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  1. Rasmussen LD, Pedersen C, Madsen HD, Laursen CB
    BMJ Case Rep, 2017 Nov 29;2017.
    PMID: 29191821 DOI: 10.1136/bcr-2017-221025
    A 36-year-old Danish man, living in Asia, was diagnosed with Pneumocystis pneumonia (PCP) and HIV in 2013 (CD4+ count: 6 cells/µL; viral load: 518 000 copies/mL). He initiated combination antiretroviral therapy. Later that year, he was also diagnosed with granulomatosis with polyangiitis and was treated with prednisolone. Despite complete viral suppression and increasing CD4+ count (162 cells/µL), he was readmitted with PCP in April 2015. Subsequently, he returned to Denmark (CD4+ count: 80 cells/µL, viral suppression). Over the following months, he developed progressive dyspnoea. Lung function tests demonstrated severely reduced lung capacity with an obstructive pattern and a moderately reduced diffusion capacity. High resolution computer tomography revealed minor areas with tree-in-bud pattern and no signs of air trapping on expiratory views. Lung biopsy showed lymphocytic infiltration surrounding the bronchioles with sparing of the alveolar septa. He was diagnosed with follicular bronchiolitis. The patient spontaneously recovered along with an improvement of the immune system.
  2. Masood M, Younis LT, Masood Y, Bakri NN, Christian B
    J Clin Periodontol, 2019 02;46(2):170-180.
    PMID: 30657192 DOI: 10.1111/jcpe.13072
    OBJECTIVES: The aim of this study was to investigate the impact of periodontal disease on the domains of oral health-related quality of life (OHRQoL) of United Kingdom adults.

    METHODS: National representative data from the 2009 Adult Dental Health Survey, United Kingdom, were used in this study. Periodontal disease severity was measured using periodontal pocket depth and categorized into three groups: pocket depth up to 3.5, 3.5-5.5 and more than 5.5 mm. OHRQoL was measured using the Oral Health Impact Profile-14 (OHIP-14) scores. Bivariate and multivariable Zero-inflated Poisson regression analysis was used.

    RESULTS: A total of 6378 participants was analysed in this study. Periodontal pocketing was significantly associated with higher OHIP-14 scores. Participants with periodontal pocket depths >3.5 mm had a significantly higher prevalence for functional limitation, physical pain and social disability than participants with pocket depths of less than 3.5 mm. Participants with periodontal pocket depth(s) >5.5 mm had significantly higher OFOVO prevalence in all the domains of OHIP-14 except handicap domain than participants with pocket depth(s) <3.5 mm.

    PARTICIPANTS:

    CONCLUSION: This study showed that for a nationally representative sample of the United Kingdom population, periodontal disease was significantly associated with the domains of OHRQoL.

  3. Abas FS, Shana'ah A, Christian B, Hasserjian R, Louissaint A, Pennell M, et al.
    Cytometry A, 2017 06;91(6):609-621.
    PMID: 28110507 DOI: 10.1002/cyto.a.23049
    The advance of high resolution digital scans of pathology slides allowed development of computer based image analysis algorithms that may help pathologists in IHC stains quantification. While very promising, these methods require further refinement before they are implemented in routine clinical setting. Particularly critical is to evaluate algorithm performance in a setting similar to current clinical practice. In this article, we present a pilot study that evaluates the use of a computerized cell quantification method in the clinical estimation of CD3 positive (CD3+) T cells in follicular lymphoma (FL). Our goal is to demonstrate the degree to which computerized quantification is comparable to the practice of estimation by a panel of expert pathologists. The computerized quantification method uses entropy based histogram thresholding to separate brown (CD3+) and blue (CD3-) regions after a color space transformation. A panel of four board-certified hematopathologists evaluated a database of 20 FL images using two different reading methods: visual estimation and manual marking of each CD3+ cell in the images. These image data and the readings provided a reference standard and the range of variability among readers. Sensitivity and specificity measures of the computer's segmentation of CD3+ and CD- T cell are recorded. For all four pathologists, mean sensitivity and specificity measures are 90.97 and 88.38%, respectively. The computerized quantification method agrees more with the manual cell marking as compared to the visual estimations. Statistical comparison between the computerized quantification method and the pathologist readings demonstrated good agreement with correlation coefficient values of 0.81 and 0.96 in terms of Lin's concordance correlation and Spearman's correlation coefficient, respectively. These values are higher than most of those calculated among the pathologists. In the future, the computerized quantification method may be used to investigate the relationship between the overall architectural pattern (i.e., interfollicular vs. follicular) and outcome measures (e.g., overall survival, and time to treatment). © 2017 International Society for Advancement of Cytometry.
  4. Hussain A, Via G, Melniker L, Goffi A, Tavazzi G, Neri L, et al.
    Crit Care, 2020 12 24;24(1):702.
    PMID: 33357240 DOI: 10.1186/s13054-020-03369-5
    COVID-19 has caused great devastation in the past year. Multi-organ point-of-care ultrasound (PoCUS) including lung ultrasound (LUS) and focused cardiac ultrasound (FoCUS) as a clinical adjunct has played a significant role in triaging, diagnosis and medical management of COVID-19 patients. The expert panel from 27 countries and 6 continents with considerable experience of direct application of PoCUS on COVID-19 patients presents evidence-based consensus using GRADE methodology for the quality of evidence and an expedited, modified-Delphi process for the strength of expert consensus. The use of ultrasound is suggested in many clinical situations related to respiratory, cardiovascular and thromboembolic aspects of COVID-19, comparing well with other imaging modalities. The limitations due to insufficient data are highlighted as opportunities for future research.
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