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      The reproductive success of bovine sperm after sex-sorting: a meta-analysis

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          Abstract

          In the three decades since its inception, the sex-sorting technology has progressed significantly. However, field studies report conflicting findings regarding reproductive outcomes. Therefore, we conducted this meta-analysis of all trials published between 1999 and 2021. Non-return rates after 24 or 60 d (NRR 24/60), pregnancy, calving, abortion, and stillbirth rates were compared after AI with sex-sorted vs non-sorted sperm. Additionally, the impact of recent developments in the sex-sorting technology was assessed. Of 860 studies found, 45 studies (72 trials) provided extractable data and were included. Overall, the results of this meta-analysis provided evidence that the NRR 24/60 was diminished by 13%, pregnancy rates were reduced by 23% (25% cows, 21% heifers) and calving rates were reduced by 24% when using sex-sorted sperm. Enhancing the dosage to 4 million sex-sorted sperm/straw (including recent improvements, high vs low dose) as well as using fresh sex-sorted sperm (sorted vs non-sorted) increased pregnancy rate ratios by 7 percentage points. The refinement of the sex-sorting technology after 2015 resulted in a lowered reduction of pregnancy and calving rate of 19% and 23%, respectively. Whereas abortion rates were similar, the stillbirth of male calves was increased by 6.3%.

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

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            Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis.

            Asymmetry in funnel plots may indicate publication bias in meta-analysis, but the shape of the plot in the absence of bias depends on the choice of axes. We evaluated standard error, precision (inverse of standard error), variance, inverse of variance, sample size and log sample size (vertical axis) and log odds ratio, log risk ratio and risk difference (horizontal axis). Standard error is likely to be the best choice for the vertical axis: the expected shape in the absence of bias corresponds to a symmetrical funnel, straight lines to indicate 95% confidence intervals can be included and the plot emphasises smaller studies which are more prone to bias. Precision or inverse of variance is useful when comparing meta-analyses of small trials with subsequent large trials. The use of sample size or log sample size is problematic because the expected shape of the plot in the absence of bias is unpredictable. We found similar evidence for asymmetry and between trial variation in a sample of 78 published meta-analyses whether odds ratios or risk ratios were used on the horizontal axis. Different conclusions were reached for risk differences and this was related to increased between-trial variation. We conclude that funnel plots of meta-analyses should generally use standard error as the measure of study size and ratio measures of treatment effect.
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              Interpretation of random effects meta-analyses

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                Author and article information

                Contributors
                sabine.koelle@ucd.ie
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                30 August 2021
                30 August 2021
                2021
                : 11
                : 17366
                Affiliations
                [1 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, School of Veterinary Medicine, Institute of Veterinary Anatomy, Histology and Embryology, , LMU Munich, ; Munich, Germany
                [2 ]GRID grid.7886.1, ISNI 0000 0001 0768 2743, School of Medicine, Health Sciences Centre, , University College Dublin (UCD), ; Dublin, Ireland
                Article
                96834
                10.1038/s41598-021-96834-2
                8405645
                34462506
                4e539585-1085-41b9-9384-04d51834a0be
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 March 2021
                : 9 August 2021
                Funding
                Funded by: Department of Agriculture, Food, and the Marine, Ireland
                Award ID: 48753
                Award ID: 48753
                Award ID: 48753
                Award Recipient :
                Categories
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                Custom metadata
                © The Author(s) 2021

                Uncategorized
                biotechnology,developmental biology
                Uncategorized
                biotechnology, developmental biology

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