Polycystic ovary syndrome (PCOS) is the most common cause of anovulatory infertility. Absent, impaired, or rare ovulation induces progesterone deficiency in the luteal phase, which is a critical problem in PCOS. A usual pattern of progesterone administration from a fixed and arbitrary pre-determined day of a menstrual cycle may preserve infertility but can easily be avoided. We present the case of a 29-year-old infertile woman who had been ineffectively treated for over two years. We introduced a line of therapy that was suited to her individual menstrual cycle by implementing biomarker recording. Supplementation based on a standardized observation of the basal body temperature (BBT) and cervical mucus stopped the vicious circle of absent ovulation and hyperandrogenism, restoring regular bleeding, ovulation cycles, and fertility. The implementation of a reliable fertility awareness method (FAM), accompanied by a standardized teaching methodology and periodic review of the observations recorded by the patient, validated through an ultrasound examination and plasma gonadotropins, estrogens, and progesterone concentrations, is key to achieving therapeutic success. The presented case is an example of a clinical vignette for many patients who have successfully managed to improve their fertility and pregnancy outcomes by applying the principles of a personalized treatment approach together with gestagens by recording their fertility biomarkers.

Premenstrual dysphoric disorder is a female affective disorder that is defined by mood symptoms. The condition is linked to unstable progesterone concentrations. Progestin supplementation is given in cases of threatened or recurrent miscarriage and for luteal phase support. Progesterone is essential for implantation, immune tolerance, and modulation of uterine contractility. For a long time, the administration of progestins was associated with an unfavorable impact on mood, leading to negative affect, and, therefore, was contraindicated in existing mood disorders. Establishing the role of the natural progesterone derivative allopregnanolone in advances in the treatment of postpartum depression has shed new light on the general pathophysiology of mood disorders. Allopregnanolone directly interacts with gamma-aminobutyric acid type A (GABA-A) receptors even at nanomolar concentrations and induces significant anti-depressant, anti-stress, sedative, and anxiolytic effects. Postpartum depression is caused by a rapid drop in hormones and can be instantly reversed by the administration of allopregnanolone. Premenstrual dysphoric disorder can also be considered to result from insufficient neuroactive steroid action due to low progesterone derivative concentration, unstable hormone levels, or decreased receptor sensitivity. The decrease in progesterone levels in perimenopause is also associated with affective symptoms and an exacerbation of some psychosomatic syndromes. Bioidentical progesterone supplementation encounters several obstacles, including limited absorption, first-pass effect, and rapid metabolism. Hence, non-bioidentical progestins with better bioavailability were widely applied. The paradoxical, unfavorable effect of progestins on mood can be explained by the fact that progestins suppress ovulation and disturb the endocrine function of the ovary in the luteal phase. Moreover, their distinct chemical structure prevents their metabolism to neuroactive, mood-improving derivatives. A new understanding of progesterone-related mood disorders can translate the study results from case series and observational studies to cohort studies, clinical trials, and novel, effective treatment protocols being developed.

This Guideline presents current management strategies which, in justified cases and after detailed analysis of a given clinical situation, may be modified and altered, which in turn might aid its future modification and update".

Virtual poster abstracts Methods: We analysed data of an individual participant data (IPD, PROSPERO database ID CRD42017072136). We developed and compared six prediction models, using undichotomised continuous information from three studies and 3,042 women. Each subsequent prediction model included a new variable. The final model included eight variables: maternal age, parity, body mass index (BMI), gestational age at ultrasound test, estimated fetal weight (EFW), umbilical artery pulsatility index (UA PI), middle cerebral artery (MCA) PI and mean uterine artery (mUtA) PI. The primary outcome was a composite adverse perinatal outcome. We applied these models in the general population, and performed planned subgroup analyses according to gestational age (GA) at delivery, birth weight (BW) centile and estimated fetal weight (EFW) centile. Discriminative capacity was expressed using receiver-operating characteristics (ROC) curve (AUC). Results: In the general population, the ROC-curve was similar between the six different models (AUC range 0.60-0.64). In pre-term and small-for-gestational age (SGA) cases, the discriminative ability of a model with maternal and fetal characteristics improved significantly with the addition of UA PI(GA<37 weeks: AUC = 0.06, BW

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