The HERA (Hyper-response Risk Assessment) Delphi consensus for the management of hyper-responders in in vitro fertilization.

PURPOSE: To provide agreed-upon guidelines on the management of a hyper-responsive patient undergoing ovarian stimulation (OS) METHODS: A literature search was performed regarding the management of hyper-response to OS for assisted reproductive technology. A scientific committee consisting of 4 experts discussed, amended, and selected the final statements. A priori, it was decided that consensus would be reached when ≥66% of the participants agreed, and ≤3 rounds would be used to obtain this consensus. A total of 28/31 experts responded (selected for global coverage), anonymous to each other. RESULTS: A total of 26/28 statements reached consensus. The most relevant are summarized here. The target number of oocytes to be collected in a stimulation cycle for IVF in an anticipated hyper-responder is 15-19 (89.3% consensus). For a potential hyper-responder, it is preferable to achieve a hyper-response and freeze all than aim for a fresh transfer (71.4% consensus). GnRH agonists should be avoided for pituitary suppression in anticipated hyper-responders performing IVF (96.4% consensus). The preferred starting dose in the first IVF stimulation cycle of an anticipated hyper-responder of average weight is 150 IU/day (82.1% consensus). ICoasting in order to decrease the risk of OHSS should not be used (89.7% consensus). Metformin should be added before/during ovarian stimulation to anticipated hyper-responders only if the patient has PCOS and is insulin resistant (82.1% consensus). In the case of a hyper-response, a dopaminergic agent should be used only if hCG will be used as a trigger (including dual/double trigger) with or without a fresh transfer (67.9% consensus). After using a GnRH agonist trigger due to a perceived risk of OHSS, luteal phase rescue with hCG and an attempt of a fresh transfer is discouraged regardless of the number of oocytes collected (72.4% consensus). The choice of the FET protocol is not influenced by the fact that the patient is a hyper-responder (82.8% consensus). In the cases of freeze all due to OHSS risk, a FET cycle can be performed in the immediate first menstrual cycle (92.9% consensus). CONCLUSION: These guidelines for the management of hyper-response can be useful for tailoring patient care and for harmonizing future research.

The HERA (Hyper-response Risk Assessment) Delphi consensus definition of hyper-responders for in-vitro fertilization.

PURPOSE: To provide an agreed upon definition of hyper-response for women undergoing ovarian stimulation (OS)? METHODS: A literature search was performed regarding hyper-response to ovarian stimulation for assisted reproductive technology. A scientific committee consisting of 5 experts discussed, amended, and selected the final statements in the questionnaire for the first round of the Delphi consensus. The questionnaire was distributed to 31 experts, 22 of whom responded (with representation selected for global coverage), each anonymous to the others. A priori, it was decided that consensus would be reached when ≥ 66% of the participants agreed and ≤ 3 rounds would be used to obtain this consensus. RESULTS: 17/18 statements reached consensus. The most relevant are summarized here. (I) Definition of a hyper-response: Collection of ≥ 15 oocytes is characterized as a hyper-response (72.7% agreement). OHSS is not relevant for the definition of hyper-response if the number of collected oocytes is above a threshold (≥ 15) (77.3% agreement). The most important factor in defining a hyper-response during stimulation is the number of follicles ≥ 10 mm in mean diameter (86.4% agreement). (II) Risk factors for hyper-response: AMH values (95.5% agreement), AFC (95.5% agreement), patient's age (77.3% agreement) but not ovarian volume (72.7% agreement). In a patient without previous ovarian stimulation, the most important risk factor for a hyper-response is the antral follicular count (AFC) (68.2% agreement). In a patient without previous ovarian stimulation, when AMH and AFC are discordant, one suggesting a hyper-response and the other not, AFC is the more reliable marker (68.2% agreement). The lowest serum AMH value that would place one at risk for a hyper-response is ≥ 2 ng/ml (14.3 pmol/L) (72.7% agreement). The lowest AFC that would place one at risk for a hyper-response is ≥ 18 (81.8% agreement). Women with polycystic ovarian syndrome (PCOS) as per Rotterdam criteria are at a higher risk of hyper-response than women without PCOS with equivalent follicle counts and gonadotropin doses during ovarian stimulation for IVF (86.4% agreement). No consensus was reached regarding the number of growing follicles ≥ 10 mm that would define a hyper-response. CONCLUSION: The definition of hyper-response and its risk factors can be useful for harmonizing research, improving understanding of the subject, and tailoring patient care.

Zygotic splitting following embryo biopsy: a cohort study of 207 697 single-embryo transfers following IVF treatment.

OBJECTIVE: To evaluate the risk of monozygotic splitting with embryo biopsy during in vitro fertilisation (IVF). DESIGN: A cohort study. SETTING: Anonymised assisted reproductive technology national data from the Human Fertilisation and Embryology Authority, UK. POPULATION: Women undergoing single-embryo transfer (SET) following either pre-implantation genetic testing (PGT) involving embryo biopsy or IVF without PGT. METHODS: Data on women undergoing SET either following PGT and non-PGT IVF treatment in 2000-2016 were analysed to compare the risk of zygotic splitting and monozygotic twining. Logistic regression analysis was performed adjusting for potential confounders. MAIN OUTCOMES: Monozygotic spitting, monozygotic twin birth. RESULTS: Data comprising a total of 207 697 SET cycles (4544 following PGT and 203 153 following non-PGT IVF) were analysed. The live birth rate per embryo transfer was 31.9% (95% confidence interval [CI] 30.5-33.2%) following PGT and 26.9% (95% CI 26.7-27.1%) following non-PGT IVF. The incidence of zygotic splitting following PGT was 2.4% (95% CI 1.7-3.3%) versus 1.5% (95% CI 1.4-1.6%) following non-PGT IVF. There was a significantly higher risk of zygotic splitting with PGT versus non-PGT IVF cycles (odds ratio [OR] 1.64, 95% CI 1.19-2.27). The higher risk of zygotic splitting with PGT cycles remained significant after adjusting for potential confounders (adjusted OR 1.51, 95% CI 1.06-2.15). CONCLUSIONS: The present study demonstrated an increased risk of monozygotic splitting with embryo biopsy. Given the current sparse literature, it is important to accumulate further evidence to validate the findings. TWEETABLE ABSTRACT: A likely increased risk of monozygotic splitting following embryo biopsy.

Micro-Computed tomography (CT) based assessment of dental regenerative therapy in the canine mandible model.

High-resolution 3D bone-tissue structure measurements may provide information critical to the understanding of the bone regeneration processes and to the bone strength assessment. Tissue engineering studies rely on such nondestructive measurements to monitor bone graft regeneration area. In this study, we measured bone yield, fractal dimension and trabecular thickness through micro-CT slices for different grafts and controls. Eight canines underwent surgery to remove a bone volume (defect) in the canine's jaw at a total of 44 different locations. We kept 11 defects empty for control and filled the remaining ones with three regenerative materials; NanoGen (NG), a FDA-approved material (n=11), a novel NanoCalcium Sulfate (NCS) material (n=11) and NCS alginate (NCS+alg) material (n=11). After a minimum of four and eight weeks, the canines were sacrificed and the jaw samples were extracted. We used a custom-built micro-CT system to acquire the data volume and developed software to measure the bone yield, fractal dimension and trabecular thickness. The software used a segmentation algorithm based on histograms derived from volumes of interest indicated by the operator. Using bone yield and fractal dimension as indices we are able to differentiate between the control and regenerative material (p<0.005). Regenerative material NCS showed an average 63.15% bone yield improvement over the control sample, NCS+alg showed 55.55% and NanoGen showed 37.5%. The bone regeneration process and quality of bone were dependent upon the position of defect and time period of healing. This study presents one of the first quantitative comparisons using non-destructive Micro-CT analysis for bone regenerative material in a large animal with a critical defect model. Our results indicate that Micro-CT measurement could be used to monitor in-vivo bone regeneration studies for greater regenerative process understanding.

Adenomyosis and female fertility: a critical review of the evidence.

Adenomyosis is frequent during the evaluation of infertile women. Present evidence suggests that adenomyosis has a negative impact on female fertility. Limited data from uncontrolled studies suggest that treatment of adenomyosis may improve fertility. This review critically appraises the existing evidence to determine the relationship between adenomyosis and female fertility. There is need for large epidemiological studies to substantiate the association between adenomyosis and infertility. Furthermore, if adenomyosis has a harmful impact on fertility there is a need to determine if its treatment improves fertility and the various treatment modalities reported need to be assessed for their effectiveness in randomised trials.

Validity of the in vitro fertilisation league tables: influence of patients' characteristics.

We tested the hypothesis that restricting comparison of the live birth rate following in vitro fertilisation (IVF) treatment in those couples having their first IVF cycle in whom the female is under 35 years of age and has a normal follicle-stimulating hormone level would improve the validity of comparing IVF clinics' success rates. We analysed all cycles performed over a 2-year period in patients who fulfilled these criteria and divided the study population according to the referring primary care trusts: group A (n = 90) were referred from Lambeth, Southwark and Lewisham and group B (n = 134) were referred from Brent and Harrow. There was no significant difference between the two groups with regard to their IVF cycle characteristics. The two groups differed in their ethnicity, cause of infertility, prevalence of uterine fibroids and smoking and alcohol consumption habits. Group A had a significantly lower live birth rate (OR = 0.45, 95% CI 0.21-0.95, P = 0.02) compared with group B. This study confirms the impact of the non-IVF-related patient characteristics on treatment outcome and the poor validity of comparing IVF clinics' success rates based on the sparse data published by national IVF registries.