5 research outputs found

    Does ovarian hyperstimulation in intrauterine insemination for cervical factor subfertility improve pregnancy rates?

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    Background: Intrauterine insemination (IUI) can be performed with or without controlled ovarian hyperstimulation (COH). Studies in which the additional benefit of COH on IUI for cervical factor subfertility is assessed are lacking. We assessed whether COH in IUI improved pregnancy rates in cervical factor subfertility. Methods: We performed a historical cohort study among couples with cervical factor subfertility, treated with IUI. A cervical factor was diagnosed by a well-timed, non-progressive post-coital test with normal semen parameters. We compared ongoing pregnancy rate per cycle in groups treated with IUI with or without COH. We tabulated ongoing pregnancy rates per cycle number and compared the effectiveness of COH by stratified univariable analysis. Results: We included 181 couples who underwent 330 cycles without COH and 417 cycles with COH. Ongoing pregnancy rates in IUI cycles without and with COH were 9.7% and 12.7%, respectively (odds ratio 1.4; 95% confidence interval 0.85-2.2). The pregnancy rates in IUI without COH in cycles 1, 2, 3 and 4 were 14%, 11%, 6% and 15%, respectively. For IUI with COH, these rates were 17%, 15%, 14% and 16%, respectively. Conclusions: Although our data indicate that COH improves the pregnancy rate over IUI without COH, IUI without COH generates acceptable pregnancy rates in couples with cervical factor subfertility. Since IUI without COH bears no increased risk for multiple pregnancy, this treatment should be seriously considered in couples with cervical factor subfertility

    Prediction Models in Reproductive Medicine

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    In dit proefschrift wordt beschreven in hoeverre het op dit moment mogelijk is om bij paren met onvervulde kinderwens de kans te voorspellen om zwanger te worden zonder fertiliteitsbehandeling. De klinische relevantie en de voorspellende waarde van een aantal factoren, die onderdeel zijn van het oriënterend fertiliteitsonderzoek (OFO), werden geëvalueerd in een theoretische en klinische setting. In de periode van januari 2002 tot en met 1 februari 2004 werden in 38 Nederlandse ziekenhuizen 7 860 subfertiele paren verzameld in het Oriënterend Fertiliteits Onderzoek project (OFO-project, internationaal ook bekend als the Collaborative Effort for Clinical Evaluation in Reproductive Medicine group (CECERM)). In de inleiding van dit proefschrift beschrijven wij de opbouw van het standaard oriënterend fertiliteitsonderzoek. Verder bespreken wij de meest relevante predictiemodellen voor het voorspellen van spontane zwangerschap. Hoofdstuk 2 richt zich op de vraag wat het beste moment is om het OFO in gang te zetten. In de hoofdstukken 3 en 4 evalueren wij in hoeverre gynaecologen in staat zijn om zelf bij subfertiele paren de kans op een zwangerschap te voorspellen. In hoofdstuk 5 valideren we het predictiemodel voor spontane zwangerschap van Hunault. In de hoofdstukken 6 tot en met 10 worden de klinische relevantie en prognostische waarde beschreven van bestaande en nieuwe onderdelen van het OFO; de obstetrische voorgeschiedenis, het zaadonderzoek, de samenlevingstest, ook wel de postcoitumtest (PCT) genoemd, obesitas en het basaal follikel stimulerend hormoon (FSH)

    Should the post-coital test (PCT) be part of the routine fertility work-up?

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    BACKGROUND: This study aimed to determine whether medical history and semen analysis can predict the result of the post-coital test (PCT). METHODS: A previously reported data set of Dutch patients collected between 1985 and 1993 was used. Our study was limited to just patients with an ovulatory cycle. Data were complete for medical history, semen analysis and PCT. We performed logistic regression analysis to evaluate whether these factors could predict the result of the PCT (PCT model). Furthermore, we evaluated the additional contribution of the PCT in the prediction of treatment-independent pregnancy (pregnancy model). RESULTS: Thirty-four percent (179 out of 522) had an abnormal PCT. The PCT model contained previous pregnancy [odds ratio (OR) 2.1; 95% confidence interval (CI) 1.3-3.5], semen volume (OR 0.88; 95% CI 0.77-0.99), sperm concentration (OR 0.96; 95% CI 0.94-0.97), sperm motility (OR 0.97; 95% CI 0.96-0.98) and sperm morphology (OR 2.7; 95% CI 1.2-6.8). The area under the ROC curve of the model was 0.81. In the pregnancy model, the result of the actual PCT could be replaced by the predicted result of the PCT model in about half of the couples, without compromising its predictive capacity. CONCLUSION: The medical history and semen analysis can predict the result of the PCT in approximately 50% of the subfertile couples with a regular cycle, without compromising its potential to predict pregnancy

    Pregnancy is predictable: A large-scale prospective external validation of the prediction of spontaneous pregnancy in subfertile couples

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    Background: Prediction models for spontaneous pregnancy may be useful tools to select subfertile couples that have good fertility prospects and should therefore be counselled for expectant management. We assessed the accuracy of a recently published prediction model for spontaneous pregnancy in a large prospective validation study. Methods: In 38 centres, we studied a consecutive cohort of subfertile couples, referred for an infertility work-up. Patients had a regular menstrual cycle, patent tubes and a total motile sperm count (TMC) >3 × 106. After the infertility work-up had been completed, we used a prediction model to calculate the chance of a spontaneous ongoing pregnancy (www.freya.nl/probability.php). The primary end-point was time until the occurrence of a spontaneous ongoing pregnancy within 1 year. The performance of the pregnancy prediction model was assessed with calibration, which is the comparison of predicted and observed ongoing pregnancy rates for groups of patients and discrimination. Results: We included 3021 couples of whom 543 (18%) had a spontaneous ongoing pregnancy, 57 (2%) a non-successful pregnancy, 1316 (44%) started treatment, 825 (27%) neither started treatment nor became pregnant and 280 (9%) were lost to follow-up. Calibration of the prediction model was almost perfect. In the 977 couples (32%) with a calculated probability between 30 and 40%, the observed cumulative pregnancy rate at 12 months was 30%, and in 611 couples (20%) with a probability of ≥40%, this was 46%. The discriminative capacity was similar to the one in which the model was developed (c-statistic 0.59). Conclusions: As the chance of a spontaneous ongoing pregnancy among subfertile couples can be accurately calculated, this prediction model can be used as an essential tool for clinical decision-making and in counselling patients. The use of the prediction model may help to prevent unnecessary treatment

    Identifying subfertile ovulatory women for timely tubal patency testing: A clinical decision rule based on medical history

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    Background: The aim of tubal testing is to identify women with bilateral tubal pathology in a timely manner, so they can be treated with IVF or tubal surgery. At present, it is unclear for which women early tubal testing is indicated, and in whom it can be deferred. Methods: Data on 3716 women who underwent tubal patency testing as a part of their routine fertility workup were used to relate elements in their medical history to the presence of tubal pathology. With multivariable logistic regression, we constructed two diagnostic models. One in which tubal disease was defined as occlusion and/or severe adhesions of at least one tube, whereas in a second model, tubal disease was defined as the presence of bilateral abnormalities. Results: Both models discriminated moderately well between women with and women without tubal disease with an area under the receiver-operating characteristic curve (AUC) of 0.65 (95% CI: 0.63-0.68) for any tubal pathology and 0.68 (95% CI: 0.65-0.71) for bilateral tubal pathology, respectively. However, the models could make an almost perfect distinction between women with a high and a low probability of tubal pathology. A decision rule in the form of a simple diagnostic score chart was developed for application of the models in clinical practice. Conclusions: In conclusion, the present study provides two easy to use decision rules that can accurately express a woman's probability of (severe) tubal pathology at the couple's first consultation. They could be used to select women for tubal testing more efficiently
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