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      Microcirculatory blood flow during cardiac arrest and cardiopulmonary resuscitation does not correlate with global hemodynamics: an experimental study

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          Abstract

          Background

          Current research highlights the role of microcirculatory disorders in post-cardiac arrest patients. Affected microcirculation shows not only dissociation from systemic hemodynamics but also strong connection to outcome of these patients. However, only few studies evaluated microcirculation directly during cardiac arrest (CA) and cardiopulmonary resuscitation (CPR). The aim of our experimental study in a porcine model was to describe sublingual microcirculatory changes during CA and CPR using recent videomicroscopic technology and provide a comparison to parameters of global hemodynamics.

          Methods

          Cardiac arrest was induced in 18 female pigs (50 ± 3 kg). After 3 min without treatment, 5 min of mechanical CPR followed. Continuous hemodynamic monitoring including systemic blood pressure and carotid blood flow was performed and blood lactate was measured at the end of baseline and CPR. Sublingual microcirculation was assessed by the Sidestream Dark Field (SDF) technology during baseline, CA and CPR. Following microcirculatory parameters were assessed off-line separately for capillaries (≤20 µm) and other vessels: total and perfused vessel density (TVD, PVD), proportion of perfused vessels (PPV), microvascular flow index (MFI) and heterogeneity index (HI).

          Results

          In comparison to baseline the CA small vessel microcirculation was only partially preserved: TVD 15.64 (13.59–18.48) significantly decreased to 12.51 (10.57–13.98) mm/mm 2, PVD 15.57 (13.56–17.80) to 5.53 (4.17–6.60) mm/mm 2, PPV 99.64 (98.05–100.00) to 38.97 (27.60–46.29) %, MFI 3.00 (3.00–3.08) to 1.29 (1.08–1.58) and HI increased from 0.08 (0.00–0.23) to 1.5 (0.71–2.00), p = 0.0003 for TVD and <0.0001 for others, respectively. Microcirculation during ongoing CPR in small vessels reached 59–85 % of the baseline values: TVD 13.33 (12.11–15.11) mm/mm 2, PVD 9.34 (7.34–11.52) mm/mm 2, PPV 72.34 (54.31–87.87) %, MFI 2.04 (1.58–2.42), HI 0.65 (0.41–1.07). The correlation between microcirculation and global hemodynamic parameters as well as to lactate was only weak to moderate (i.e. Spearman’s ρ 0.02–0.51) and after adjustment for multiple correlations it was non-significant.

          Conclusions

          Sublingual microcirculatory parameters did not correlate with global hemodynamic parameters during simulated porcine model of CA and CPR. SDF imaging provides additional information about tissue perfusion in the course of CPR.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12967-016-0934-5) contains supplementary material, which is available to authorized users.

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          Most cited references29

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          Multiple correlations and Bonferroni's correction.

          Correlation coefficients between biological measurements and clinical scales are often calculated in psychiatric research. Calculating numerous correlations increases the risk of a type I error, i.e., to erroneously conclude the presence of a significant correlation. To avoid this, the level of statistical significance of correlation coefficients should be adjusted. Threshold levels of significance for correlation coefficients were adjusted for multiple comparisons in a set of k correlation coefficients (k = 1, 5, 10, 20, 50, 100) by Bonferroni's correction. Significant correlation coefficients were then calculated according to sample size. The change in the threshold values of significance is larger when the number of correlations goes from 1 to 5 than when it goes from 50 to 100. A correlation coefficient, statistically significant at 5% when calculated alone, can be under the threshold level of significance when calculated even among a few other coefficients. Focusing on the most relevant variables or the use of multivariate statistics is advocated.
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            How to evaluate the microcirculation: report of a round table conference

            Introduction Microvascular alterations may play an important role in the development of organ failure in critically ill patients and especially in sepsis. Recent advances in technology have allowed visualization of the microcirculation, but several scoring systems have been used so it is sometimes difficult to compare studies. This paper reports the results of a round table conference that was organized in Amsterdam in November 2006 in order to achieve consensus on image acquisition and analysis. Methods The participants convened to discuss the various aspects of image acquisition and the different scores, and a consensus statement was drafted using the Delphi methodology. Results The participants identified the following five key points for optimal image acquisition: five sites per organ, avoidance of pressure artifacts, elimination of secretions, adequate focus and contrast adjustment, and recording quality. The scores that can be used to describe numerically the microcirculatory images consist of the following: a measure of vessel density (total and perfused vessel density; two indices of perfusion of the vessels (proportion of perfused vessels and microcirculatory flow index); and a heterogeneity index. In addition, this information should be provided for all vessels and for small vessels (mostly capillaries) identified as smaller than 20 μm. Venular perfusion should be reported as a quality control index, because venules should always be perfused in the absence of pressure artifact. It is anticipated that although this information is currently obtained manually, it is likely that image analysis software will ease analysis in the future. Conclusion We proposed that scoring of the microcirculation should include an index of vascular density, assessment of capillary perfusion and a heterogeneity index.
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              A guide to human in vivo microcirculatory flow image analysis

              Various noninvasive microscopic camera technologies have been used to visualize the sublingual microcirculation in patients. We describe a comprehensive approach to bedside in vivo sublingual microcirculation video image capture and analysis techniques in the human clinical setting. We present a user perspective and guide suitable for clinical researchers and developers interested in the capture and analysis of sublingual microcirculatory flow videos. We review basic differences in the cameras, optics, light sources, operation, and digital image capture. We describe common techniques for image acquisition and discuss aspects of video data management, including data transfer, metadata, and database design and utilization to facilitate the image analysis pipeline. We outline image analysis techniques and reporting including video preprocessing and image quality evaluation. Finally, we propose a framework for future directions in the field of microcirculatory flow videomicroscopy acquisition and analysis. Although automated scoring systems have not been sufficiently robust for widespread clinical or research use to date, we discuss promising innovations that are driving new development. Electronic supplementary material The online version of this article (doi:10.1186/s13054-016-1213-9) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                petra.krupickova@fnmotol.cz
                Mikulas.Mlcek@staff.cuni.cz
                MichalHuptych@seznam.cz
                zuzana.mormanova@nemlib.cz
                Tomas.Boucek@vfn.cz
                tbelz@email.cz
                stanislav.lacko78@gmail.com
                milos.cerny@fnmotol.cz
                petr.neuzil@homolka.cz
                otomar.kittnar@lf1.cuni.cz
                Ales.Linhart@vfn.cz
                jbelo@vfn.cz
                Journal
                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                1479-5876
                8 June 2016
                8 June 2016
                2016
                : 14
                : 163
                Affiliations
                [ ]First Faculty of Medicine, Charles University in Prague, Katerinska 1660/32, 121 08 Prague 2, Czech Republic
                [ ]Department of Neonatology with NICU, University Hospital in Motol, V Uvalu 84, 150 06 Prague 5, Czech Republic
                [ ]Institute of Physiology, First Faculty of Medicine, Charles University in Prague, Albertov 5, 128 00 Prague 2, Czech Republic
                [ ]Czech Institute of Informatics, Robotics and Cybernetics (CIIRC), Czech Technical University in Prague, Zikova 1903/4, 166 36 Prague 6, Czech Republic
                [ ]Department of Neonatology, Krajska nemocnice Liberec, a.s., Husova 357/10, 460 63 Liberec, Czech Republic
                [ ]2nd Department of Medicine-Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, U Nemocnice 2, 128 00 Prague 2, Czech Republic
                [ ]Department of Cardiology, Na Homolce Hospital, Roentgenova 2, 150 30 Prague 5, Czech Republic
                Article
                934
                10.1186/s12967-016-0934-5
                4898356
                27277706
                07aaad53-82af-4a30-9bf5-32df45c6694f
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 16 October 2015
                : 1 June 2016
                Funding
                Funded by: Charles University in Prague, Czech Republic
                Award ID: GA UK No 942314
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Medicine
                microcirculation,sidestream dark field imaging,cardiac arrest,cardiopulmonary resuscitation,animal model,sublingual area,microscopy camera technology

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