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      The POSEIDON Criteria and Its Measure of Success Through the Eyes of Clinicians and Embryologists

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          Abstract

          This article represents a viewpoint on the POSEIDON criteria by a group of clinicians and embryologists. Its primary objective is to contextualize the Poseidon criteria and their metric of success for the relevant Frontiers Research Topic “POSEIDON's Stratification of Low Prognosis Patients in ART: The WHY, the WHAT, and the HOW”. “Low prognosis” relates with reduced oocyte number, which can be associated with low or sometimes a normal ovarian reserve and is aggravated by advanced female age. These aspects will ultimately affect the number of embryos generated and consequently, the cumulative live birth rate. The novel system relies on female age, ovarian reserve markers, ovarian sensitivity to exogenous gonadotropin, and the number of oocytes retrieved, which will both identify the patients with low prognosis and stratify such patients into one of four groups of women with “expected” or “unexpected” impaired ovarian response to exogenous gonadotropin stimulation. Furthermore, the POSEIDON group introduced a new measure of clinical success in ART, namely, the ability to retrieve the number of oocytes needed to obtain at least one euploid blastocyst for transfer in each patient. Using the POSEIDON criteria, the clinician can firstly identify and classify patients who have low prognosis in ART, and secondly, aim at designing an individualized treatment plan to maximize the chances of achieving the POSEIDON measure of success in each of the four low prognosis groups. The novel POSEIDON classification system is anticipated to improve counseling and management of low prognosis patients undergoing ART, with an expected positive effect on reproductive success and a reduction in the time to live birth.

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          Most cited references46

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          Defining and classifying clinical indicators for quality improvement.

          J Mainz (2003)
          This paper provides a brief review of definitions, characteristics, and categories of clinical indicators for quality improvement in health care. Clinical indicators assess particular health structures, processes, and outcomes. They can be rate- or mean-based, providing a quantitative basis for quality improvement, or sentinel, identifying incidents of care that trigger further investigation. They can assess aspects of the structure, process, or outcome of health care. Furthermore, indicators can be generic measures that are relevant for most patients or disease-specific, expressing the quality of care for patients with specific diagnoses. Monitoring health care quality is impossible without the use of clinical indicators. They create the basis for quality improvement and prioritization in the health care system. To ensure that reliable and valid clinical indicators are used, they must be designed, defined, and implemented with scientific rigour.
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            Association between the number of eggs and live birth in IVF treatment: an analysis of 400 135 treatment cycles.

            While live birth is the principal clinical outcome following in vitro fertilization (IVF) treatment, the number of eggs retrieved following ovarian stimulation is often used as a surrogate outcome in clinical practice and research. The aim of this study was to explore the association between egg number and live birth following IVF treatment and identify the number of eggs that would optimize the IVF outcome. Anonymized data on all IVF cycles performed in the UK from April 1991 to June 2008 were obtained from the Human Fertilization and Embryology Authority (HFEA). We analysed data from 400 135 IVF cycles. A logistic model was fitted to predict live birth using fractional polynomials to handle the number of eggs as a continuous independent variable. The prediction model, which was validated on a separate HFEA data set, allowed the estimation of the probability of live birth for a given number of eggs, stratified by age group. We produced a nomogram to predict the live birth rate (LBR) following IVF based on the number of eggs and the age of the female. The median number of eggs retrieved per cycle was 9 [inter-quartile range (IQR) 6-13]. The overall LBR was 21.3% per fresh IVF cycle. There was a strong association between the number of eggs and LBR; LBR rose with an increasing number of eggs up to ∼15, plateaued between 15 and 20 eggs and steadily declined beyond 20 eggs. During 2006-2007, the predicted LBR for women with 15 eggs retrieved in age groups 18-34, 35-37, 38-39 and 40 years and over was 40, 36, 27 and 16%, respectively. There was a steady increase in the LBR per egg retrieved over time since 1991. The relationship between the number of eggs and live birth, across all female age groups, suggests that the number of eggs in IVF is a robust surrogate outcome for clinical success. The results showed a non-linear relationship between the number of eggs and LBR following IVF treatment. The number of eggs to maximize the LBR is ∼15.
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              Fresh versus elective frozen embryo transfer in IVF/ICSI cycles: a systematic review and meta-analysis of reproductive outcomes

              Elective freezing of all good quality embryos and transfer in subsequent cycles, i.e. elective frozen embryo transfer (eFET), has recently increased significantly with the introduction of the GnRH agonist trigger protocol and improvements in cryo-techniques. The ongoing discussion focuses on whether eFET should be offered to the overall IVF population or only to specific subsets of patients. Until recently, the clinical usage of eFET was supported by only a few randomized controlled trials (RCT) and meta-analyses, suggesting that the eFET not only reduced ovarian hyperstimulation syndrome (OHSS), but also improved reproductive outcomes. However, the evidence is not unequivocal, and recent RCTs challenge the use of eFET for the general IVF population.
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                Author and article information

                Contributors
                Journal
                Front Endocrinol (Lausanne)
                Front Endocrinol (Lausanne)
                Front. Endocrinol.
                Frontiers in Endocrinology
                Frontiers Media S.A.
                1664-2392
                20 November 2019
                2019
                : 10
                : 814
                Affiliations
                [1] 1ANDROFERT, Andrology and Human Reproduction Clinic , Campinas, Brazil
                [2] 2Department of Neuroscience, Reproductive Science and Odontostomatology, University of Naples Federico II , Naples, Italy
                [3] 3Fertility Clinic Skive, Skive Regional Hospital , Skive, Denmark
                [4] 4Faculty of Health, Aarhus University , Aarhus, Denmark
                [5] 5Fertility Center Hamburg , Hamburg, Germany
                [6] 6Laboratory of Reproductive Biology, Faculty of Health and Medical Sciences, University Hospital of Copenhagen , Copenhagen, Denmark
                [7] 7Center for Gynecology, Endocrinology, and Reproductive Medicine , Ulm, Germany
                [8] 8Department of Gynaecology, Jena-University Hospital-Friedrich, Schiller University , Jena, Germany
                [9] 9Faculty of Life Sciences and Medicine, King's College London , London, United Kingdom
                [10] 10Dexeus University Hospital , Barcelona, Spain
                [11] 11Instituto Valenciano de Infertilidad , Rome, Italy
                [12] 12Service de Médecine de la Reproduction et Préservation de la Fertilité, Hôpital Antoine Béclère , Clamart, France
                [13] 13Anatolia IVF , Ankara, Turkey
                [14] 14ORIGEN, Center for Reproductive Medicine , Rio de Janeiro, Brazil
                [15] 15Department of Obstetrics and Gynecology, University of Medicine and Pharmacy , Ho Chi Minh City, Vietnam
                [16] 16IVFMD, My Duc Hospital , Ho Chi Minh City, Vietnam
                [17] 17Nova IVI Fertility , Ahmedabad, India
                [18] 18GENERA, Center for Reproductive Medicine , Rome, Italy
                Author notes

                Edited by: William Colin Duncan, University of Edinburgh, United Kingdom

                Reviewed by: Paolo Emanuele Levi-Setti, Humanitas Clinical and Research Center, Milan University, Italy; Richard Ivell, University of Nottingham, United Kingdom

                *Correspondence: Sandro C. Esteves s.esteves@ 123456androfert.com.br

                This article was submitted to Reproduction, a section of the journal Frontiers in Endocrinology

                †ORCID: Sandro C. Esteves orcid.org/0000-0002-1313-9680

                Article
                10.3389/fendo.2019.00814
                6880663
                31824427
                2f700d9d-656b-403d-bc46-3c3a8d934a65
                Copyright © 2019 Esteves, Alviggi, Humaidan, Fischer, Andersen, Conforti, Bühler, Sunkara, Polyzos, Galliano, Grynberg, Yarali, Özbek, Roque, Vuong, Banker, Rienzi, Vaiarelli, Cimadomo and Ubaldi.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 08 June 2019
                : 06 November 2019
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 56, Pages: 8, Words: 6968
                Categories
                Endocrinology
                Perspective

                Endocrinology & Diabetes
                poseidon criteria,ovarian stimulation,low prognosis,poor ovarian response,oocyte,blastocyst,assisted reproductive technology,art calculator

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