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  1. Article ; Online: Hand hygiene of kindergarten children-Understanding the effect of live feedback on handwashing behaviour, self-efficacy, and motivation of young children: Protocol for a multi-arm cluster randomized controlled trial.

    Dangis, Glenda / Terho, Kirsi / Graichen, Joanna / Günther, Sebastian A / Rosio, Riitta / Salanterä, Sanna / Staake, Thorsten / Stingl, Carlo / Pakarinen, Anni

    PloS one

    2023  Volume 18, Issue 1, Page(s) e0280686

    Abstract: Early implementation of interventions at a young age fosters behaviour changes and helps to adopt behaviours that promote health. Digital technologies may help to promote the hand hygiene behaviour of children. However, there is a lack of digital ... ...

    Abstract Early implementation of interventions at a young age fosters behaviour changes and helps to adopt behaviours that promote health. Digital technologies may help to promote the hand hygiene behaviour of children. However, there is a lack of digital feedback interventions focusing on the hand hygiene behaviour of preschool children in childhood education and care settings. This study protocol aims to describe a study that evaluates the effectiveness of a gamified live feedback intervention and explores underlying behavioural theories in achieving better hand hygiene behaviour of preschool children in early childhood education and care settings. This study will be a four-arm cluster randomized controlled trial with three phases and a twelve-month follow-up by country stratification. The sample size is 106 children of which one cluster will have a minimum number of 40 children. During the baseline phase, all groups will have automated monitoring systems installed. In the intervention phase, the control group will have no screen activity. The intervention groups will have feedback displays during the handwashing activity. Intervention A will receive instructions, and intervention B and C groups will receive instructions and a reward. In the post-intervention phase, all the groups will have no screen activity except intervention C which will receive instructions from the screen but no reward. The outcome measures will be hand hygiene behaviour, self-efficacy, and intrinsic motivation. Outcome measures will be collected at baseline, intervention, and post-intervention phases and a 12-month follow-up. The data will be analysed with quantitative and qualitative methods. The findings of the planned study will provide whether this gamified live feedback intervention can be recommended to be used in educational settings to improve the hand hygiene behaviour of preschool children to promote health. The trial is registered with ClinicalTrials.gov (registration number NCT05395988 https://clinicaltrials.gov/ct2/show/NCT05395988?term=NCT05395988&draw=2&rank=1).
    MeSH term(s) Humans ; Child, Preschool ; Hand Hygiene ; Hand Disinfection/methods ; Motivation ; Health Promotion ; Feedback ; Self Efficacy ; Randomized Controlled Trials as Topic
    Language English
    Publishing date 2023-01-24
    Publishing country United States
    Document type Clinical Trial Protocol ; Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0280686
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Impact of gender on extent of lung injury in COVID-19.

    Dangis, A / De Brucker, N / Heremans, A / Gillis, M / Frans, J / Demeyere, A / Symons, R

    Clinical radiology

    2020  Volume 75, Issue 7, Page(s) 554–556

    MeSH term(s) Aged ; Belgium ; Betacoronavirus ; COVID-19 ; Coronavirus Infections/complications ; Coronavirus Infections/diagnostic imaging ; Female ; Humans ; Lung/diagnostic imaging ; Lung Injury/complications ; Lung Injury/diagnostic imaging ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral/complications ; Pneumonia, Viral/diagnostic imaging ; SARS-CoV-2 ; Sex Factors ; Tomography, X-Ray Computed/methods
    Keywords covid19
    Language English
    Publishing date 2020-04-23
    Publishing country England
    Document type Letter
    ZDB-ID 391227-9
    ISSN 1365-229X ; 0009-9260
    ISSN (online) 1365-229X
    ISSN 0009-9260
    DOI 10.1016/j.crad.2020.04.005
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: A statistical framework to estimate diagnostic test performance for COVID-19.

    Symons, R / Beath, K / Dangis, A / Lefever, S / Smismans, A / De Bruecker, Y / Frans, J

    Clinical radiology

    2020  Volume 76, Issue 1, Page(s) 75.e1–75.e3

    MeSH term(s) COVID-19/diagnosis ; COVID-19/diagnostic imaging ; COVID-19 Nucleic Acid Testing/methods ; COVID-19 Nucleic Acid Testing/standards ; COVID-19 Nucleic Acid Testing/statistics & numerical data ; Humans ; Lung/diagnostic imaging ; Reproducibility of Results ; Tomography, X-Ray Computed/methods ; Tomography, X-Ray Computed/standards ; Tomography, X-Ray Computed/statistics & numerical data
    Keywords covid19
    Language English
    Publishing date 2020-10-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 391227-9
    ISSN 1365-229X ; 0009-9260
    ISSN (online) 1365-229X
    ISSN 0009-9260
    DOI 10.1016/j.crad.2020.10.004
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Impact of gender on extent of lung injury in COVID-19

    Dangis, A. / De Brucker, N. / Heremans, A. / Gillis, M. / Frans, J. / Demeyere, A. / Symons, R.

    Clinical Radiology

    2020  Volume 75, Issue 7, Page(s) 554–556

    Keywords Radiology Nuclear Medicine and imaging ; General Medicine ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 391227-9
    ISSN 1365-229X ; 0009-9260
    ISSN (online) 1365-229X
    ISSN 0009-9260
    DOI 10.1016/j.crad.2020.04.005
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: A statistical framework to estimate diagnostic test performance for COVID-19

    Symons, R. / Beath, K. / Dangis, A. / Lefever, S. / Smismans, A. / De Bruecker, Y. / Frans, J.

    Clinical Radiology ; ISSN 0009-9260

    2020  

    Keywords Radiology Nuclear Medicine and imaging ; General Medicine ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    DOI 10.1016/j.crad.2020.10.004
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Accuracy and Reproducibility of Low-Dose Submillisievert Chest CT for the Diagnosis of COVID-19.

    Dangis, Anthony / Gieraerts, Christopher / De Bruecker, Yves / Janssen, Lode / Valgaeren, Hanne / Obbels, Dagmar / Gillis, Marc / Van Ranst, Marc / Frans, Johan / Demeyere, Annick / Symons, Rolf

    Radiology. Cardiothoracic imaging

    2020  Volume 2, Issue 2, Page(s) e200196

    Abstract: Purpose: To demonstrate the accuracy and reproducibility of low-dose submillisievert chest CT for the diagnosis of coronavirus disease 2019 (COVID-19) infection in patients in the emergency department.: Materials and methods: This was a Health ... ...

    Abstract Purpose: To demonstrate the accuracy and reproducibility of low-dose submillisievert chest CT for the diagnosis of coronavirus disease 2019 (COVID-19) infection in patients in the emergency department.
    Materials and methods: This was a Health Insurance Portability and Accountability Act-compliant, institutional review board-approved retrospective study. From March 14 to 24, 2020, 192 patients in the emergency department with symptoms suggestive of COVID-19 infection were studied by using low-dose chest CT and real-time reverse transcription polymerase chain reaction (RT-PCR). Image analysis included the likelihood of COVID-19 infection and the semiquantitative extent of lung involvement. CT images were analyzed by two radiologists blinded to the RT-PCR results. Reproducibility was assessed using the McNemar test and intraclass correlation coefficient. Time between CT acquisition and report was measured.
    Results: When compared with RT-PCR, low-dose submillisievert chest CT demonstrated excellent sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for diagnosis of COVID-19 (86.7%, 93.6%, 91.1%, 90.3%, and 90.2%, respectively), in particular in patients with clinical symptoms for more than 48 hours (95.6%, 93.2%, 91.5%, 96.5%, and 94.4%, respectively). In patients with a positive CT result, the likelihood of disease increased from 43.2% (pretest probability) to 91.1% or 91.4% (posttest probability), while in patients with a negative CT result, the likelihood of disease decreased to 9.6% or 3.7% for all patients or those with clinical symptoms for >48 hours. The prevalence of alternative diagnoses based on chest CT in patients without COVID-19 infection was 17.6%. The mean effective radiation dose was 0.56 mSv ± 0.25 (standard deviation). Median time between CT acquisition and report was 25 minutes (interquartile range: 13-49 minutes). Intra- and interreader reproducibility of CT was excellent (all intraclass correlation coefficients ≥ 0.95) without significant bias in the Bland-Altman analysis.
    Conclusion: Low-dose submillisievert chest CT allows for rapid, accurate, and reproducible assessment of COVID-19 infection in patients in the emergency department, in particular in patients with symptoms lasting longer than 48 hours. Chest CT has the additional advantage of offering alternative diagnoses in a significant subset of patients.© RSNA, 2020.
    Language English
    Publishing date 2020-04-21
    Publishing country United States
    Document type Journal Article
    ISSN 2638-6135
    ISSN (online) 2638-6135
    DOI 10.1148/ryct.2020200196
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials.

    Gieraerts, Christopher / Dangis, Anthony / Janssen, Lode / Demeyere, Annick / De Bruecker, Yves / De Brucker, Nele / van Den Bergh, Annelies / Lauwerier, Tine / Heremans, André / Frans, Eric / Laurent, Michaël / Ector, Bavo / Roosen, John / Smismans, Annick / Frans, Johan / Gillis, Marc / Symons, Rolf

    Radiology. Cardiothoracic imaging

    2020  Volume 2, Issue 5, Page(s) e200441

    Abstract: Purpose: To compare the prognostic value and reproducibility of visual versus AI-assisted analysis of lung involvement on submillisievert low-dose chest CT in COVID-19 patients.: Materials and methods: This was a HIPAA-compliant, institutional review ...

    Abstract Purpose: To compare the prognostic value and reproducibility of visual versus AI-assisted analysis of lung involvement on submillisievert low-dose chest CT in COVID-19 patients.
    Materials and methods: This was a HIPAA-compliant, institutional review board-approved retrospective study. From March 15 to June 1, 2020, 250 RT-PCR confirmed COVID-19 patients were studied with low-dose chest CT at admission. Visual and AI-assisted analysis of lung involvement was performed by using a semi-quantitative CT score and a quantitative percentage of lung involvement. Adverse outcome was defined as intensive care unit (ICU) admission or death. Cox regression analysis, Kaplan-Meier curves, and cross-validated receiver operating characteristic curve with area under the curve (AUROC) analysis was performed to compare model performance. Intraclass correlation coefficients (ICCs) and Bland- Altman analysis was used to assess intra- and interreader reproducibility.
    Results: Adverse outcome occurred in 39 patients (11 deaths, 28 ICU admissions). AUC values from AI-assisted analysis were significantly higher than those from visual analysis for both semi-quantitative CT scores and percentages of lung involvement (all P<0.001). Intrareader and interreader agreement rates were significantly higher for AI-assisted analysis than visual analysis (all ICC ≥0.960 versus ≥0.885). AI-assisted variability for quantitative percentage of lung involvement was 17.2% (coefficient of variation) versus 34.7% for visual analysis. The sample size to detect a 5% change in lung involvement with 90% power and an α error of 0.05 was 250 patients with AI-assisted analysis and 1014 patients with visual analysis.
    Conclusion: AI-assisted analysis of lung involvement on submillisievert low-dose chest CT outperformed conventional visual analysis in predicting outcome in COVID-19 patients while reducing CT variability. Lung involvement on chest CT could be used as a reliable metric in future clinical trials.
    Language English
    Publishing date 2020-10-22
    Publishing country United States
    Document type Journal Article
    ISSN 2638-6135
    ISSN (online) 2638-6135
    DOI 10.1148/ryct.2020200441
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Accuracy and reproducibility of low-dose submillisievert chest CT for the diagnosis of COVID-19

    Dangis, Anthony / Gieraerts, Christopher / Bruecker, Yves De / Janssen, Lode / Valgaeren, Hanne / Obbels, Dagmar / Gillis, Marc / Ranst, Marc Van / Frans, Johan / Demeyere, Annick / Symons, Rolf

    Radiol Cardiothorac Imaging

    Abstract: PURPOSE: To demonstrate the accuracy and reproducibility of low-dose submillisievert chest CT for the diagnosis of COVID-19 infection in emergency room (ER) patients. MATERIALS AND METHODS: This was a HIPAA-compliant, institutional review board-approved ... ...

    Abstract PURPOSE: To demonstrate the accuracy and reproducibility of low-dose submillisievert chest CT for the diagnosis of COVID-19 infection in emergency room (ER) patients. MATERIALS AND METHODS: This was a HIPAA-compliant, institutional review board-approved retrospective study. From March 14(th) to March 24(th) 2020, 192 ER patients with symptoms suggestive of COVID-19 infection were studied with low-dose chest CT and real time polymerase chain reaction (RT-PCR). Image analysis included likelihood of COVID-19 infection and semi-quantitative extent of lung involvement. CT images were analyzed by 2 radiologists blinded to RT-PCR results. Reproducibility was assessed with McNemar test and intra-class correlation coefficient (ICC). Time between CT acquisition and report was measured. RESULTS: When compared to RT-PCR, low-dose submillisievert chest CT demonstrated excellent sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for diagnosis of COVID-19 (86.7%, 93.6%, 91.1%, 90.3%, and 90.2%, respectively), in particular in patients with clinical symptoms for >48h (95.6%, 93.2%, 91.5%, 96.5%, and 94.4%, respectively). In patients with a positive CT, likelihood of disease increased from 43.2% (pre-test probability) to 91.1% or 91.4% (post-test probability), while in patients with a negative CT, likelihood of disease decreased to 9.6% or 3.7% for all patients or those with clinical symptoms for >48h, respectively. The prevalence of alternative diagnoses based on chest CT in patients without COVID-19 infection was 17.6%. Mean effective radiation dose was 0.56±0.25 mSv (SD). Median time between CT acquisition and report was 25 minutes (IQR: 13-49 minutes). Intra- and interreader reproducibility of CT was excellent (all ICC□0.95) without significant bias in Bland-Altman analysis. CONCLUSION: Low-dose submillisievert chest CT allows for rapid, accurate and reproducible assessment of COVID-19 infection in ER patients, in particular in patients with symptoms lasting longer than 48 hours. Chest CT has the additional advantage of offering alternative diagnoses in a significant subset of patients.
    Keywords covid19
    Publisher PMC
    Document type Article ; Online
    DOI 10.1148/ryct.2020200196
    Database COVID19

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