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Children (Basel) ; 9(6)2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1884023


Specific Learning Disorders (SLD) are a group of heterogeneous health deficits frequently diagnosed in early childhood that cause difficulties in general intellectual functioning. In the last decades in Italy new laws have been developed to give practical guidelines for the best education plans for children with SLD. BACKGROUND: The aim of our study was to determine the efficacy of the educational treatment on SLD in Primary and Secondary schools in the Italian city of Barletta. We acquired valuable data to evaluate Special Education Needs during COVID-19. METHODS: Our study was conducted from April to June 2021, during the second "lockdown" period in Italy. A fact-finding survey was conducted to schools with a questionnaire provided to the teachers to acquire data on the SEN applied in the management of distance learning for children. RESULTS: The study involved 15 male and 6 female pupils with SLD in Primary Schools and 18 male and 6 female in Secondary Schools. The schools participating in the study organized distance learning programs with a support teacher with a 1:1 ratio. Data showed that all children with SLD needed a support teacher. CONCLUSIONS: The findings of this pilot study suggest that distance learning programs are able to achieve adequate educational goals, despite the difficulties of the lockdown period.

International Journal of Environmental Research and Public Health ; 17(18):6914, 2020.
Article | MDPI | ID: covidwho-783872


Purpose: To compare different commercial software in the quantification of Pneumonia Lesions in COVID-19 infection and to stratify the patients based on the disease severity using on chest computed tomography (CT) images. Materials and methods: We retrospectively examined 162 patients with confirmed COVID-19 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) test. All cases were evaluated separately by radiologists (visually) and by using three computer software programs: (1) Thoracic VCAR software, GE Healthcare, United States;(2) Myrian, Intrasense, France;(3) InferRead, InferVision Europe, Wiesbaden, Germany. The degree of lesions was visually scored by the radiologist using a score on 5 levels (none, mild, moderate, severe, and critic). The parameters obtained using the computer tools included healthy residual lung parenchyma, ground-glass opacity area, and consolidation volume. Intraclass coefficient (ICC), Spearman correlation analysis, and non-parametric tests were performed. Results: Thoracic VCAR software was not able to perform volumes segmentation in 26/162 (16.0%) cases, Myrian software in 12/162 (7.4%) patients while InferRead software in 61/162 (37.7%) patients. A great variability (ICC ranged for 0.17 to 0.51) was detected among the quantitative measurements of the residual healthy lung parenchyma volume, GGO, and consolidations volumes calculated by different computer tools. The overall radiological severity score was moderately correlated with the residual healthy lung parenchyma volume obtained by ThoracicVCAR or Myrian software, with the GGO area obtained by the ThoracicVCAR tool and with consolidation volume obtained by Myrian software. Quantified volumes by InferRead software had a low correlation with the overall radiological severity score. Conclusions: Computer-aided pneumonia quantification could be an easy and feasible way to stratify COVID-19 cases according to severity;however, a great variability among quantitative measurements provided by computer tools should be considered.