5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Airway pressure release ventilation during acute hypoxemic respiratory failure: a systematic review and meta-analysis of randomized controlled trials

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Airway pressure release ventilation (APRV) has been considered a tempting mode of ventilation during acute respiratory failure within the concept of open lung ventilation. We performed a systematic review and meta-analysis to verify whether adult patients with hypoxemic respiratory failure have a higher number of ventilator-free days at day 28 when ventilated in APRV compared to conventional ventilation strategy. Secondary outcomes were difference in PaO 2/FiO 2 at day 3, ICU length of stay (LOS), ICU and hospital mortality, mean arterial pressure (MAP), risk of barotrauma and level of sedation. We searched MEDLINE, Scopus and Cochrane Central Register of Controlled Trials database until December 2018.

          Results

          We considered five RCTs for the analysis enrolling a total of 330 patients. For ventilatory-free day at day 28, the overall mean difference (MD) between APRV and conventional ventilation was 6.04 days (95%CI 2.12, 9.96, p = 0.003; I 2 = 65%, p = 0.02). Patients treated with APRV had a lower ICU LOS than patients treated with conventional ventilation (MD 3.94 days [95%CI 1.44, 6.45, p = 0.002; I 2 = 37%, p = 0.19]) and a lower hospital mortality (RD 0.16 [95%CI 0.02, 0.29, p = 0.03; I 2 = 0, p = 0.5]). PaO 2/FiO 2 at day 3 was not different between the two groups (MD 40.48 mmHg [95%CI − 25.78, 106.73, p = 0.23; I 2 = 92%, p < 0.001]). MAP was significantly higher during APRV (MD 5 mmHg [95%CI 1.43, 8.58, p = 0.006; I 2 = 0%, p = 0.92]). Then, there was no difference regarding the onset of pneumothorax under the two ventilation strategies (RR 1.94 [95%CI 0.54, 6.94, p = 0.31; I 2 = 0%, p = 0.74]). ICU mortality and sedation level were not included into quantitative analysis.

          Conclusion

          This study showed a higher number of ventilator-free days at 28 day and a lower hospital mortality in acute hypoxemic patients treated with APRV than conventional ventilation, without any negative hemodynamic impact or higher risk of barotrauma. However, these results need to be interpreted with caution because of the low-quality evidence supporting them and the moderate heterogeneity found. Other well-designed RCTs need to be conducted to confirm our findings.

          Related collections

          Most cited references22

          • Record: found
          • Abstract: not found
          • Article: not found

          Bias in meta-analysis detected by a simple, graphical test

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

              Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.
                Bookmark

                Author and article information

                Contributors
                andrea.carsetti@ospedaliriuniti.marche.it
                eli.dam86@alice.it
                robertadomizi@gmail.com
                cla.scorcella@alice.it
                simonapantanetti@gmail.com
                falmed@libero.it
                a.donati@univpm.it
                e.adrario@univpm.it
                Journal
                Ann Intensive Care
                Ann Intensive Care
                Annals of Intensive Care
                Springer International Publishing (Cham )
                2110-5820
                4 April 2019
                4 April 2019
                2019
                : 9
                : 44
                Affiliations
                [1 ]ISNI 0000 0004 1759 6306, GRID grid.411490.9, Anesthesia and Intensive Care Unit, , Azienda Ospedaliero Universitaria Ospedali Riuniti, ; Ancona, Italy
                [2 ]ISNI 0000 0001 1017 3210, GRID grid.7010.6, Anesthesia and Intensive Care Unit, , Università Politecnica delle Marche, ; Ancona, Italy
                Author information
                http://orcid.org/0000-0001-6096-6251
                Article
                518
                10.1186/s13613-019-0518-7
                6449410
                30949778
                4afe0a20-ca76-4ba4-b5cb-3b74eae2553b
                © The Author(s) 2019

                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.

                History
                : 17 January 2019
                : 30 March 2019
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Emergency medicine & Trauma
                airway pressure release ventilation,acute respiratory failure,acute respiratory distress syndrome,meta-analysis

                Comments

                Comment on this article

                scite_

                Similar content419

                Cited by19

                Most referenced authors1,513