Effect and Relationship of Seasons on the High Risk of Ovarian Hyperstimulation Syndrome After Oocyte Retrieval in Patients With Polycystic Ovary Syndrome

Optimized personalized management approach for moderate/severe OHSS: development and prospective validation of an OHSS risk assessment index

STUDY QUESTION

Can a simplified ovarian hyperstimulation syndrome (OHSS) risk assessment index be developed and validated with sufficient discrimination of moderate/severe OHSS from those without OHSS?

SUMMARY ANSWER

This easy-to-use OHSS risk assessment index shows good discriminative power and high calibration accuracy in internal and external validation cohorts.

WHAT IS KNOWN ALREADY

An early alert and risk stratification is critical to prevent the occurrence of OHSS. We have previously developed a multi-stage smartphone app-based prediction model to evaluate the risk of OHSS, but app use might not be so convenient in many primary institutions. A simplified OHSS risk assessment index has been required.

STUDY DESIGN, SIZE, DURATION

This training and internal validation of an OHSS risk assessment index used retrospective cohort data from January 2016 to December 2020. External validation was performed with a prospective cohort database from January 2021 to May 2022. There were 15 066 cycles in the training cohort, 6502 cycles in the internal validation cohort, and 8097 cycles in the external validation cohort.

PARTICIPANTS/MATERIALS, SETTING, METHODS

This study was performed in the reproductive medicine center of a tertiary hospital. Infertile women who underwent ovarian stimulation were included. Data were extracted from the local database with detailed medical records. A multi-stage risk assessment index was constructed at multiple stages. The first stage was before the initiation of ovarian stimulation, the second was before the ovulation trigger, the third was after oocyte retrieval, and the last stage was on the embryo transfer day if fresh embryo transfer was scheduled.

MAIN RESULTS AND THE ROLE OF CHANCE

We established a simplified multi-stage risk assessment index for moderate/severe OHSS, the performance of which was further evaluated with discrimination and calibration abilities in training and internal and external validation cohorts. The discrimination abilities of the OHSS risk assessment index were determined with C-statistics. C-statistics in training (Stages 1-4: 0.631, 0.692, 0.751, 0.788, respectively) and internal (Stages 1-4: 0.626, 0.642, 0.755, 0.771, respectively) and external validation (Stages 1-4: 0.668, 0.670, 0.754, 0.773, respectively) cohorts were all increased from Stage 1 to 3 with similar trends, and were comparable between Stages 3 and 4. Calibration plots showed high agreement between observed and predicted cases in all three cohorts. Incidences of OHSS based on diverse risk stratification (negligible risk, low risk, medium risk, and high risk) were 0%, 0.6%, 2.7%, and 8.3% in the training cohort, 0%, 0.6%, 3.3%, and 8.5% in the internal validation cohort, and 0.1%, 1.1%, 4.1%, and 7.2% in the external validation cohort.

LIMITATIONS, REASONS FOR CAUTION

The influence from clinical interventions including cryopreservation of all embryos cannot be eliminated and thus certain risk factors like estrogen level on trigger day might be assigned with a lower risk score. Another weakness of the study is that several preventive treatments, for instance oral aspirin and letrozole, were not recorded and evaluated in the model. Despite the robust reliability of OHSS assessment index, this tool cannot be used directly for clinical decision-making or as a diagnostic tool. Its value lies in its capacity to evaluate the prognosis of various interventions and to facilitate clinician-patient communication. The combination of this tool and further symptoms and examinations should be all taken into consideration for accurate and personalized management of OHSS.

WIDER IMPLICATIONS OF THE FINDINGS

The OHSS risk assessment index can be implemented to facilitate personalized counseling and management of OHSS.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by National Key R&D Program of China (2022YFC2702504), Medical Research Fund Guangdong Provincial (A2024003), and Xinjiang Support Rural Science and Technology (Special Correspondent) Program in Guangdong Province (KTPYJ 2023014). All authors had nothing to disclose.

TRIAL REGISTRATION NUMBER

N/A.

Gonadotropin upregulates intraovarian calpains-1 and -2 during ovarian follicular recruitment in the SD rat model

Calpain role has been shown in the cumulus cell-oocyte complexes and, corpus luteum. We investigated the association of calpains-1 and -2 in ovarian folliculogenesis using the Sprague-Dawley (SD) rat model and steroidogenesis in the human granulosa cells (hGCs). We induced PCOS in 42-day-old SD rats by letrozole oral gavage for 21 days. Premature ovarian failure (POF) was induced in 21-day-old SD rats by 4-vinylcyclohexene diepoxide (VCD). Ovulation and ovarian hyperstimulatory (OHS) syndrome were induced by pregnant mare gonadotropin (PMSG) + human chorionic gonadotropin (hCG) treatments in 21 days SD rats, respectively. Steroidogenesis is stimulated in human granulosa cells (hGCs) by forskolin and the response of 17-beta-estradiol (E2) on calpains expression was checked in hGCs. The protein expression by immunoblotting and activity by biochemical assay of calpains-1 and -2 showed an oscillating pattern in the ovarian cycle. PMSG-induced follicular recruitment showed upregulation of calpains-1 and -2, but with no change during ovarian function cessation (POF). Upregulated calpain-2 expression and calpain activity was found in the hCG +PMSG-induced ovulation. Letrozole-induced PCOS showed downregulation of calpain-1, but upregulation of calpain-2. PMSG+hCG-induced OHS led to the upregulation of calpain-1. Letrozole and metformin separately increased the expression level of calpains-1 and -2 in the hGCs during luteinization. In conclusion, the expression levels of calpains -1 and -2 are increased with ovarian follicular recruitment by PMSG and calpain-1 is decreased in the PCOS condition, and letrozole and metformin upregulate the expression of calpains-1 and -2 during luteinization in the hGCs possibly via E2 action.

Progress of the application clinical prediction model in polycystic ovary syndrome

Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease, complications, and treatment outcomes by applying specific methodologies. Polycystic ovary syndrome (PCOS) is a common disease with a high incidence rate, huge heterogeneity, short- and long-term complications, and complex treatments. In this systematic review study, we reviewed the progress of clinical prediction models in PCOS patients, including diagnosis and prediction models for PCOS complications and treatment outcomes. We aimed to provide ideas for medical researchers and clues for the management of PCOS. In the future, models with poor accuracy can be greatly improved by adding well-known parameters and validations, which will further expand our understanding of PCOS in terms of precision medicine. By developing a series of predictive models, we can make the definition of PCOS more accurate, which can improve the diagnosis of PCOS and reduce the likelihood of false positives and false negatives. It will also help discover complications earlier and treatment outcomes being known earlier, which can result in better outcomes for women with PCOS.

Comparison of the Effectiveness of Various Medicines in the Prevention of Ovarian Hyperstimulation Syndrome: A Network Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Previous studies have described the effects of different drugs in preventing ovarian hyperstimulation syndrome (OHSS). However, the efficacies of those drugs in preventing OHSS remain inconclusive.

METHODS

We searched the PubMed, Web of Science, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases. A network meta-analysis of randomized controlled trials (RCTs) was performed up to August 2021. We investigated the following drugs in our study: aspirin, albumin, metformin, calcium, cabergoline, quinagolide, letrozole, hydroxyethyl starch (HES), and glucocorticoids. The primary outcome was the incidence rate of moderate-to-severe OHSS, with the results presented as risk ratios (RRs) with 95% confidence intervals (CIs).

RESULTS

The incidence of moderate-to-severe OHSS was significantly reduced by calcium administration (risk ratios [RR] 0.14, 95% confidence interval [CI]: 0.04, 0.46) (grade: high), HES (RR 0.25, 95% CI 0.07, 0.73) (grade: high), and cabergoline (RR 0.43, 95% CI 0.24, 0.71) (grade: moderate). The surface under the cumulative ranking curve (SUCRA) indicated that calcium (SUCRA, 92.4%) was the most effective intervention for preventing moderate-to-severe OHSS. These drugs were safe and did not affect clinical pregnancy, miscarriage, or live birth rates.

CONCLUSION

Calcium, HES, and cabergoline could effectively and safely prevent moderate-to-severe OHSS, with calcium as the most effective intervention.

A Personalized Management Approach of OHSS: Development of a Multiphase Prediction Model and Smartphone-Based App

OBJECTIVE

This study aimed to develop multiphase big-data-based prediction models of ovarian hyperstimulation syndrome (OHSS) and a smartphone app for risk calculation and patients' self-monitoring.

METHODS

Multiphase prediction models were developed from a retrospective cohort database of 21,566 women from January 2017 to December 2020 with controlled ovarian stimulation (COS). There were 17,445 women included in the final data analysis. Women were randomly assigned to either training cohort (n = 12,211) or validation cohort (n = 5,234). Their baseline clinical characteristics, COS-related characteristics, and embryo information were evaluated. The prediction models were divided into four phases: 1) prior to COS, 2) on the day of ovulation trigger, 3) after oocyte retrieval, and 4) prior to embryo transfer. The multiphase prediction models were built with stepwise regression and confirmed with LASSO regression. Internal validations were performed using the validation cohort and were assessed by discrimination and calibration, as well as clinical decision curves. A smartphone-based app "OHSS monitor" was constructed as part of the built-in app of the IVF-aid platform. The app had three modules, risk prediction module, symptom monitoring module, and treatment monitoring module.

RESULTS

The multiphase prediction models were developed with acceptable distinguishing ability to identify OHSS at-risk patients. The C-statistics of the first, second, third, and fourth phases in the training cohort were 0.628 (95% CI 0.598-0.658), 0.715 (95% CI 0.688-0.742), 0.792 (95% CI 0.770-0.815), and 0.814 (95% CI 0.793-0.834), respectively. The calibration plot showed the agreement of predictive and observed risks of OHSS, especially at the third- and fourth-phase prediction models in both training and validation cohorts. The net clinical benefits of the multiphase prediction models were also confirmed with a clinical decision curve. A smartphone-based app was constructed as a risk calculator based on the multiphase prediction models, and also as a self-monitoring tool for patients at risk.

CONCLUSIONS

We have built multiphase prediction models based on big data and constructed a user-friendly smartphone-based app for the personalized management of women at risk of moderate/severe OHSS. The multiphase prediction models and user-friendly app can be readily used in clinical practice for clinical decision-support and self-management of patients.