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Updated: Jun 23, 2026

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Published on: August 4, 2021
Association between urinary hCG trajectories and the risk of miscarriage in women undergoing embryo transfer: a
Jing Wang1,2, Xin Wang1,2, Liming Wang1
1Department of Reproduction, Hebei Maternity Hospital, Shijiazhuang, Hebei, China.
Objective:
To investigate the association between the dynamic trajectories of urinary human chorionic gonadotropin (hCG) and the risk of early miscarriage after embryo transfer.
Methods:
In this prospective cohort study conducted in Hebei Maternity Hospital, 207 women undergoing embryo transfer were enrolled. Starting from the 7th day after transfer, urinary hCG levels were quantitatively measured daily using a latex immunochromatography assay. Early pregnancy development was monitored, with miscarriage as the primary outcome. Latent class trajectory modeling was applied to identify distinct hCG trajectory patterns. Multivariate logistic regression was used to assess the relationship between hCG trajectories and miscarriage risk. The predictive performance of the trajectory model was evaluated using ten-fold cross-validated ROC analysis, decision curve analysis (DCA), and calibration curves.
Results:
Urinary hCG was measured over a period of 7 to 51 days. Three distinct hCG trajectories were identified: a Low-Slow group (15.5%), a Low-Steady group (51.2%), and a High-Steady group (33.3%). Compared with the High-Steady trajectory, the Low-Slow trajectory (aOR = 38.11, 95% CI: 26.51-54.78) and the Low-Steady trajectory (aOR = 1.60, 95% CI: 1.14-2.25) were significantly associated with an increased risk of miscarriage. Model 3 predicted miscarriage with an area under the ROC curve (AUC) of 0.857 (95% CI: 0.835-0.879). DCA indicated limited incremental net benefit, while the calibration curve demonstrated good agreement between predicted probabilities and observed outcomes.
Conclusion:
A Low-Slow increasing or Low-Steady increasing urinary hCG trajectory after embryo transfer is associated with a higher risk of early miscarriage. Early recognition of these abnormal hCG dynamics may facilitate risk stratification and personalized clinical management.

