consent. Women recalled from population-based screening reading were included. Reference standard was histology and/or 65 1 year follow up. Negative multiple assessment was considered for patients lost at follow up. Two blinded readers (R1, R2) evaluated first DM and subsequently DM+DBT. RR, sensitivity, specificity, accuracy, positive and negative predictive values (PPV, NPV), were calculated for R1, R2, and DR. Cohen \u3ba and \u3c7(2) were used for R1-R2 agreement and RR related to breast density. RESULTS: We included 280 cases (41 malignancies, 66 benign lesions, and 173 negative examinations). The RR reduction was 43% (R1), 58% (R2), 43% (DR). Sensitivity, specificity, accuracy, PPV and NPV were: 93%, 67%, 71%, 33%, 98% for R1; 88%, 73%, 75%, 36%, 97% for R2; 98%, 55%, 61%, 27%, 99% for DR. The agreement was higher for DM+DBT (\u3ba=0.459 versus \u3ba=0.234). Reduction in RR was independent from breast density (p=0.992). CONCLUSION: DBT was confirmed to reduce RR, as shown by 13 of 15 previous studies (reported reduction 6-82%, median 31%). This reduction is confirmed when using DR. DBT allows an increased inter-reader agreement

Procalcitonin Predicts Bacterial Infection, but Not Long-Term Occurrence of Adverse Events in Patients with Acute Coronary Syndrome

This study compiles data to determine if procalcitonin (PCT) values may predict both the risk of bacterial infection and potentially negative long-term outcomes in patients with acute coronary syndromes (ACS). All patients with a diagnosis of ACS that had PCT levels assessed during the first 24 h of hospitalization were enrolled in this study. The primary outcome was to detect the presence of bacterial infection defined as the occurrence of fever and at least one positive blood or urinary culture with clinical signs of infection. The secondary outcome was to monitor the occurrence after 1 year of the composite outcome of all-cause mortality, stroke and myocardial infarction. Overall, 569 patients were enrolled (mean age 69.37 ± 14 years, 30% females). Of these, 44 (8%) met the criteria for bacterial infection. After multivariate analysis, PCT and SBP were found to be independent predictors of bacterial infections (OR for PCT above the cut-off 2.67, 95% CI 1.09–6.53, p = 0.032 and OR for SBP 0.98, 95% CI 0.97–0.99, p = 0.043). After 1 year, the composite outcome of all-cause death, MI and stroke occurred in 104 patients (18%). PCT was not found to be an independent predictor of these outcomes. In conclusion, when assessing ACS, we found that testing for PCT levels during hospital admissions procedures was a good predictor of bacterial infections but not of all-cause mortality, stroke, or myocardial infarction. Clinicaltrial.org identifier: NCT02438085

Asthma in patients admitted to emergency department for COVID-19: prevalence and risk of hospitalization

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