Economic evaluation of GnRH-agonist long protocol and GnRH-antagonist protocol in IVT/ICSI among the Chinese population: using pharmacoeconomic models.

OBJECTIVE: This paper uses health economics methods to discuss the cost-effectiveness value of long protocol and antagonist protocol for in vitro fertilisation and embryo transfer (ET) in the Chinese population. DESIGN: Health economic evaluation study. SETTING: The data needed to construct the model for this study were derived from published studies and other secondary sources in China. PARTICIPANTS: No patients participated in the study. MEASURES: The main outcomes were live birth rate (LBR) and cost. From the societal perspective, we considered the direct and indirect costs over the course of the treatment cycles. A cost-effectiveness was measured using the incremental cost-effectiveness ratio and the probability that a protocol has higher net monetary benefit. Sensitivity analysis was carried out to verify the reliability of the simulation results. RESULTS: For the Chinese population, the long protocol resulted in a higher LBR than the antagonist protocol (29.33% vs 20.39%), but at the same time, it was more expensive (ï¿¥29 146.26 (US$4333.17) vs ï¿¥23 343.70 (US$3470.51)), in the case of considering only one fresh ET cycle. It was the same when considering subsequent frozen ET (FET) cycles (51.78% vs 42.81%; ï¿¥30 703.02 (US$4564.62) vs ï¿¥24 740.95 (US$3678.24)). The results of most subgroups were consistent with the results of the basic analysis. However, for certain populations, the long protocol was the inferior protocol (less effective and more expensive). CONCLUSION: For the Chinese population, when the monetary value per live birth was greater than ï¿¥65 420 (US$9726) and ï¿¥66 400 (US$9872), respectively, considering only one fresh cycle and considering subsequent frozen cycles, the long protocol is the preferred protocol. This threshold also varies for women of different ages and ovarian response capacities. For women in POSEIDON (Patient-Oriented Strategies Encompassing IndividualizeD Oocyte Number) group 2, group 3 and group 4, antagonist protocol is recommended as the preferred protocol. The results of this study need to be verified by further large-scale randomised controlled trials.

Gender differences in sleep behaviors under China's universal two-child policy.

Since 2016, China has progressively relaxed family planning policies to stimulate birth rates. This paper examines the behavioral health repercussions of China's 2016 universal two-child policy (UTCP) by analyzing sleep pattern data from China Family Panel Studies. Napping is a composite indicator that denotes health outcomes, job quality, and personal well-being. It reveals work conditions and environments to some extent. UTCP may lead to heightened social expectations regarding pregnancy likelihood, and changes in social expectations within the workplace may make work environments less equitable and more stressful for females. Leveraging a difference-in-difference model, this paper explores how napping behaviors among the working-age cohort have responded to the policy shifts. Our analysis reveals a gender discrepancy in response to the policy, specifically, females exhibit a discernible reduction in the likelihood of napping, as well as in the duration of both daytime naps and daily sleep. Conversely, such effects are not significant among males. These results suggest policy consequences extend beyond individuals directly impacted by childbirth or contemplating parenthood. Hence, while promoting fertility is still the government's goal, policymakers are encouraged to consider the broader challenges the female population faces from social and workplace environment factors.

Efficacy of non-invasive chromosome screening, preimplantation genetic testing for aneuploidy, and morphological grading in selecting embryos of patients with advanced maternal age: a three-armed prospective cohort study.

BACKGROUND: Non-invasive chromosome screening (NICS) and trophectoderm biopsy preimplantation genetic testing for aneuploidy (TE-PGT) were both applied for embryo ploidy detection, However, the cumulative live birth rates (CLBR) of NICS and TE-PGT in older age groups have yet to be reported. This study aimed to ascertain whether NICS and TE-PGT could enhance the cumulative live birth rates among patients of advanced maternal age. METHODS: A total of 384 couples aged 35-40 years were recruited. The patients were assigned to three groups: NICS, TE-PGT, and intracytoplasmic sperm injection (ICSI). All patients received frozen single blastocyst transfer. Patients in the NICS and TE-PGT groups underwent aneuploidy screening. RESULTS: When compared to the ICSI group, the CLBR was significantly higher in the NICS and TE-PGT groups (27.9% vs. 44.9% vs. 51.0%, p = 0.003 for NICS vs. ICSI, p < 0.001 for TE-PGT vs. ICSI). There were no significant differences in the clinical outcomes between the NICS and TE-PGT groups. Adjusting for confounding factors, the NICS and TE-PGT groups still showed a higher CLBR than the ICSI group (adjusted odds ratio (OR) 3.847, 95% confidence interval (CI) 1.939 to 7.634; adjusted OR 3.795, 95% CI 1.981 to 7.270). Additionally, the cumulative pregnancy loss rates of the NICS and TE-PGT groups were significantly lower than that of the ICSI group (adjusted OR 0.277, 95% CI 0.087 to 0.885; adjusted OR 0.182, 95% CI 0.048 to 0.693). There was no significant difference in the birth weights of the three groups (p = 0.108). CONCLUSIONS: In women 35-40 years old, the CLBR can be increased by selecting euploid embryos using NICS and TE-PGT. For elderly women at high risk of embryonic aneuploidy, NICS, characterized by its safety and non-invasive nature, may emerge as an alternative option for preimplantation genetic testing.

The effect of Chinese herbal medicine on male factor infertility: study protocol for a randomized controlled trial.

Background: The global prevalence of infertility is 9%, with male factors potentially accounting for 40% to 60% of cases. Conventional treatments can be ineffective, invasive, costly, and linked to adverse effects and high risks. Previous studies have shown that, Chinese herbal medicine (CHM) can regulate the hypothalamus-pituitary-testis axis, improve sperm abnormalities and quality, mitigate oxidative stress, and decrease DNA fragmentation index (DFI). Yet, the evidence backing the use of Chinese herbal medicine (CHM) for treating male factor infertility lacks conviction due to study design limitations, and there remains a scarcity of studies on the live birth rate following CHM treatment for male factor infertility. Here, we describe the rationale and design of a randomized waitlist-controlled trial to evaluate the effect of CHM on the live birth rate among males with infertility. Methods: This study is a single-center, randomized, waitlist-controlled study. A total of 250 couples diagnosed with male factor infertility will be enrolled in this study and then randomly allocated into two groups in a 1:1 ratio. Male participants in CHM group (treatment group) will receive CHM once a day for 3 months. Male participants in the waitlist group (control group) will not receive any treatment for 3 months. After 3 months, participants in both groups need to be followed up for another 12 months. The primary outcome will be the live birth rate; secondary outcomes include semen quality parameters, DFI and pregnancy related outcomes. Safety will also be assessed. Discussion: The purpose of this trial is to explore the effects and safety of CHM on the live birth rate among couples dealing with male factor infertility. The outcome of this trial may provide a viable treatment option for male factor infertility. Trial registration: Chinese Clinical Trial Registry: ChiCTR2200064416. Registered on 7 October 2022, https://www.chictr.org.cn.

Analysis of assisted reproductive outcomes for gynecologic cancer survivors: a retrospective study.

OBJECTIVE: To examine the reproductive outcomes of assisted reproductive technology (ART) in gynecologic cancer patients and to assess maternal and neonatal complications. METHODS: Women diagnosed with gynecologic cancer who underwent their first in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) treatment between 2013 and 2021 at Shanghai Ji Ai Genetics and IVF Institute were included in this study. Infertile women without any history of cancer were matched to the cancer group. The primary outcome was the cumulative live birth rate. Baseline and follow-up data were compared between groups using Student's t-tests for normally distributed variables and with Chi-square test for categorical variables. A propensity score-based patient-matching approach was adopted to ensure comparability between individuals with and without specific cancer type. RESULTS: A total of 136 patients with a history of gynecologic cancer and 241 healthy infertile controls were included in this study. Endometrial cancer constituted 50.70% of the cases and cervical cancer constituted 34.60% of the cases. The cancer group exhibited significantly shorter duration of stimulation, lower levels of estradiol, lower number of retrieved oocytes, day-3 embryos, and blastocysts compared to the control group (P < 0.05). The cumulative live birth rate of the gynecologic cancer group was significantly lower than that of the control group (36.10% vs. 60.50%, P < 0.001). Maternal and neonatal complications did not significantly differ between the groups (P > 0.05). The endometrial cancer and cervical cancer groups showed significantly lower cumulative live birth rates than their matched controls (38.60% vs. 64.50%, P = 0.011 and 24.20% vs. 68.60%, P < 0.001, respectively). CONCLUSIONS: These findings highlight the decreased occurrence of pregnancy and live birth in female gynecologic cancer patients undergoing ART, particularly in endometrial cancers and cervical cancers. These findings have important implications for counseling and managing gynecologic cancer patients undergoing ART.

Effectiveness and safety of GnRH antagonist originator and generic in real-world clinical practice: a retrospective cohort study.

Objective: This study aims to determine whether the live birth rates were similar between GnRH antagonist original reference product Cetrotide® and generic Ferpront®, in gonadotropin-releasing hormone (GnRH) antagonist protocol for controlled ovarian stimulation (COS). Methods: This retrospective cohort study investigates COS cycles utilizing GnRH antagonist protocols. The research was conducted at a specialized reproductive medicine center within a tertiary care hospital, spanning the period from October 2019 to October 2021. Within this timeframe, a total of 924 cycles were administered utilizing the GnRH antagonist originator, Cetrotide® (Group A), whereas 1984 cycles were undertaken using the generic, Ferpront® (Group B). Results: Ovarian reserve markers, including anti-Mullerian hormone, antral follicle number, and basal follicular stimulating hormone, were lower in Group A compared to Group B. Propensity score matching (PSM) was performed to balance these markers between the groups. After PSM, baseline clinical features were similar, except for a slightly longer infertile duration in Group A versus Group B (4.43 ± 2.92 years vs. 4.14 ± 2.84 years, P = 0.029). The duration of GnRH antagonist usage was slightly longer in Group B than in Group A (6.02 ± 1.41 vs. 5.71 ± 1.48 days, P < 0.001). Group B had a slightly lower number of retrieved oocytes compared to Group A (14.17 ± 7.30 vs. 14.96 ± 7.75, P = 0.024). However, comparable numbers of usable embryos on day 3 and good-quality embryos were found between the groups. Reproductive outcomes, including biochemical pregnancy loss, clinical pregnancy, miscarriage, and live birth rate, did not differ significantly between the groups. Multivariate logistic regression analyses suggested that the type of GnRH antagonist did not independently impact the number of oocytes retrieved, usable embryos, good-quality embryos, moderate to severe OHSS rate, clinical pregnancy, miscarriage, or live birth rate. Conclusion: The retrospective analysis revealed no clinically significant differences in reproductive outcomes between Cetrotide® and Ferpront® when used in women undergoing their first and second COS cycles utilizing the GnRH antagonist protocol.

Exploring the mystical relationship between the Moon, Sun, and birth rate.

OBJECTIVE: The Moon has a noticeable influence on the Earth due to its gravity, the most visible manifestation of which are tides. We aimed to see if the Moon's daily cycle, like the Sun's, affects the prevalence and incidence of childbirth. METHODS: In this retrospective cohort study, we examined all deliveries at the Academic Hospital of Udine between 2001 and 2019. All consecutive singleton pregnancies with spontaneous labor and vaginal delivery were included. RESULTS: During the period, 13,349 singleton pregnancies with spontaneous labor and vaginal delivery were delivered in 6939 days. A significantly higher prevalence of deliveries was found with the Moon above the horizon (50.63% vs. 49.37%, p < 0.05). Moreover, during the day, there was a significantly higher prevalence of deliveries than during nighttime (53.74% vs. 45.79%, p < 0.05). Combining the Moon and Sun altitude, the majority of deliveries were registered when both were above the horizon (27.39% vs. 26.13%, 23.25%, or 23.24%, p < 0.05). These findings were confirmed in multivariate analysis after adjusting for parity, gestational age, or season. We found no correlation between birth and the Moon phase. CONCLUSIONS: Our data support the interaction of the Moon and the Sun in determining the time of birth. More research is needed to understand these phenomena and improve our understanding of labor initiation mechanisms.

Clinical data-based modeling of IVF live birth outcome and its application.

BACKGROUND: The low live birth rate and difficult decision-making of the in vitro fertilization (IVF) treatment regimen bring great trouble to patients and clinicians. Based on the retrospective clinical data of patients undergoing the IVF cycle, this study aims to establish classification models for predicting live birth outcome (LBO) with machine learning methods. METHODS: The historical data of a total of 1405 patients undergoing IVF cycle were first collected and then analyzed by univariate and multivariate analysis. The statistically significant factors were identified and taken as input to build the artificial neural network (ANN) model and supporting vector machine (SVM) model for predicting the LBO. By comparing the model performance, the one with better results was selected as the final prediction model and applied in real clinical applications. RESULTS: Univariate and multivariate analysis shows that 7 factors were closely related to the LBO (with P < 0.05): Age, ovarian sensitivity index (OSI), controlled ovarian stimulation (COS) treatment regimen, Gn starting dose, endometrial thickness on human chorionic gonadotrophin (HCG) day, Progesterone (P) value on HCG day, and embryo transfer strategy. By taking the 7 factors as input, the ANN-based and SVM-based LBO models were established, yielding good prediction performance. Compared with the ANN model, the SVM model performs much better and was selected as the final model for the LBO prediction. In real clinical applications, the proposed ANN-based LBO model can predict the LBO with good performance and recommend the embryo transfer strategy of potential good LBO. CONCLUSIONS: The proposed model involving all essential IVF treatment factors can accurately predict LBO. It can provide objective and scientific assistance to clinicians for customizing the IVF treatment strategy like the embryo transfer strategy.

Association between pre-gravid body mass index and clinical outcomes in in vitro fertilization: a multicentered retrospective cohort study.

BACKGROUND: With the increasing incidence of obesity and the childbearing-age delay among women, a debate over obesity's impacts on pregnancy and neonatal outcomes becomes hot. The potential negative effects of obesity and aging on fertility lead to an idea, whether an obese female pursuing IVF treatment can benefit from an ideal BMI achieved over a long-time weight loss process at the cost of aging? We aimed to assess the association between body mass index (BMI) and clinical or neonatal outcomes in patients undergoing in vitro fertilization (IVF) treatment, for answering whether it is necessary to lose weight first for obese patients, particularly those at advanced age. METHODS: A retrospective cohort study was performed using multicentered data from China. The women were stratified into 5 groups in terms of pre-gravid BMI (kg/m2) with the WHO obesity standard (group 1: BMI < 18.5; group 2: 18.5 ≤ BMI < 23.0; group 3: 23.0 ≤ BMI < 25.0; group 4: 25.0 ≤ BMI < 30.0; group 5: BMI ≥ 30.0). The primary outcome was cumulative live birth rate (CLBR), and other clinical and neonatal outcomes were weighed as secondary outcomes. Multivariate logistic regression analyses were carried to evaluate the association between BMI and the CLBR, or between BMI and some neonatal outcomes. Furthermore, we implemented a machine-learning algorithm to predict the CLBR based on age and BMI. RESULTS: A total of 115,287 women who underwent first IVF cycles with autologous oocytes from January 2013 to December 2017 were included in our study. The difference in the CLBR among the five groups was statistically significant (P < 0.001). The multivariate logistic regression analysis showed that BMI had no significant impact on the CLBR, while women's age associated with the CLBR negatively. Further, the calculation of the CLBR in different age stratifications among the five groups revealed that the CLBR lowered with age increasing, quantitatively, it decreased by approximately 2% for each one-year increment after 35 years old, while little difference observed in the CLBR corresponding to the five groups at the same age stratification. The machine-learning algorithm derived model showed that BMI's effect on the CLBR in each age stratification was negligible, but age's impact on the CLBR was overwhelming. The multivariate logistic regression analysis showed that BMI did not affect preterm birth, low birth weight infant, small for gestational age (SGA) and large for gestational age (LGA), while BMI was an independent risk factor for fetal macrosomia, which was positively associated with BMI. CONCLUSIONS: Maternal pre-gravid BMI had no association with the CLBR and neonatal outcomes, except for fetal macrosomia. While the CLBR was lowered with age increasing. For the IVF-pursuing women with obesity plus advanced age, rather than losing weight first, the sooner the treatment starts, the better. A multicentered prospective study with a large size of samples is needed to confirm this conclusion in the future.

Individualized luteal phase support in frozen-thawed embryo transfer after intramuscular progesterone administration might rectify live birth rate.

Background: The serum P concentrations are suggested to have an impact on pregnancy outcome. However there is no consensus about the optimal progesterone cut-off during the luteal phase. Few studies evaluated the effectiveness of a "rescue protocol" for low serum P concentrations and most of these studies used vaginal progesterone administration. There is paucity of data on the effectiveness of rescue protocol using intramuscular progesterone (IM-P) in frozen-thawed embryo transfer (FET). Methods: This study is a retrospective cohort study included 637 single or double blastocyst FETs with artificially prepared endometrium receiving 100 mg IM progesterone (P) after incremental estrogen treatment. Serum P concentrations were evaluated using blood samples obtained 117-119 hours after the first IM-P administration and 21 ± 2 hours after the last IM-P administration. Patients with serum P concentrations <20.6 ng/ml on the ET day were administrated 400 mg vaginal progesterone for rescue. Results: Demographic and cycle characteristics were similar between patients receiving rescue vaginal P (embryo transfer (ET)-day P concentration < 20.6 ng/ml) and patients who did not need rescue vaginal P (ET-day P concentration ≥ 20.6 ng/ml). Clinical pregnancy, miscarriage, and live birth rates were similar between two groups: 52.9%(45/85) vs 59.6%(326/552), p=0.287; 11.1%(5/45) vs 14.1%(46/326), p=0.583; and 47.1%(40/85) vs 50.7%(280/552), p=0.526, respectively. Logistic regression analysis revealed that the female age (p = 0.008, OR=0.942, 95% CI = 0.902-0.984) and embryo quality (ref: good quality for moderate: p=0.02, OR=0.469, 95% CI =0.269-0.760; for poor: p=0.013, OR= 0.269, 95% CI = 0.092-0.757) were independent variables for live birth. Following rescue protocol implementation, ET-day P concentration was not a significant predictor of live birth. Conclusions: Rescue vaginal P administration for low ET day serum P concentrations following IM-P yields comparable live birth rates.

Predicting Future Birth Rates with the Use of an Adaptive Machine Learning Algorithm: A Forecasting Experiment for Scotland.

The total fertility rate is influenced over an extended period of time by shifts in population socioeconomic characteristics and attitudes and values. However, it may be impacted by macroeconomic trends in the short term, although these effects are likely to be minimal when fertility is low. With the objective of forecasting monthly deliveries, this study concentrates on the analysis of registered births in Scotland. Through this approach, we examine the significance of precisely forecasting fertility trends, which can subsequently aid in the anticipation of demand in diverse sectors by allowing policymakers to anticipate changes in population dynamics and customize policies to tackle emerging demographic challenges. Consequently, this has implications for fiscal stability, national economic accounts and the environment. In conducting our analysis, we incorporated non-linear machine learning methods alongside traditional statistical approaches to forecast monthly births in an out-of-sample exercise that occurs one step in advance. The outcomes underscore the efficacy of machine learning in generating precise predictions within this particular domain. In sum, this research will comprehensively demonstrate a cutting-edge model of machine learning that utilizes several attributes to assist in clinical decision-making, predict potential complications during pregnancy and choose the appropriate delivery method, as well as help in medical diagnosis and treatment.

Birth Patterns in the Aftermath of the 1918 Influenza Pandemic in India: The Case of Madras City.

This paper examines the timing of one-time fluctuations in births subsequent to the 1918 influenza pandemic in Madras (now Chennai), India. After seasonally decomposing key demographic aggregates, we identified abrupt one-time fluctuations in excess births, deaths, and infant deaths. We found a contemporaneous spike in excess deaths and infant deaths and a 40-week lag between the spike in deaths and a subsequent deficit in births. The results suggest that India experienced the same kind of short-term postpandemic "baby bust" that was observed in the United States and other countries. Identifying the mechanisms underlying this widespread phenomenon remains an open question and an important topic for future research.

State of South Dakota's Child: 2023.

In 2022, there was a decrease in births in the state with 111 fewer resident newborns than in the previous year. This represented a decrease of 1% of its white and 3.5% of its AIBO (American Indian, Black and Other) births. The 2022 birth rate per 1,000 population for the state (12.3) is higher than observed nationally (10.9) but matches its 2020 rate that was an historic low. Approximately 22% of all births in 2022 were AIBO and this percent of the state's entire birth cohort has decreased in the past several years. The American Indian contribution to the AIBO cohort has also decreased as its racial diversity has increased. The percent of births that are low birth weight has consistently been lower in South Dakota than nationally. An increase of 16 infant deaths in 2022 from 2021 and the decreased number of births led to an increase in the infant mortality rate (IMR = deaths in first year of life per 1,000 live births) from 6.3 to 7.8, but this 2022 IMR is not statistically significantly higher than its previous five-year mean. Further, the 2022 increase in the IMR was almost entirely among white infants with the post neonatal mortality rate (PNMR = deaths between 28 and 365 days of life) decreasing between these two years for AIBO infants. Nonetheless, the state's five year mean rates of death (2018-2022) are significantly higher for the AIBO than white infants for the neonatal (0-27 days) and post neonatal periods of the first year of life. Recently, however, the ratio of AIBO to white post neonatal mortality rate (PNMR) has decreased, but increased for the neonatal mortality rate (NMR). Infants in South Dakota are significantly more likely between 2018 and 2022 to die of congenital anomalies, sudden unexpected infant death (SUID), and accidents/homicides than in the United States in 2021. SUID remains the leading cause of post neonatal death and its risk may be decreased when babies are placed to sleep supine and alone in environments that are devoid of soft hazards.

Commentary on van Raalte et al.'s "The Dangers of Drawing Cohort Profiles From Period Data: A Research Note".

van Raalte et al. (2023) alerted demographers to the potential dangers of calculating cohort measures from the "diagonals" of gridded age-period (AP) data. In the case of cohort fertility, however, a minor change to the estimation procedure can mitigate the trend and cohort size biases that the authors identify. With an appropriate algorithm, researchers can estimate cohort fertility indices from AP data quite well.

Trends in fertility and abortion in Czechia.

The assessment of the development of fertility and abortion rates over the last three decades shows that Czechia has reached the top position in Europe with a total fertility rate of 1.83 children per woman in 2021. The postponement of fertility to women's older age, which was behind the sharp drop in fertility to 1.1, has been gradually slowed down and halted between 2015 and 2021. In recent years, there has been an increase in fertility rates for women aged 30 and older as well as a balanced increase for women under 30. In the European context Czechia has maintained its position as a country with lower rates of reproductive ageing. The favourable demographic position of Czechia among European countries is also illustrated by the relatively low level of the abortion rate. The postponement of female fertility to older ages has not been accompanied by an increase in the abortion rate among young women, but on the contrary a decline in fertility has been accompanied by a decline in the abortion rate. Given the year-on-year increase in total fertility (from 1.71 in 2020 to 1.83 in 2021), the initial effect of the COVID-19 pandemic on fertility can be assessed positively. However, the subsequent decline to 1.62 in 2022 is already the result of a combination of adverse effects stemming from the consequences of antipandemic measures and worsening economic conditions, to which new security risks associated with the war in Ukraine have subsequently been added. This has created the conditions for a further postponement of fertility until women are older.

Reconstructing Prospective Intergenerational Educational Mobility in 12 Countries.

In this article, we reconstruct prospective intergenerational educational mobility and explore fertility's role in this process for women born between 1925 and 1950 in 12 European countries. We do so by combining high-quality retrospective data (Generations and Gender Survey) and low-requirement prospective datasets using an inferential method developed and advanced in prior research. Our analysis shows that the negative educational fertility gradient partly compensates for the inequality in prospective mobility rates between lower and higher educated women and is most pronounced in high-inequality contexts. However, fertility's role is small and declining and thus does not account for much of the differences in mobility rates between countries. We also explore the relative importance of sibship size effects in mediating the effect of fertility gradient, finding it negligible. Finally, we explore the correspondence between prospective and retrospective estimates in the reconstruction of prospective mobility rates and suggest why the former, when available, must be preferred.

Decomposing the Drivers of Population Aging: A Research Note.

Population aging is an important and increasingly relevant area of study for demographers. A growing body of research seeks to determine how long-term changes in births, mortality, and migration-the three drivers of any demographic process-have shaped the present aging situation. Using variable-r decomposition and cohort data, this research note presents a formula for the change in the old-age dependency ratio to determine the extent to which relative changes in births, as well as in mortality and migration rates, contribute to aging. This perspective provides a careful and in-depth picture of aging and contributes to the debate concerning whether changes in births or mortality have had the strongest effect on population aging. When applied to Australia, the United States, and several European populations, the decomposition of the old-age dependency ratio shows that aging occurred in all populations and that changes in both births and mortality contributed to this aging. Analysis of these populations demonstrates that although they differed regarding which of these factors contributed more, changes in births prevailed as the more significant factor. In nearly all populations, migration decreased the rate of population aging.

Changes in online public opinions associated with various three-child supportive policies in China: Observational study using social media data over time.

BACKGROUND: According to the Seventh National Census, China's fertility rate is less than 1.5, marking a significant national issue with potential risks. To counter this low birth rate, the Chinese government has relaxed family planning policies and introduced supportive measures. PURPOSE: Changes in birth policy have attracted considerable attention from the people of China. This article aims to study the public's response to the three-child support policy using Weibo as a window. The goal is to provide a more balanced evaluation of current perspectives, enabling policymakers to formulate better fertility information, particularly when anticipating a poor public response to controversial policies. METHODOLOGY: This research uses a crawler to gather data from Sina Weibo. Through opinion mining of Weibo posts on the three-child policy, Weibo users' online opinions on the three-child policy are analyzed from two perspectives: their attention content and sentiment tendency. Using an interrupted time series, it examines changes in online views on the policy, matching policy documents to the time nodes of Weibo posts. FINDINGS: The public has shown great interest in and provided short-term positive feedback on policies related to improving maternity insurance, birth rewards, and housing subsidies. In contrast, there has been a continuous negative response to policies such as extending maternity leave, which has particularly sparked concerns among women regarding future employment and marital rights protection. On social media, the public's attention to the three-child birth policy has focused mainly on the protection of women's rights, especially legal rights after childbirth, and issues related to physical and mental health. Child-rearing support and economic pressure are also hot topics, involving the daily expenses of multichild families, childcare services, and housing pressure. However, this study also revealed that infertile or single women express a strong desire to have children, but due to limitations in the personal medical insurance system, this desire has not been fully satisfied. CONTRIBUTIONS: Our study demonstrates the feasibility of a rapid and flexible method for evaluating the public response to various three-child supportive policies in China using near real-time social media data. This information can help policy makers anticipate public responses to future pandemic three-child policies and ensure that adequate resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed but controversial, restrictions.

Predicting personalized cumulative live birth rate after a complete in vitro fertilization cycle: an analysis of 32,306 treatment cycles in China.

BACKGROUND: The cumulative live birth rate (CLBR) has been regarded as a key measure of in vitro fertilization (IVF) success after a complete treatment cycle. Women undergoing IVF face great psychological pressure and financial burden. A predictive model to estimate CLBR is needed in clinical practice for patient counselling and shaping expectations. METHODS: This retrospective study included 32,306 complete cycles derived from 29,023 couples undergoing IVF treatment from 2014 to 2020 at a university-affiliated fertility center in China. Three predictive models of CLBR were developed based on three phases of a complete cycle: pre-treatment, post-stimulation, and post-treatment. The non-linear relationship was treated with restricted cubic splines. Subjects from 2014 to 2018 were randomly divided into a training set and a test set at a ratio of 7:3 for model derivation and internal validation, while subjects from 2019 to 2020 were used for temporal validation. RESULTS: Predictors of pre-treatment model included female age (non-linear relationship), antral follicle count (non-linear relationship), body mass index, number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, tubal factor, male factor, and scarred uterus. Predictors of post-stimulation model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. Predictors of post-treatment model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), cumulative Day-3 embryos live-birth capacity (non-linear relationship), number of previous IVF attempts, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. The C index of the three models were 0.7559, 0.7744, and 0.8270, respectively. All models were well calibrated (p = 0.687, p = 0.468, p = 0.549). In internal validation, the C index of the three models were 0.7422, 0.7722, 0.8234, respectively; and the calibration P values were all greater than 0.05. In temporal validation, the C index were 0.7430, 0.7722, 0.8234 respectively; however, the calibration P values were less than 0.05. CONCLUSIONS: This study provides three IVF models to predict CLBR according to information from different treatment stage, and these models have been converted into an online calculator ( https://h5.eheren.com/hcyc/pc/index.html#/home ). Internal validation and temporal validation verified the good discrimination of the predictive models. However, temporal validation suggested low accuracy of the predictive models, which might be attributed to time-associated amelioration of IVF practice.