Nomogram model to predict the risk of moderate to severe ovarian hyperstimulation syndrome of long protocol group in fresh cycle

To explore the risk factors of moderate to severe ovarian hyperstimulation syndrome (Ovarian hyperstimulation syndrome, OHSS) in patients using the early-follicular phase long-acting gonadotropin-releasing hormone agonist long protocol (EFLL) group in fresh cycles, and to establish a nomogram model to predict the risk of moderate to severe OHSS. We retrospectively analyzed clinical data from 4,204 patients who receiving in vitro fertilization/intracytoplasmic sperm injection and embryo transfer (IVF/ICSI-ET) at the Reproductive Medicine Department of the Second Affiliated Hospital of Zhengzhou University from January 2015 to August 2024. A total of 4204 cases using EFLL protocol were included. The clinical cases were randomly divided into a modeling group (2,942 cases) and a verification group (1,262 cases) at a ratio of 7:3. Logistic regression analysis was used to identify the independent risk factors associated with the occurrence of moderate to severe OHSS in fresh cycles, Based on the selected independent risk factors and correlated regression coefficients, we established a nomogram model to predict the probability of moderate to severe OHSS in this patients, and the predictive accuracy of the model was measured using the area under the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Univariate and multivariate logistic regression analyses showed that Antal follicle count (AFC) (OR, 1.04; 95%CI, 1.02-1.07; P = 0.002), estrogen levels on the day of hCG injection (OR, 1.01; 95%CI, 1.01-1.01; P<0.01), progesterone levels on the day of hCG injection (OR, 1.18; 95%CI, 1.04-1.34; P = 0.011),, whether the patient had a hypothyroidism (OR, 3.62; 95%CI, 2.10-6.23; P < 0.001), and infertility type (OR, 0.59; 95%CI, 0.35-0.99; P = 0.048) are the independent risk factors for the occurrence of moderate to severe OHSS in fresh cycles. The ROC curve (AUC) being 0.83 (95% CI: 0.78-0.88) for the modeling group and 0.84 (95% CI: 0.78-0.90) for the validation group. The calibration curve and decision curve demonstrated good consistency between the predicted rates of moderate to severe OHSS and the actual incidence. AFC, estrogen levels on the day of hCG injection, progesterone levels on the day of hCG injection, whether the patient had a hypothyroidism, and infertility type are the independent risk factors for moderate to moderate to severe OHSS in fresh cycles. The established nomogram model has proven to be a novel tool that can intuitively predict the incidence of moderate to severe OHSS in the patients that receiving EFLL protocol in fresh cycles, and this nomogram model developed in this study showed better net benefit, have a good clinical applicability for decision-making and could help the clinician to set up a better clinical management strategies for conducting a precise personal therapy.

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Publication Details

Journal
Scientific Reports
Published
2025-03-17
DOI
https://doi.org/10.1038/s41598-025-94049-3
Citations
1
Primary Topic
Ovarian function and disorders
Type
article
Field-Weighted Citation Impact
1.70
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article

Nomogram model to predict the risk of moderate to severe ovarian hyperstimulation syndrome of long protocol group in fresh cycle

Qian Dou, Huanxin Liu, Pengfen Li, Xujing Geng et al.
1 citations
Scientific Reports
Ovarian function and disorders
1.70
article

Nomogram model to predict the risk of moderate to severe ovarian hyperstimulation syndrome of long protocol group in fresh cycle

Qian Dou, Huanxin Liu, Pengfen Li, Xujing Geng, Huihui Deng, Dan Zhang, Peipei Guo, Yungai Xiang
article en
1 citations

Abstract

To explore the risk factors of moderate to severe ovarian hyperstimulation syndrome (Ovarian hyperstimulation syndrome, OHSS) in patients using the early-follicular phase long-acting gonadotropin-releasing hormone agonist long protocol (EFLL) group in fresh cycles, and to establish a nomogram model to predict the risk of moderate to severe OHSS. We retrospectively analyzed clinical data from 4,204 patients who receiving in vitro fertilization/intracytoplasmic sperm injection and embryo transfer (IVF/ICSI-ET) at the Reproductive Medicine Department of the Second Affiliated Hospital of Zhengzhou University from January 2015 to August 2024. A total of 4204 cases using EFLL protocol were included. The clinical cases were randomly divided into a modeling group (2,942 cases) and a verification group (1,262 cases) at a ratio of 7:3. Logistic regression analysis was used to identify the independent risk factors associated with the occurrence of moderate to severe OHSS in fresh cycles, Based on the selected independent risk factors and correlated regression coefficients, we established a nomogram model to predict the probability of moderate to severe OHSS in this patients, and the predictive accuracy of the model was measured using the area under the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Univariate and multivariate logistic regression analyses showed that Antal follicle count (AFC) (OR, 1.04; 95%CI, 1.02-1.07; P = 0.002), estrogen levels on the day of hCG injection (OR, 1.01; 95%CI, 1.01-1.01; P<0.01), progesterone levels on the day of hCG injection (OR, 1.18; 95%CI, 1.04-1.34; P = 0.011),, whether the patient had a hypothyroidism (OR, 3.62; 95%CI, 2.10-6.23; P < 0.001), and infertility type (OR, 0.59; 95%CI, 0.35-0.99; P = 0.048) are the independent risk factors for the occurrence of moderate to severe OHSS in fresh cycles. The ROC curve (AUC) being 0.83 (95% CI: 0.78-0.88) for the modeling group and 0.84 (95% CI: 0.78-0.90) for the validation group. The calibration curve and decision curve demonstrated good consistency between the predicted rates of moderate to severe OHSS and the actual incidence. AFC, estrogen levels on the day of hCG injection, progesterone levels on the day of hCG injection, whether the patient had a hypothyroidism, and infertility type are the independent risk factors for moderate to moderate to severe OHSS in fresh cycles. The established nomogram model has proven to be a novel tool that can intuitively predict the incidence of moderate to severe OHSS in the patients that receiving EFLL protocol in fresh cycles, and this nomogram model developed in this study showed better net benefit, have a good clinical applicability for decision-making and could help the clinician to set up a better clinical management strategies for conducting a precise personal therapy.

Scientific ReportsVol. 15(1)
Second Affiliated Hospital of Zhengzhou University (CN)
Zero hunger
Openalex Percentile: Top 19%
Ovarian function and disorders
1.70
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