不明原因不孕症
不育
控制性卵巢过度刺激
医学
宫内授精
妇科
随机对照试验
产科
自发受孕
怀孕
外科
生物
遗传学
作者
Nicole Au,Qian Feng,Laxmi Shingshetty,Abha Maheshwari,Ben W. Mol
标识
DOI:10.1016/j.fertnstert.2024.02.044
摘要
Abstract
Importance
The diagnosis of unexplained infertility presents a dilemma as it signifies both uncertainty about the cause of infertility and the potential for natural conception. Immediate treatment of all would result in overtreatment. Prediction models estimating the likelihood of natural conception and subsequent live birth can guide treatment decisions. Objective
To evaluate if in couples with unexplained infertility, prediction models are effective in guiding treatment decisions. Evidence review
This review examines 25 studies that assess prediction models for natural conception in couples with unexplained infertility in terms of derivation, validation, and impact analysis. Findings
The largest prediction models have been integrated in the synthesis models of Hunault, that includes female age, infertility duration, having been pregnant before and motile sperm percentage. Despite its limited discriminative capacity, this model demonstrates excellent calibration. Importantly, the impact of the Hunault model has been evaluated in randomized clinical trials, and shows that in couples with unexplained infertility and 12-month natural conception chances exceeding 30%, immediate treatment with intra-uterine insemination (IUI) and controlled ovarian hyperstimulation (COH) is not better than expectant management for 6 months. Below the threshold of 30%, treatment with IUI is superior over expectant management, but immediate IVF was not better than IUI. Conclusion
In couples with unexplained infertility and a good prognosis for natural conception, treatment can be delayed, while in couples with a poor prognosis, immediate treatment (with IUI-COH) is warranted. Relevance
These data indicate that in couples with unexplained infertility, integration of prediction models into clinical decision-making can optimize treatment selection and maximize fertility outcomes while limiting unnecessary treatment.
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