Prolactin (PRL) is an anterior pituitary hormone which has its principle physiological action in initiation and maintenance of lactation. In human reproduction, pathological hyperprolactinemia most commonly presents as an ovulatory disorder and is often associated with secondary amenorrhea or oligomenorrhea. Galactorrhea, a typical symptom of hyperprolactinemia, occurs in less than half the cases. Out of the causes of hyperprolactinemia, pituitary tumors may be responsible for almost 50% of cases and need to be investigated especially in the absence of history of drug induced hyperprolactinemia. In women with hyperprolactinemic amenorrhea one important consequence of estrogen deficiency is osteoporosis, which deserves specific therapeutic consideration. Problem in diagnosing and treating hyperprolactinemia is the occurrence of the ‘big big molecule of prolactin’ that is biologically inactive (called macroprolactinemia), but detected by the same radioimmunoassay as the biologically active prolactin. This may explain many cases of very high prolactin levels sometimes found in normally ovulating women and do not require any treatment. Dopamine agonist is the mainstay of treatment. However, presence of a pituitary macroadenoma may require surgical or radiological management.

Purpose Sperm quality plays an important role in determining embryo development and intracytoplasmic sperm injection (ICSI) outcome. Selection of competent sperm based on its ability to bind to hyaluronic acid (HA) has been suggested as one of the methods to assess sperm quality. The aim of the present study was to examine whether injection of HA bound sperm helps in improving outcome in patients undergoing ICSI with unexplained infertility having normal semen parameters. Methods Patients with unexplained infertility having normal semen parameters in accordance with WHO 2010 criterion, undergoing their first IVF-ICSI cycle were enrolled during the course of the study.156 patients were prospectively randomized after oocyte retrieval and were assigned to either the ICSI group, where sperm selection for injection was based on visual assessment, or the PICSI group, where sperm were selected based on their ability to bind to HA. Only fresh embryo transfers were included in the analysis. Results There was no difference in the fertilization rates, number of top quality embryos and clinical pregnancy rates between the ICSI and PICSI groups (65.7 % vs 64.7 %; 45.8 % vs 43.6 % and 35 % vs 35.2 % respectively). However, a higher pregnancy loss rate was observed in the ICSI group (25 % vs 12 %; P =0.227) as compared to the PICSI group, but the difference was not statistically significant. Implantation rates were 22.03 % and 18.84 % in the PICSI and ICSI groups respectively. There were 22 (31 %) live births in the PICSI group and 21(26.3 %) live births in the ICSI group. Conclusions Patients with unexplained infertility having normal semen parameters may constitute a patient group which does not benefit from this sperm selection method. A larger study may be necessary to establish a relationship between PICSI and pregnancy loss rate in patients undergoing IVF with unexplained infertility.

OBJECTIVES:(a) To establish the cut-off levels for anti-Mullerian hormone (AMH) in a population of Indian women that would determine poor response. (b) To determine which among the three ie.,: age, follicle stimulating hormone (FSH), or AMH, is the better determinant of ovarian reserve.STUDY DESIGN:Prospective observational study.SETTING:In vitro fertilization (IVF) unit of a tertiary hospital.MATERIALS AND METHODS:The inclusion criterion was all women who presented to the center for in-vitro fertilization/Intracytoplasmic sperm injection (IVF/ICSI). The exclusion criteria were age >45 years, major medical illnesses precluding IVF or pregnancy, FSH more than 20 IU/L, and failure to obtain consent. The interventions including baseline pelvic scan, day 2/3 FSH, luteinizing hormone (LH), estradiol estimations, and AMH measurement on any random day of cycle were done. Subjects underwent IVF according to long agonist or antagonist protocol regimen. Oocyte recovery was correlated with studied variables. The primary outcome measure was the number of oocytes aspirated (OCR). Three categories of ovarian response were defined: poor response, OCR ≤ 3; average response, OCR between 4 and 15; hyperresponse, OCR > 15.RESULTS:Of the 198 patients enrolled, poor, average, and hyperresponse were observed in 23%, 63%, and 14% respectively. Correlation coefficient for AMH with ovarian response was r = 0.591. Area under the curve (AUCs) for poor response for AMH, subject's age, and FSH were 0.768, 0.624, and 0.635, respectively. The discriminatory level of AMH for prediction of absolute poor response was 2 pmoL/l, with 98% specificity and 20% sensitivity.CONCLUSIONS:AMH fares better than age and FSH in predicting the overall ovarian response and poor response, though it cannot be the absolute predictor of non-responder status. A level of 2 pmol/l is discriminatory for poor response.

OBJECTIVE:To study the prevalence of metabolic syndrome (MBS) in Indian women and to see how does it correlate to body mass index (BMI) and polycystic ovarian syndrome (PCOS) in this population.STUDY DESIGN:Prospective cross-sectional observational study.SETTING:Infertility clinic of a tertiary center.MATERIALS AND METHODS:Two hundred women, 120 with PCOs and 80 age-matched controls were enrolled. The prevalence of MBS was studied in the women with and without and was co related to BMI by further subgrouping as team (BMI <23 kg/m3) and obese (BMI >23 kg/m2). The sample size was: team controls-40, obese controls-40, team PCOS-80. Each subject underwent a physical examination and laboratory evaluation for the diagnosis of MBS, which was defined according to the guidelines of National Cholesterol Education Program Adult Treatment Pamel (NCEP ATP III) 2005.INTERVENTION:None.MAIN OUTCOME MEASURES:Main Outcome Measures: Subjects with and without PCOs were compared with each other for the prevalence of MBS, and similarly team subjects were compared with obese subjects. Receiver operator characteristic (ROC) curves were obtained for both the PCOS and non PCOS population separately, co-relating the prevalence of MBS with BMI. These ROC curves were used to establish the cut off values of BMI, which could best predict the risk of MBS.RESULTS:The prevalence of MBS was significantly higher in the women with PCOS, as compared to age-matched controls. Similarly, when BMI was considered, MBS was more prevalent in overweight subjects than in lean subjects with or without PCOS. In subgroup analysis, the presence of PCOS had a lesser impact on the prevalence of MBS as compared to non-PCOS controls with higher BMI. The relative risk of MBS increased as follows: lean controls-1, lean PCOS-2.66, obese controls-5.33, and obese PCOS-6.5. The most appropriate cut-off level of BMI for predicting the risk of MBS in Indian women without PCOS seems to be 23 kg/m2, whereas, with PCOS, it was 22.5 kg/m2.CONCLUSION:MBS is more prevalent in women with PCOS. However, obesity is an independent and stronger risk factor for developing MBS. To reduce the risk of MBS and its related long-term health consequences, lifestyle modification is advisable above BMI of 23 kg/m2 in the normal population and 22.5 kg/m2 in women with PCOS.

AIMS:To study the prevalence of clinical manifestations in obese and lean polycystic ovarian syndrome (PCOS) women and their health hazards.SETTINGS AND DESIGN:This prospective study was carried out in a tertiary care infertility clinic from 1.7.2005 till 31.12.2007.MATERIALS AND METHODS:These women were diagnosed to have PCOS by the European Society of Human Reproduction and Embryology and the American Society of Reproductive Medicine, Rotterdam 2003 criteria. They were further divided into two groups according to their body mass index (BMI): Group A (n = 300), overweight and obese with BMI >23 and Group B (n = 150), normal weight and lean with BMI ≤23.STASTICAL ANALYSIS AND RESULTS:The prevalence of menstrual irregularities [79.2% vs. 44%, P = 0.000, 95% confidence interval (CI) = 0.26–0.44)] and clinical hyperandrogenism (74.2% vs. 50.6%, P = 0.000, 95% CI=0.14–0.32) was signifi cantly higher in the obese group, whereas android central obesity (waist to hip ratio >0.85) was similar in both groups, irrespective of body weight (47.7% vs. 38%, P = 0.056, 95% CI=0.06 to +0.18). Comparative data of various health manifestations in lean vs. obese women with POCS [Table 4]. Of the health risk manifestations, hypertension occurred in both groups with a similar frequency (41% vs. 35.5%, P = 0.261, 95% CI=0.03 to +0.15). Group A showed an increased prevalence of IGT (25% vs. 10%, P = 0.000, 95% CI= 0.13–0.29) and type two diabetes mellitus (11.7% vs. 6%, P = 0.000, 95% CI= 0.13–0.29) as compared with group B. endometrial hyperplasia (EH) also showed an increase prevalence in Group A compared with Group B (5.6% vs. 2%, P = 0.055, 95% CI= 0.01–0.08), although not statistically significant.CONCLUSION:PCOS emerges as a clinically heterogeneous condition with increased prevalence of health risks such as hypertension, diabetes and EH. Of these, diabetes and EH appear to be more prevalent in the obese, putting them at a greater risk of morbid problems at a much younger age than the lean ones.

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The markers prescribed by EAA alone are not suitable for the diagnosis of Y chromosome microdeletions in infertile males. The protocol for identification of Y chromosome microdeletions in cases of nonobstructive azoospermia/severe oligospermia would have to include a different set of STS markers.

This is the largest and most diversely represented survey of specific IVF practices addressing oocyte maturation triggers, oocyte retrieval and embryo transfers. Several uniform practice patterns were identified that can be correlated with evidence-based medicine; however, we identified multiple variable practice patterns which is likely the result of the absence of definitive evidence to guide IVF practitioners. The results of this survey allow IVF providers to compare their specific practice patterns with those of a global diverse population of IVF providers.