Development of nomogram to predict the probability of blastocyst formation on day 5: a retrospective study

Development of nomogram to predict the probability of blastocyst formation on day 5: a retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Development of nomogram to predict the probability of blastocyst formation on day 5: a retrospective study Huan Zhang, Wumin Jin, Junhui Sun, Zhihui Xu, Danna Ye This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2721055/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Blastocyst transfer may cause cycle cancellation due to no blastocyst has developed. Could we develop a model for predicting probability of blastocyst formation on Day 5? Methods The model was developed base on 4327 fresh in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) cycles. Univariate logistic regression analysis and multivariate logistic regression analysis were conduct to investigate the relationship between patient and cycle characteristics and the formation of usable blastocysts on Day 5. And the nomogram was developed based on variables selected from multivariate logistic regression analysis. Discrimination and calibration of the model was evaluated by area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration curve. Results Female age, type of fertilization, fertilization rate, cleavage rate, number of Day 3 embryo extended culture to blastocyst stage, high-quality rate of Day 3 embryos extended culture to blastocyst stage, were predictors of usable blastocysts formation on Day 5. Results showed AUC in the training cohort was 0.874 (95% CI 0.862–0.887) and AUC in validation cohort was 0.886 (95% CI 0.867–0.905), indicating the good discrimination ability of the model. And the calibration curves in training and validation cohorts were both close to the ideal diagonal line, reflecting good accuracy of the model. Conclusion This model provides an intuitive and simple tool for predicting the probability of usable blastocysts formation on Day 5, and it may be helpful to reduce the cancellation rate of blastocyst transfer. blastocyst prediction model nomogram extended embryo culture blastocyst formation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The improvements in embryo in vitro culture techniques, especially the advances in embryo culture media during the last decade, has led to a widespread usage of extending embryo culture to blastocyst stage (Glujovsky et al., 2022 ). Compared to cleavage stage embryo transfer on Day 3, blastocyst transfer on Day 5 or Day 6 has some advantages. It was well known, embryo transfer on the blastocyst stage had more opportunity to select embryo with the most implantation potential for transfer since embryo self-selection occurs following the embryonic genome activation on day 3 (Martins et al., 2017 ). Moreover, embryo transfer on the blastocyst stage was proposed to improve embryonic and uterine synchrony since embryo implantation commonly occurred between day 7 and 10 post-ovulation (Ojosnegros et al., 2021 ). Some studies have demonstrated that blastocyst transfer could achieve a higher implantation rate, clinical pregnancy, and live birth rate than cleavage stage embryos transfer with equal number of embryos (Clua et al., 2022 ; Li et al., 2021 ; Yang L, 2018). Another study reported that single blastocyst transfer could achieve comparable clinical pregnancy rate and reduce multiple pregnancy rates compared to two cleavage embryos transfers (Zander-Fox et al., 2011 ). However, blastocyst transfer may cause cycle cancellation due to no blastocyst formation (Neuhausser et al., 2020 ). In recent years, various methods have been used to predict the formation of blastocysts, such as time-lapse monitoring, gene expression profiling, and proteomics (Braga et al., 2016 ; Liao et al., 2021 ; Wong et al., 2010 ); however, these methods are time-consuming, laborious, and expensive, and thus not suitable for every patient. Nomograms, as statistical tools, are widely used to predict the diagnosis, occurrence, and development (Chen et al., 2021 ; Liu et al., 2022 ; Mu et al., 2020 ). This could calculate the probability of a specific outcome for each patient. In recent years, nomogram has been applied in the field of reproductive medicine. A previous study has developed a nomogram for predicting the cancellation of blastocyst transfer based on training cohort of 562 cycles; however, the calibration curve of validation cohort showed poor performance (P < 0.01) (Dessolle et al., 2009 ). A recent study established three nomograms for predicting blastocyst formation rates according to different types of female infertility; however, these models are only suitable for IVF cycles (Jin et al., 2021 ). In the present study, we sought to develop a nomogram for predicting the probability of usable blastocysts formation on day 5 based on a large retrospective dataset, and hoped that it could reduce the cancellation rate of blastocyst transfer. Materials and Methods Patients A total of 4327 fresh IVF or ICSI cycles between August 2019 and December 2021 were analyzed in this retrospective study. All the cycles were performed at The Reproductive Medicine Center of The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China. The inclusion criteria were as follows: (1) patients undergoing IVF or ICSI in fresh cycles; (2) at least one zygote extended culture to day 5. The exclusion criteria were as follows: (1) cycles with donor sperm, surgically retrieved sperm, or retrograde ejaculation; (2) sperm concentration ≤ 1 × 10 6 /mL; (3) cycles during half ICSI or oocyte in vitro maturation (IVM) treatment. The study was approved by the Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University (Program NO: KY2022-R205) and was carried out in compliance with the Declaration of Helsinki. As a retrospective study, the Ethics Committee of the First Afliated Hospital of Wenzhou Medical University approved the exemption of informed consent, and the datasets were anonymized before their use. Assisted Reproductive Technology procedures In our center, antagonist protocol, long agonist protocol, and other protocols of controlled ovarian hyperstimulation (COH) were applied as described previously (Jin et al., 2015 ; Yu et al., 2018 ). Human chorionic gonadotropin (HCG; Livzon, China) was used to trigger ovulation when at least one follicle reached 18 mm in diameter. After 36 h, oocytes were retrieved under transvaginal ultrasound and incubated in a humidified incubator for 2–4 h with 6% CO 2 and 5% O 2 at 37°C. Sperm samples were collected by the method of masturbation on the day of oocyte retrieval. After sperm samples liquefaction, sperm was evaluated for volume, concentration, and motility based on the fifth edition of the World Health Organization laboratory manual (WHO., 2010). Then, the samples were washed to remove the seminal fluid by density gradient centrifugation (DGC). For IVF cycles, sperm samples were washed twice by fertilization medium (G-IVF PLUS, Vitrolife) and then allowed to swim up before IVF. For ICSI cycles, sperm samples were washed once by fertilization medium (G-IVF PLUS, Vitrolife) before ICSI. In addition, the sperm DNA fragmentation (SDF) was assessed by sperm chromatin dispersion assay 1–2 months prior to IVF or ICSI cycles, as described by Zhang et al. (Zhang et al., 2022 ). IVF or ICSI procedures were conducted depending on the clinical indications. For IVF cycle, micro-drop insemination technique was utilized, and oocytes were cultured at a concentration of 400,000 progressive motile sperm cells/ml. For ICSI cycle, cumulus cells were denuded from oocytes by hyaluronidase treatment, and then sperm was injected in oocytes. Fertilization was assessed 16–18 h after insemination, and only the zygotes consisting of two pronuclei and two polar bodies were considered normal fertilization. On Day 3, the cleavage stage embryos were graded based on their morphology. Embryos with 7–9 blastomeres and < 20% anucleate fragments were defined as high-quality embryos in our center. According to the clinical requirements, usually the two top-quality embryos were transferred or vitrified. The surplus embryos were transferred from the cleavage embryo culture medium (G1-Plus, Vitrolife) into the blastocyst culture medium (G2-Plus, Vitrolife). On day 5 or 6, the morphology of blastocysts was evaluated based on the criteria of Gardner and Schoolcraft (Alpha Scientists in Reproductive and Embryology, 2011 ). The blastocysts with Gardner score ≥ 2BC were defined as usable blastocysts and vitrified. Development and evaluation of the nomogram model The endpoint of the present study was the formation of usable blastocysts on Day 5. The nomogram model was constructed as follows. First, univariate logistic regression analysis was performed to screen the predictive factors. Variables including female age, infertility duration, body mass index (BMI), type of fertilization, COH protocols, primary or secondary infertility, presence or absence of polycystic ovary syndrome (PCOS), sperm concentration, sperm motility, oocytes retrieved, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, high-quality rate of Day 3 embryos extended culture to blastocyst stage, and SDF were analyzed in univariate logistic regression analysis. Second, significant variables in univariate logistic regression analysis (P < 0.05) were further analyzed in multivariate logistic regression analysis. A backward stepwise variable selection was conducted to determine the variables that could be removed to improve the overall quality of the model (as measured by Akaike’s information criterion). Finally, the nomogram was developed based on variables selected from multivariate logistic regression analysis. The AUC of ROC curve and calibration curve were used to assessment the discrimination and calibration, respectively. The value of AUC ranged from 0–1, and the value of AUC 0.5–0.7, 0.7–0.8, or 0.8–0.9 was considered as poor, fair, or good performance, respectively (Dessolle et al., 2009 ). Statistical analysis Data were performed using SPSS software (Statistical Package for the Social Sciences, version 16.0, SPSS Inc., IL, USA) and R software (version 4.1.2; http://www.r-project.org/ ). For continuous variables, the normal distribution was expressed as mean ± standard deviation and analyzed using t-test, while the skewed distribution was presented as median (P25, P75) and analyzed by Mann-Whitney U test. Categorical variables were reported as frequencies (percentages) and analyzed using chi-square test. All statistical tests were two-sided, and P-value < 0.05 was considered significant. In the present study, imputation for missing variables was considered if missing values were < 20%. We used a series mean to replace the missing values for infertility duration, BMI and SDF. Results General characteristics A total of 4327 cycles were randomly separated into training (3031) and validation cohorts (1296) at the ratio of 7:3. The patient and cycle characteristics of the two cohorts are summarized in Table 1 . No significant differences were observed between the two cohorts, except that the type of fertilization of the validation cohort was preferred for ICSI. Table 1 Patients and cycles characteristics in the training and validation cohorts Training cohort Validation cohort P-value Number of cycles 3031 1296 Female age (years) 32.0 (29.0–35.7) 31.9 (28.8–35.9) 0.755 Male age (years) 33.8 (30.6–37.6) 33.7 (30.3–37.9) 0.805 Duration of infertility (years) 3.0 (2.0–4.0) 3.0 (2.0–4.0) 0.373 Female BMI (kg/m 2 ) 22.0 (20.0–24.0) 22.2 (19.9–24.0) 0.296 Primary or secondary infertility Primary (%) Secondary (%) 34.9 65.1 34.0 66.0 0.564 Type of fertilization ICSI (%) IVF (%) 21.3 78.7 24.1 75.9 0.043 COH protocols Antagonist (%) Long agonist (%) Other (%) 56.5 24.2 19.3 55.2 24.5 20.2 0.699 Sperm concentration (milllion/mL) 46.0 (35.0–64.0) 46.0 (33.3–63.8) 0.362 Sperm motility (%) 47.0 (41.0–53.0) 47.0 (40.0–53.0) 0.746 SDF SDF ≤ 30 (%) SDF > 30 (%) 92.9 7.1 91.8 8.2 0.198 PCOS PCOS (%) No-PCOS (%) 14.3 85.7 14.0 86.0 0.804 Gonadotrophin duration (days) 10.0 (9.0–11.0) 10.0 (9.0,11.0) 0.916 Gonadotrophin dosage (IU) 1725 (1350–2250) 1726 (1375–2200) 0.774 Oocytes retrieved 13.0 (8.0–18.0) 13.0 (9.0–18.0) 0.295 Fertilization rate (%) 69.4 (56.3–82.1) 70.0 (57.1–81.8) 0.767 Cleavage rate (%) 100 (100–100) 100 (100–100) 0.755 Number of day3 embryos extended culture to blastocyst stage 5 (3.0–9.0) 5 (3.0–9.0) 0.776 High quality rate of day3 embryos extended culture to blastocyst 25.0 (0–50) 25.0 (0–50) 0.600 Usable blastulation rate on day 5 30.0 (0–30) 30.0 (0–30) 0.563 Usable blastulation rate 41.7(8.3–63.6) 40.0(1.8–66.7) 0.945 Screening for predictive factors Univariate logistic regression analysis demonstrated that female age, infertility duration, type of fertilization, COH protocols, presence or absence of PCOS, oocytes retrieved, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, and high-quality rate of Day 3 embryos extended culture to blastocyst stage are associated with the formation of usable blastocysts on Day 5 (P < 0.05). Multivariate logistic regression analysis showed that the formation of usable blastocysts on Day 5 was associated with female age [P < 0.01, odds ratio (OR) 0.970, 95% confidence interval (CI): 0.950–0.991), type of fertilization (ICSI vs . IVF) (P < 0.01, OR 0.612, 95% CI: 0.474–0.789), cleavage rate (P < 0.01, OR 1.040, 95% CI: 1.019–1.062), number of Day 3 embryos extended culture to the blastocyst stage (P < 0.01, OR 1.465, 95% CI: 1.404–1.530), and high-quality rate of Day 3 embryos extended culture to the blastocyst stage (P < 0.01, OR 1.028, 95% CI: 1.024–1.032). Although fertilization rate (P = 0.06, OR 1.005, 95% CI: 1.000–1.011) was not statistically related to stable blastocyst formation on Day 5, its inclusion could improve the overall quality of the model. The equation calculating the probability of usable blastocysts formation on Day 5 was: P = 1 / [1 + exp(-X)] where X = -4.812365 − 0.030108 × X1 − 0.491476 × X2 + 0.005328 × X3 + 0.039225 × X4 + 0.381565 × X5 + 0.027819 × X6; Where X1 was female age, X2 was the type of fertilization (0 if IVF and 1 if ICSI), X3 was fertilization rate, X4 was cleavage rate, X5 was number of Day 3 embryos extended culture to blastocyst stage, and X6 was high-quality rate of Day 3 embryos extended culture to blastocyst stage. Nomogram development and evaluation The nomogram developed based on this equation is shown in Fig. 1 . For each cycle, high total points indicated a higher probability of blastocyst formation on Day 5. Additionally, The Hosmer − Lemeshow test suggested that the model was a good fit (P = 0.368). Results showed that the AUC of ROC in the training cohort was 0.874 (95% CI: 0.862–0.887) (Fig. 2 ) and that in the validation cohort was 0.886 (95% CI: 0.867–0.905) (Fig. 3 ), indicating a good discrimination ability of the model. The calibration curves in both cohorts (Figs. 4 and 5 ) was close to the ideal diagonal line, reflecting the good accuracy of the model. Discussion In the present study, we developed a model for predicting the individual probability of usable blastocyst formation on Day 5 based on training cohorts and then the model was validated by validation cohort. The model indicated that female age, type of fertilization, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, and high-quality rate of Day 3 embryos extended culture to blastocyst stage were predictors of usable blastocysts formation on Day 5. Two previously study have developed models to predict blastocyst formation on Day 5(Dessolle et al., 2009 ; Jin et al., 2021 ), however our prediction model has some advantages compared to the two studies. First, the discrimination of our predict model was better than these previously predicted models. In the present the AUC value of training cohort and validation cohorts were 0.874 (95% CI: 0.862–0.886) and 0.886 (95% CI: 0.867–0.905) respectively, showing good discrimination ability of the model; while the AUC values of training cohorts of these previously predicted models were fair performance. Second, the accuracy of our model was better than the model developed by Dessolle L et al., as the calibration curves of training cohort and validation were close to the ideal diagonal line in the present study while the calibration curve of validation cohort was poor performance (P < 0.01) in Dessolle L et al. 's study. Third, our prediction model could be used for predicting blastocyst formation in both IVF and ICSI cycles while models of Jin H et al. 's study are only suitable for IVF cycles. Previous studies have shown that female age is strongly associated with the clinical outcomes of reproductive medicine (van Loendersloot et al., 2010 ; von Wolff et al., 2019 ). Some studies have shown that increased female age has a negative effect on blastocyst formation (Dessolle et al., 2009 ; Jin et al., 2021 ; La Marca et al., 2022 ; Thomas et al., 2010 ). In our nomogram model, a lower female age corresponding to higher points indicated a higher probability of blastocyst formation on Day 5; these results were consistent with the published data. It was well known, abnormalities in the oocyte ooplasm, including organelle dysfunction, altered metabolism, and aberrant gene regulation, would be accumulative with increased female age and progressively undermined oocyte quality (Bebbere et al., 2022 ). Oocytes derived from older woman would reduce the ability to repair sperm DNA fragmentation which was negatively correlated with blastocyst formation(Sedó et al., 2017 ; Setti et al., 2021 ). Moreover, mitochondrial function at morula stage was decreased with maternal ageing, and thus impar morula-to-blastocyst transition(Hashimoto and Morimoto, 2022 ). A recent study has indicated that advanced maternal age significantly effect on pronuclear, chromatin dynamics, regulation of cell polarity and blastocyst formation rate (Ezoe et al., 2023 ). Type of fertilization was also an independent predictor in our model. In the present study, multivariate regression analysis showed that type of fertilization was associated with the formation of usable blastocysts on Day 5 (ICSI vs . IVF) (P < 0.01, OR 0.612, 95% CI: 0.474–0.789). This result was in accordance with some earlier published studies (Dessolle et al., 2009 ; Thomas et al., 2010 ; Yin et al., 2014 ). Thomas et al. indicated that ICSI has a negative effect on blastocyst formation rate (Thomas et al., 2010 ). Yin et al. found that either the blastocyst formation rate where blastocyst derived from good morphology embryos or the total blastocyst formation rate in IVF cycles was significantly higher compared to ICSI cycles (Yin et al., 2014 ). This phenomenon could be explained that ICSI technology can bypass the selective biological barrier of zona pellucida and may bring abnormal sperm into the oocyte, subsequently affecting embryonic development and blastocyst formation. One study has determined that the ICSI zygotes have many more vacuoles than IVF zygotes, and the presence of vacuoles was related to a lower blastocyst formation rate (Ebner et al., 2005 ). In the present study, number of Day 3 embryos extended culture to blastocyst stage was significant associated with usable blastocyst formation on Day 5 and was included in the model. Surprisingly, the number of oocytes retrieved was not incorporated into the model. A systematic review and meta-analysis has indicated that the number of oocytes retrieved was positively correlated with the number of high-quality embryo (Vermey et al., 2019 ). Moreover, two studies that construct prediction models for predicting blastocyst formation have demonstrated that the number of oocytes retrieved was an important predictor of blastocyst formation (Dessolle et al., 2009 ; Jin et al., 2021 ). The causation of the number of Day 3 embryos extended culture to blastocyst stage rather than the number of oocytes retrieved entered in the model, may be attributed to the fact that not all Day 3 embryos cohort were cultured to blastocyst stage and usually the best one or two embryos were transferred or vitrified in the present study. The fertilization rate, cleavage rate, high-quality rate of Day 3 embryos extended culture to blastocyst stage were residual predictors of usable blastocyst formation on Day 5. Higher fertilization rate or cleavage rate usually produce more zygotes and cleaved embryos in fresh cycles, earlier study has demonstrated that the number of zygotes and cleaved embryos have positive effect on clinical outcomes(Hariton et al., 2017 ). It was shown that high-quality Day 3 embryos have more potential to develop into blastocysts(Yin et al., 2014 ), in the present study high-quality rate of Day 3 embryos extended culture to blastocyst stage corresponded to a high point; these results were similar to the previously predicted models(Dessolle et al., 2009 ; Jin et al., 2021 ). In the present study, we developed a prediction model with good discrimination and accuracy. Nevertheless, the study has two limitations. First, the present study was a retrospective study, and hence the probability of potential bias could not be excluded. Second, the data analyzed in the present study was from a single center; thus, a multicenter study should be conducted to test the applicability of the model future. In conclusion, we developed a model to predict the probability of usable blastocysts formation on Day 5. Variables, including female age, type of fertilization, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, and high-quality rate of Day 3 embryos extended culture to blastocyst stage were entered into this model. This prediction model performed satisfactorily, as confirmed by validation data. Thus, it provides an intuitive and simple tool for predicting the probability of usable blastocyst formation on Day 5, which might be helpful in decreasing the cancellation rate of blastocyst transfer. Abbreviations IVF In Vitro Fertilization ICSI Intracytoplasmic Sperm Injection )， AUC Area Under the Curve ROC Receiver Operating Characteristic IVM In Vitro Maturation COH Controlled Ovarian Hyperstimulation DGC Density Gradient Centrifugation HCG Human Chorionic Gonadotropin SDF Sperm DNA Fragmentation BMI Body Mass Index PCOS Polycystic Ovary Syndrome OR Odds Ratio CI Confidence Interval Declarations Ethics approval and consent to participate This study followed the Declaration of Helsinki and was performed in accordance with the relevant local guidelines and regulations. The present study was approved by the Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University (Program NO: KY2022-R205), Wenzhou, Zhejiang, China. As a retrospective study, the Ethics Committee of the First Afliated Hospital of Wenzhou Medical University approved the exemption of informed consent, and the datasets were anonymized before their use. Consent for publication Not applicable. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Funding Not applicable. Authors’ contributions Z. conceived of study and drafted the manuscript. D.Y. designed the study. W.J. and J.S. contributed to data acquisition. H.Z. and Z.X. interpreted the data. All authors critically and substantially revised the manuscript and approved the submitted version. Acknowledgements Not applicable. References Alpha Scientists in Reproductive, M., and Embryology, E.S.I.G.o. The Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting. Hum Reprod 2011; 26: 1270-1283. Bebbere, D., Coticchio, G., Borini, A., Ledda, S. Oocyte aging: looking beyond chromosome segregation errors. Journal of Assisted Reproduction and Genetics 2022; 39: 793-800. 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Yang L, C.S., Zhang S, Kong X, Gu Y, Lu C, Dai J, Gong F, Lu G, Lin G. Single embryo transfer by Day 3 time-lapse selection versus Day 5 conventional morphological selection: a randomized, open-label, non-inferiority trial. Human Reproduction 2018; 33: 869-876. Yin, H., Jiang, H., He, R., Wang, C., Zhu, J., Luan, K. The effects of fertilization mode, embryo morphology at day 3, and female age on blastocyst formation and the clinical outcomes. Systems Biology in Reproductive Medicine 2014; 61: 50-56. Yu, R., Jin, H., Huang, X., Lin, J., Wang, P. Comparison of modified agonist, mild-stimulation and antagonist protocols for in vitro fertilization in patients with diminished ovarian reserve. Journal of International Medical Research 2018; 46: 2327-2337. Zander-Fox, D.L., Tremellen, K., Lane, M. Single blastocyst embryo transfer maintains comparable pregnancy rates to double cleavage-stage embryo transfer but results in healthier pregnancy outcomes. Australian and New Zealand Journal of Obstetrics and Gynaecology 2011; 51: 406-410. Zhang, H., Li, Y., Wang, H., Zhou, W., Zheng, Y., Ye, D. Does sperm DNA fragmentation affect clinical outcomes during vitrified-warmed single-blastocyst transfer cycles? A retrospective analysis of 2034 vitrified-warmed single-blastocyst transfer cycles. Journal of Assisted Reproduction and Genetics 2022; 39: 1359-1366. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2721055","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":194857776,"identity":"5b32ba85-b414-4129-96b7-573884f4e5c4","order_by":0,"name":"Huan Zhang","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Zhang","suffix":""},{"id":194857777,"identity":"6b1f7c73-8ee0-4cfd-9568-a90ff3d0f40f","order_by":1,"name":"Wumin Jin","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wumin","middleName":"","lastName":"Jin","suffix":""},{"id":194857778,"identity":"0af349f4-fcf1-4561-8106-c3105222ac88","order_by":2,"name":"Junhui Sun","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Junhui","middleName":"","lastName":"Sun","suffix":""},{"id":194857779,"identity":"a2a106fd-8b73-4bdf-a627-29b157e9b4f1","order_by":3,"name":"Zhihui Xu","email":"","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhihui","middleName":"","lastName":"Xu","suffix":""},{"id":194857780,"identity":"e4877e83-2c50-4236-ac72-d8d78c3b242e","order_by":4,"name":"Danna Ye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYJACCRDBD2Ezk6BFsoFkLQYHiNVicLyB8cbPHXfkjW9kp0kwVFgnNrCfPYBfy5kDzJa9Z54ZbruRu02C4Ux6YgNPXgJ+LTcS2CR42w4zbrsN1MLYdjixQYLHAL+W+w/YJP+2HbbfPBuk5R8xWm4wsEkDbUncIA3S0kCEFskzCczWsm2Hk2fcf7vZIuFYunEbTw5+LXzHDzDefNt22La/5+zGGx9qrGX72c/g16JwgP8DgpcAxGx41QOBfAMhFaNgFIyCUTAKAB1ER9HfYJfwAAAAAElFTkSuQmCC","orcid":"","institution":"The First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Danna","middleName":"","lastName":"Ye","suffix":""}],"badges":[],"createdAt":"2023-03-22 03:59:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2721055/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2721055/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":36376499,"identity":"4a1c75ef-d937-49a8-82d9-6c5b0fa34d2f","added_by":"auto","created_at":"2023-04-27 13:28:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":157408,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram to predict the probability of usable blastocysts formation on day\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2721055/v1/77c1823a0ae44ddb5cd09f18.png"},{"id":36377751,"identity":"79a0be02-ceca-4509-922c-6ea15bc2bdb4","added_by":"auto","created_at":"2023-04-27 13:36:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38057,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of training cohort.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2721055/v1/0daa11464baa81c09295b6a6.png"},{"id":36377731,"identity":"2658e495-3f29-4d1f-b1da-bf004c467936","added_by":"auto","created_at":"2023-04-27 13:36:37","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38293,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of validation cohort.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2721055/v1/6f78d451e4ae3f1914c77d54.png"},{"id":36376495,"identity":"ee4cf01d-7321-43e6-b783-c83118661d45","added_by":"auto","created_at":"2023-04-27 13:28:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48673,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration curve of training cohort.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2721055/v1/74777472b6be588890796d14.png"},{"id":36376496,"identity":"309539f7-bb84-473d-87a9-4a75962f1680","added_by":"auto","created_at":"2023-04-27 13:28:37","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":48987,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration curve of validation cohort.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2721055/v1/ca0b83bbe2bc91d1ab45d6a5.png"},{"id":42219144,"identity":"c9fa14c3-c65e-4507-9aba-ee00c85bef8d","added_by":"auto","created_at":"2023-08-28 07:07:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1399008,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2721055/v1/13f51e72-b5a1-4dc8-bf1c-779c55f51bd7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of nomogram to predict the probability of blastocyst formation on day 5: a retrospective study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe improvements in embryo in vitro culture techniques, especially the advances in embryo culture media during the last decade, has led to a widespread usage of extending embryo culture to blastocyst stage (Glujovsky et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Compared to cleavage stage embryo transfer on Day 3, blastocyst transfer on Day 5 or Day 6 has some advantages. It was well known, embryo transfer on the blastocyst stage had more opportunity to select embryo with the most implantation potential for transfer since embryo self-selection occurs following the embryonic genome activation on day 3 (Martins et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Moreover, embryo transfer on the blastocyst stage was proposed to improve embryonic and uterine synchrony since embryo implantation commonly occurred between day 7 and 10 post-ovulation (Ojosnegros et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Some studies have demonstrated that blastocyst transfer could achieve a higher implantation rate, clinical pregnancy, and live birth rate than cleavage stage embryos transfer with equal number of embryos (Clua et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yang L, 2018). Another study reported that single blastocyst transfer could achieve comparable clinical pregnancy rate and reduce multiple pregnancy rates compared to two cleavage embryos transfers (Zander-Fox et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, blastocyst transfer may cause cycle cancellation due to no blastocyst formation (Neuhausser et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In recent years, various methods have been used to predict the formation of blastocysts, such as time-lapse monitoring, gene expression profiling, and proteomics (Braga et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liao et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wong et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); however, these methods are time-consuming, laborious, and expensive, and thus not suitable for every patient.\u003c/p\u003e \u003cp\u003eNomograms, as statistical tools, are widely used to predict the diagnosis, occurrence, and development (Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This could calculate the probability of a specific outcome for each patient. In recent years, nomogram has been applied in the field of reproductive medicine. A previous study has developed a nomogram for predicting the cancellation of blastocyst transfer based on training cohort of 562 cycles; however, the calibration curve of validation cohort showed poor performance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Dessolle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). A recent study established three nomograms for predicting blastocyst formation rates according to different types of female infertility; however, these models are only suitable for IVF cycles (Jin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, we sought to develop a nomogram for predicting the probability of usable blastocysts formation on day 5 based on a large retrospective dataset, and hoped that it could reduce the cancellation rate of blastocyst transfer.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eA total of 4327 fresh IVF or ICSI cycles between August 2019 and December 2021 were analyzed in this retrospective study. All the cycles were performed at The Reproductive Medicine Center of The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China. The inclusion criteria were as follows: (1) patients undergoing IVF or ICSI in fresh cycles; (2) at least one zygote extended culture to day 5. The exclusion criteria were as follows: (1) cycles with donor sperm, surgically retrieved sperm, or retrograde ejaculation; (2) sperm concentration\u0026thinsp;\u0026le;\u0026thinsp;1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e/mL; (3) cycles during half ICSI or oocyte in vitro maturation (IVM) treatment.\u003c/p\u003e \u003cp\u003eThe study was approved by the Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University (Program NO: KY2022-R205) and was carried out in compliance with the Declaration of Helsinki. As a retrospective study, the Ethics Committee of the First Afliated Hospital of Wenzhou Medical University approved the exemption of informed consent, and the datasets were anonymized before their use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAssisted Reproductive Technology procedures\u003c/h2\u003e \u003cp\u003eIn our center, antagonist protocol, long agonist protocol, and other protocols of controlled ovarian hyperstimulation (COH) were applied as described previously (Jin et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Human chorionic gonadotropin (HCG; Livzon, China) was used to trigger ovulation when at least one follicle reached 18 mm in diameter. After 36 h, oocytes were retrieved under transvaginal ultrasound and incubated in a humidified incubator for 2\u0026ndash;4 h with 6% CO\u003csub\u003e2\u003c/sub\u003e and 5% O\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C.\u003c/p\u003e \u003cp\u003eSperm samples were collected by the method of masturbation on the day of oocyte retrieval. After sperm samples liquefaction, sperm was evaluated for volume, concentration, and motility based on the fifth edition of the World Health Organization laboratory manual (WHO., 2010). Then, the samples were washed to remove the seminal fluid by density gradient centrifugation (DGC). For IVF cycles, sperm samples were washed twice by fertilization medium (G-IVF PLUS, Vitrolife) and then allowed to swim up before IVF. For ICSI cycles, sperm samples were washed once by fertilization medium (G-IVF PLUS, Vitrolife) before ICSI. In addition, the sperm DNA fragmentation (SDF) was assessed by sperm chromatin dispersion assay 1\u0026ndash;2 months prior to IVF or ICSI cycles, as described by Zhang et al. (Zhang et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIVF or ICSI procedures were conducted depending on the clinical indications. For IVF cycle, micro-drop insemination technique was utilized, and oocytes were cultured at a concentration of 400,000 progressive motile sperm cells/ml. For ICSI cycle, cumulus cells were denuded from oocytes by hyaluronidase treatment, and then sperm was injected in oocytes. Fertilization was assessed 16\u0026ndash;18 h after insemination, and only the zygotes consisting of two pronuclei and two polar bodies were considered normal fertilization. On Day 3, the cleavage stage embryos were graded based on their morphology. Embryos with 7\u0026ndash;9 blastomeres and \u0026lt;\u0026thinsp;20% anucleate fragments were defined as high-quality embryos in our center. According to the clinical requirements, usually the two top-quality embryos were transferred or vitrified. The surplus embryos were transferred from the cleavage embryo culture medium (G1-Plus, Vitrolife) into the blastocyst culture medium (G2-Plus, Vitrolife). On day 5 or 6, the morphology of blastocysts was evaluated based on the criteria of Gardner and Schoolcraft (Alpha Scientists in Reproductive and Embryology, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The blastocysts with Gardner score\u0026thinsp;\u0026ge;\u0026thinsp;2BC were defined as usable blastocysts and vitrified.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDevelopment and evaluation of the nomogram model\u003c/h2\u003e \u003cp\u003eThe endpoint of the present study was the formation of usable blastocysts on Day 5. The nomogram model was constructed as follows. First, univariate logistic regression analysis was performed to screen the predictive factors. Variables including female age, infertility duration, body mass index (BMI), type of fertilization, COH protocols, primary or secondary infertility, presence or absence of polycystic ovary syndrome (PCOS), sperm concentration, sperm motility, oocytes retrieved, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, high-quality rate of Day 3 embryos extended culture to blastocyst stage, and SDF were analyzed in univariate logistic regression analysis. Second, significant variables in univariate logistic regression analysis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were further analyzed in multivariate logistic regression analysis. A backward stepwise variable selection was conducted to determine the variables that could be removed to improve the overall quality of the model (as measured by Akaike\u0026rsquo;s information criterion). Finally, the nomogram was developed based on variables selected from multivariate logistic regression analysis.\u003c/p\u003e \u003cp\u003eThe AUC of ROC curve and calibration curve were used to assessment the discrimination and calibration, respectively. The value of AUC ranged from 0\u0026ndash;1, and the value of AUC 0.5\u0026ndash;0.7, 0.7\u0026ndash;0.8, or 0.8\u0026ndash;0.9 was considered as poor, fair, or good performance, respectively (Dessolle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were performed using SPSS software (Statistical Package for the Social Sciences, version 16.0, SPSS Inc., IL, USA) and R software (version 4.1.2; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.r-project.org/\u003c/span\u003e\u003cspan address=\"http://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For continuous variables, the normal distribution was expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and analyzed using t-test, while the skewed distribution was presented as median (P25, P75) and analyzed by Mann-Whitney U test. Categorical variables were reported as frequencies (percentages) and analyzed using chi-square test. All statistical tests were two-sided, and P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. In the present study, imputation for missing variables was considered if missing values were \u0026lt;\u0026thinsp;20%. We used a series mean to replace the missing values for infertility duration, BMI and SDF.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eGeneral characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 4327 cycles were randomly separated into training (3031) and validation cohorts (1296) at the ratio of 7:3. The patient and cycle characteristics of the two cohorts are summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. No significant differences were observed between the two cohorts, except that the type of fertilization of the validation cohort was preferred for ICSI.\u003c/p\u003e\n \u003cp\u003eTable 1 Patients and cycles characteristics in the training and validation cohorts\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"574\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003eTraining cohort\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003eValidation cohort\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eNumber of cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e3031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e1296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eFemale age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e32.0 (29.0\u0026ndash;35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e31.9 (28.8\u0026ndash;35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eMale age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e33.8 (30.6\u0026ndash;37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e33.7 (30.3\u0026ndash;37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eDuration of infertility (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e3.0 (2.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e3.0 (2.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eFemale BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e22.0 (20.0\u0026ndash;24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e22.2 (19.9\u0026ndash;24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary or secondary infertility\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePrimary (%)\u003c/p\u003e\n \u003cp\u003eSecondary (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e34.9\u003c/p\u003e\n \u003cp\u003e65.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e34.0\u003c/p\u003e\n \u003cp\u003e66.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eType of fertilization\u003c/p\u003e\n \u003cp\u003eICSI (%)\u003c/p\u003e\n \u003cp\u003eIVF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21.3\u003c/p\u003e\n \u003cp\u003e78.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24.1\u003c/p\u003e\n \u003cp\u003e75.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eCOH protocols\u003c/p\u003e\n \u003cp\u003eAntagonist (%)\u003c/p\u003e\n \u003cp\u003eLong agonist (%)\u003c/p\u003e\n \u003cp\u003eOther (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56.5\u003c/p\u003e\n \u003cp\u003e24.2\u003c/p\u003e\n \u003cp\u003e19.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55.2\u003c/p\u003e\n \u003cp\u003e24.5\u003c/p\u003e\n \u003cp\u003e20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.699\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eSperm concentration (milllion/mL)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e46.0 (35.0\u0026ndash;64.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e46.0 (33.3\u0026ndash;63.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eSperm motility (%)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e47.0\u0026nbsp;(41.0\u0026ndash;53.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e47.0\u0026nbsp;(40.0\u0026ndash;53.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eSDF\u003c/p\u003e\n \u003cp\u003eSDF \u0026le; 30 (%)\u003c/p\u003e\n \u003cp\u003eSDF \u0026gt; 30 (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e92.9\u003c/p\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e91.8\u003c/p\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003ePCOS\u003c/p\u003e\n \u003cp\u003ePCOS (%)\u003c/p\u003e\n \u003cp\u003eNo-PCOS (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003cp\u003e85.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003cp\u003e86.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eGonadotrophin duration (days)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e10.0\u0026nbsp;(9.0\u0026ndash;11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e10.0\u0026nbsp;(9.0,11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eGonadotrophin dosage (IU)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e1725 (1350\u0026ndash;2250)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e1726 (1375\u0026ndash;2200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eOocytes retrieved\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e13.0\u0026nbsp;(8.0\u0026ndash;18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e13.0 (9.0\u0026ndash;18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eFertilization rate (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e69.4\u0026nbsp;(56.3\u0026ndash;82.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e70.0\u0026nbsp;(57.1\u0026ndash;81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eCleavage rate (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e100 (100\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e100 (100\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eNumber of day3 embryos extended\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;culture to blastocyst stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e5\u0026nbsp;(3.0\u0026ndash;9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e5\u0026nbsp;(3.0\u0026ndash;9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eHigh quality rate of day3 embryos\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;extended culture to blastocyst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e25.0 (0\u0026ndash;50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e25.0 (0\u0026ndash;50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eUsable blastulation rate on day 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e30.0 (0\u0026ndash;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e30.0 (0\u0026ndash;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.198606271777%\" valign=\"top\"\u003e\n \u003cp\u003eUsable blastulation rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.738675958188153%\" valign=\"top\"\u003e\n \u003cp\u003e41.7(8.3\u0026ndash;63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.473867595818817%\" valign=\"top\"\u003e\n \u003cp\u003e40.0(1.8\u0026ndash;66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.588850174216027%\" valign=\"top\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eScreening for predictive factors\u003c/h2\u003e\n \u003cp\u003eUnivariate logistic regression analysis demonstrated that female age, infertility duration, type of fertilization, COH protocols, presence or absence of PCOS, oocytes retrieved, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, and high-quality rate of Day 3 embryos extended culture to blastocyst stage are associated with the formation of usable blastocysts on Day 5 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multivariate logistic regression analysis showed that the formation of usable blastocysts on Day 5 was associated with female age [P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, odds ratio (OR) 0.970, 95% confidence interval (CI): 0.950\u0026ndash;0.991), type of fertilization (ICSI \u003cem\u003evs\u003c/em\u003e. IVF) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, OR 0.612, 95% CI: 0.474\u0026ndash;0.789), cleavage rate (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, OR 1.040, 95% CI: 1.019\u0026ndash;1.062), number of Day 3 embryos extended culture to the blastocyst stage (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, OR 1.465, 95% CI: 1.404\u0026ndash;1.530), and high-quality rate of Day 3 embryos extended culture to the blastocyst stage (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, OR 1.028, 95% CI: 1.024\u0026ndash;1.032). Although fertilization rate (P\u0026thinsp;=\u0026thinsp;0.06, OR 1.005, 95% CI: 1.000\u0026ndash;1.011) was not statistically related to stable blastocyst formation on Day 5, its inclusion could improve the overall quality of the model.\u003c/p\u003e\n \u003cp\u003eThe equation calculating the probability of usable blastocysts formation on Day 5 was: P\u0026thinsp;=\u0026thinsp;1 / [1\u0026thinsp;+\u0026thinsp;exp(-X)] where X = -4.812365\u0026thinsp;\u0026minus;\u0026thinsp;0.030108 \u0026times; X1\u0026thinsp;\u0026minus;\u0026thinsp;0.491476 \u0026times; X2\u0026thinsp;+\u0026thinsp;0.005328 \u0026times; X3\u0026thinsp;+\u0026thinsp;0.039225 \u0026times; X4\u0026thinsp;+\u0026thinsp;0.381565 \u0026times; X5\u0026thinsp;+\u0026thinsp;0.027819 \u0026times; X6; Where X1 was female age, X2 was the type of fertilization (0 if IVF and 1 if ICSI), X3 was fertilization rate, X4 was cleavage rate, X5 was number of Day 3 embryos extended culture to blastocyst stage, and X6 was high-quality rate of Day 3 embryos extended culture to blastocyst stage.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eNomogram development and evaluation\u003c/h2\u003e\n \u003cp\u003eThe nomogram developed based on this equation is shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. For each cycle, high total points indicated a higher probability of blastocyst formation on Day 5. Additionally, The Hosmer\u0026thinsp;\u0026minus;\u0026thinsp;Lemeshow test suggested that the model was a good fit (P\u0026thinsp;=\u0026thinsp;0.368).\u003c/p\u003e\n \u003cp\u003eResults showed that the AUC of ROC in the training cohort was 0.874 (95% CI: 0.862\u0026ndash;0.887) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) and that in the validation cohort was 0.886 (95% CI: 0.867\u0026ndash;0.905) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), indicating a good discrimination ability of the model. The calibration curves in both cohorts (Figs. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) was close to the ideal diagonal line, reflecting the good accuracy of the model.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we developed a model for predicting the individual probability of usable blastocyst formation on Day 5 based on training cohorts and then the model was validated by validation cohort. The model indicated that female age, type of fertilization, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, and high-quality rate of Day 3 embryos extended culture to blastocyst stage were predictors of usable blastocysts formation on Day 5.\u003c/p\u003e \u003cp\u003eTwo previously study have developed models to predict blastocyst formation on Day 5(Dessolle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), however our prediction model has some advantages compared to the two studies. First, the discrimination of our predict model was better than these previously predicted models. In the present the AUC value of training cohort and validation cohorts were 0.874 (95% CI: 0.862\u0026ndash;0.886) and 0.886 (95% CI: 0.867\u0026ndash;0.905) respectively, showing good discrimination ability of the model; while the AUC values of training cohorts of these previously predicted models were fair performance. Second, the accuracy of our model was better than the model developed by Dessolle L et al., as the calibration curves of training cohort and validation were close to the ideal diagonal line in the present study while the calibration curve of validation cohort was poor performance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in Dessolle L et al. 's study. Third, our prediction model could be used for predicting blastocyst formation in both IVF and ICSI cycles while models of Jin H et al. 's study are only suitable for IVF cycles.\u003c/p\u003e \u003cp\u003ePrevious studies have shown that female age is strongly associated with the clinical outcomes of reproductive medicine (van Loendersloot et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; von Wolff et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Some studies have shown that increased female age has a negative effect on blastocyst formation (Dessolle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; La Marca et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Thomas et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In our nomogram model, a lower female age corresponding to higher points indicated a higher probability of blastocyst formation on Day 5; these results were consistent with the published data. It was well known, abnormalities in the oocyte ooplasm, including organelle dysfunction, altered metabolism, and aberrant gene regulation, would be accumulative with increased female age and progressively undermined oocyte quality (Bebbere et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Oocytes derived from older woman would reduce the ability to repair sperm DNA fragmentation which was negatively correlated with blastocyst formation(Sed\u0026oacute; et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Setti et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, mitochondrial function at morula stage was decreased with maternal ageing, and thus impar morula-to-blastocyst transition(Hashimoto and Morimoto, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A recent study has indicated that advanced maternal age significantly effect on pronuclear, chromatin dynamics, regulation of cell polarity and blastocyst formation rate (Ezoe et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eType of fertilization was also an independent predictor in our model. In the present study, multivariate regression analysis showed that type of fertilization was associated with the formation of usable blastocysts on Day 5 (ICSI \u003cem\u003evs\u003c/em\u003e. IVF) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, OR 0.612, 95% CI: 0.474\u0026ndash;0.789). This result was in accordance with some earlier published studies (Dessolle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Thomas et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Yin et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Thomas et al. indicated that ICSI has a negative effect on blastocyst formation rate (Thomas et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Yin et al. found that either the blastocyst formation rate where blastocyst derived from good morphology embryos or the total blastocyst formation rate in IVF cycles was significantly higher compared to ICSI cycles (Yin et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This phenomenon could be explained that ICSI technology can bypass the selective biological barrier of zona pellucida and may bring abnormal sperm into the oocyte, subsequently affecting embryonic development and blastocyst formation. One study has determined that the ICSI zygotes have many more vacuoles than IVF zygotes, and the presence of vacuoles was related to a lower blastocyst formation rate (Ebner et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, number of Day 3 embryos extended culture to blastocyst stage was significant associated with usable blastocyst formation on Day 5 and was included in the model. Surprisingly, the number of oocytes retrieved was not incorporated into the model. A systematic review and meta-analysis has indicated that the number of oocytes retrieved was positively correlated with the number of high-quality embryo (Vermey et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, two studies that construct prediction models for predicting blastocyst formation have demonstrated that the number of oocytes retrieved was an important predictor of blastocyst formation (Dessolle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The causation of the number of Day 3 embryos extended culture to blastocyst stage rather than the number of oocytes retrieved entered in the model, may be attributed to the fact that not all Day 3 embryos cohort were cultured to blastocyst stage and usually the best one or two embryos were transferred or vitrified in the present study.\u003c/p\u003e \u003cp\u003eThe fertilization rate, cleavage rate, high-quality rate of Day 3 embryos extended culture to blastocyst stage were residual predictors of usable blastocyst formation on Day 5. Higher fertilization rate or cleavage rate usually produce more zygotes and cleaved embryos in fresh cycles, earlier study has demonstrated that the number of zygotes and cleaved embryos have positive effect on clinical outcomes(Hariton et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It was shown that high-quality Day 3 embryos have more potential to develop into blastocysts(Yin et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), in the present study high-quality rate of Day 3 embryos extended culture to blastocyst stage corresponded to a high point; these results were similar to the previously predicted models(Dessolle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, we developed a prediction model with good discrimination and accuracy. Nevertheless, the study has two limitations. First, the present study was a retrospective study, and hence the probability of potential bias could not be excluded. Second, the data analyzed in the present study was from a single center; thus, a multicenter study should be conducted to test the applicability of the model future.\u003c/p\u003e \u003cp\u003eIn conclusion, we developed a model to predict the probability of usable blastocysts formation on Day 5. Variables, including female age, type of fertilization, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, and high-quality rate of Day 3 embryos extended culture to blastocyst stage were entered into this model. This prediction model performed satisfactorily, as confirmed by validation data. Thus, it provides an intuitive and simple tool for predicting the probability of usable blastocyst formation on Day 5, which might be helpful in decreasing the cancellation rate of blastocyst transfer.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIVF\u0026nbsp; \u0026nbsp;In\u0026nbsp;Vitro\u0026nbsp;Fertilization\u003c/p\u003e\n\u003cp\u003eICSI\u0026nbsp; Intracytoplasmic\u0026nbsp;Sperm\u0026nbsp;Injection )，\u003c/p\u003e\n\u003cp\u003eAUC\u0026nbsp; \u0026nbsp;Area\u0026nbsp;Under the\u0026nbsp;Curve\u003c/p\u003e\n\u003cp\u003eROC\u0026nbsp; \u0026nbsp;Receiver\u0026nbsp;Operating\u0026nbsp;Characteristic\u003c/p\u003e\n\u003cp\u003eIVM\u0026nbsp; \u0026nbsp;In\u0026nbsp;Vitro\u0026nbsp;Maturation\u003c/p\u003e\n\u003cp\u003eCOH\u0026nbsp; \u0026nbsp;Controlled Ovarian\u0026nbsp;Hyperstimulation\u003c/p\u003e\n\u003cp\u003eDGC\u0026nbsp; \u0026nbsp;Density\u0026nbsp;Gradient\u0026nbsp;Centrifugation\u003c/p\u003e\n\u003cp\u003eHCG\u0026nbsp; \u0026nbsp;Human\u0026nbsp;Chorionic\u0026nbsp;Gonadotropin\u003c/p\u003e\n\u003cp\u003eSDF\u0026nbsp; \u0026nbsp;Sperm DNA\u0026nbsp;Fragmentation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBMI\u0026nbsp; \u0026nbsp;Body\u0026nbsp;Mass\u0026nbsp;Index\u003c/p\u003e\n\u003cp\u003ePCOS\u0026nbsp; Polycystic\u0026nbsp;Ovary\u0026nbsp;Syndrome\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOR\u0026nbsp; \u0026nbsp;Odds\u0026nbsp;Ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI \u0026nbsp; Confidence Interval\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study followed the Declaration of Helsinki and was performed in accordance with the relevant local guidelines and regulations.\u0026nbsp;The present study was approved by\u0026nbsp;the\u0026nbsp;Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University (Program NO: KY2022-R205), Wenzhou, Zhejiang, China.\u0026nbsp;As a retrospective study, the Ethics Committee of the First Afliated Hospital of Wenzhou Medical University approved the exemption of informed consent, and the datasets were anonymized before their use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003col start=\"8\"\u003e\n \u003cli\u003eZ. conceived of study and drafted the manuscript. D.Y. designed the study. W.J. and J.S. contributed to data acquisition. H.Z. and Z.X. interpreted the data. All authors critically and substantially revised the manuscript and approved the submitted version.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlpha Scientists in Reproductive, M., and Embryology, E.S.I.G.o. \u003cstrong\u003eThe Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting.\u003c/strong\u003e Hum Reprod 2011; 26: 1270-1283.\u003c/li\u003e\n\u003cli\u003eBebbere, D., Coticchio, G., Borini, A., Ledda, S. \u003cstrong\u003eOocyte aging: looking beyond chromosome segregation errors.\u003c/strong\u003e Journal of Assisted Reproduction and Genetics 2022; 39: 793-800.\u003c/li\u003e\n\u003cli\u003eBraga, D.P.A.F., Setti, A.S., Lo Turco, E.G., Cordeiro, F.B., Cabral, E.C., Cortezzi, S.S., Ono, E., Figueira, R.C.S., Eberlin, M.N., Borges, E. \u003cstrong\u003eProtein expression in human cumulus cells as an indicator of blastocyst formation and pregnancy success.\u003c/strong\u003e Journal of Assisted Reproduction and Genetics 2016; 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Reproductive Health 2020; 17.\u003c/li\u003e\n\u003cli\u003eOjosnegros, S., Seriola, A., Godeau, A.L., Veiga, A. \u003cstrong\u003eEmbryo implantation in the laboratory: an update on current techniques.\u003c/strong\u003e Human Reproduction Update 2021; 27: 501-530.\u003c/li\u003e\n\u003cli\u003eSed\u0026oacute;, C.A., Bilinski, M., Lorenzi, D., Uriondo, H., Nobl\u0026iacute;a, F., Longobucco, V., Lagar, E.V., Nodar, F. \u003cstrong\u003eEffect of sperm DNA fragmentation on embryo development: clinical and biological aspects.\u003c/strong\u003e JBRA Assist Reprod 2017.\u003c/li\u003e\n\u003cli\u003eSetti, A.S., Braga, D.P.d.A.F., Provenza, R.R., Iaconelli, A., Borges, E.\u003cstrong\u003e Oocyte ability to repair sperm DNA fragmentation: the impact of maternal age on intracytoplasmic sperm injection outcomes. \u003c/strong\u003eFertility and Sterility 2021; 116: 123-129.\u003c/li\u003e\n\u003cli\u003eThomas, M.R., Sparks, A.E., Ryan, G.L., Van Voorhis, B.J. \u003cstrong\u003eClinical predictors of human blastocyst formation and pregnancy after extended embryo culture and transfer. \u003c/strong\u003eFertility and Sterility 2010: 94: 543-548.\u003c/li\u003e\n\u003cli\u003evan Loendersloot, L.L., van Wely, M., Limpens, J., Bossuyt, P.M.M., Repping, S., van der Veen, F. \u003cstrong\u003ePredictive factors in in vitro fertilization (IVF): a systematic review and meta-analysis. \u003c/strong\u003eHuman Reproduction Update 2010; 16: 577-589.\u003c/li\u003e\n\u003cli\u003eVermey, B.G., Chua, S.J., Zafarmand, M.H., Wang, R., Longobardi, S., Cottell, E., Beckers, F., Mol, B.W., Venetis, C.A., D\u0026apos;Hooghe, T. \u003cstrong\u003eIs there an association between oocyte number and embryo quality? A systematic review and meta-analysis. \u003c/strong\u003eReproductive BioMedicine Online 2019; 39: 751-763.\u003c/li\u003e\n\u003cli\u003evon Wolff, M., Schwartz, A.K., Bitterlich, N., Stute, P., F\u0026auml;h, M. \u003cstrong\u003eOnly women\u0026rsquo;s age and the duration of infertility are the prognostic factors for the success rate of natural cycle IVF.\u003c/strong\u003e Arch Gynecol Obstet 2019; 299: 883-889.\u003c/li\u003e\n\u003cli\u003eWHO. \u003cstrong\u003eWHO laboratory manual for the Examination and processing of human semen FIFTH EDITION. \u003c/strong\u003eWHO Press 2010; 223-225.\u003c/li\u003e\n\u003cli\u003eWong, C.C., Loewke, K.E., Bossert, N.L., Behr, B., De Jonge, C.J., Baer, T.M., Pera, R.A.R. \u003cstrong\u003eNon-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage.\u003c/strong\u003e Nature Biotechnology 2010; 28: 1115-1121.\u003c/li\u003e\n\u003cli\u003eYang L, C.S., Zhang S, Kong X, Gu Y, Lu C, Dai J, Gong F, Lu G, Lin G. Single embryo transfer by Day 3 \u003cstrong\u003etime-lapse selection versus Day 5 conventional morphological selection: a randomized, open-label, non-inferiority trial.\u003c/strong\u003e Human Reproduction 2018; 33: 869-876.\u003c/li\u003e\n\u003cli\u003eYin, H., Jiang, H., He, R., Wang, C., Zhu, J., Luan, K. \u003cstrong\u003eThe effects of fertilization mode, embryo morphology at day 3, and female age on blastocyst formation and the clinical outcomes.\u003c/strong\u003e Systems Biology in Reproductive Medicine 2014; 61: 50-56.\u003c/li\u003e\n\u003cli\u003eYu, R., Jin, H., Huang, X., Lin, J., Wang, P. \u003cstrong\u003eComparison of modified agonist, mild-stimulation and antagonist protocols for in vitro fertilization in patients with diminished ovarian reserve.\u003c/strong\u003e Journal of International Medical Research 2018; 46: 2327-2337.\u003c/li\u003e\n\u003cli\u003eZander-Fox, D.L., Tremellen, K., Lane, M. \u003cstrong\u003eSingle blastocyst embryo transfer maintains comparable pregnancy rates to double cleavage-stage embryo transfer but results in healthier pregnancy outcomes.\u003c/strong\u003e Australian and New Zealand Journal of Obstetrics and Gynaecology 2011; 51: 406-410.\u003c/li\u003e\n\u003cli\u003eZhang, H., Li, Y., Wang, H., Zhou, W., Zheng, Y., Ye, D. \u003cstrong\u003eDoes sperm DNA fragmentation affect clinical outcomes during vitrified-warmed single-blastocyst transfer cycles? A retrospective analysis of 2034 vitrified-warmed single-blastocyst transfer cycles.\u003c/strong\u003e Journal of Assisted Reproduction and Genetics 2022; 39: 1359-1366.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"blastocyst, prediction model, nomogram, extended embryo culture, blastocyst formation","lastPublishedDoi":"10.21203/rs.3.rs-2721055/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2721055/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBlastocyst transfer may cause cycle cancellation due to no blastocyst has developed. Could we develop a model for predicting probability of blastocyst formation on Day 5?\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe model was developed base on 4327 fresh in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) cycles. Univariate logistic regression analysis and multivariate logistic regression analysis were conduct to investigate the relationship between patient and cycle characteristics and the formation of usable blastocysts on Day 5. And the nomogram was developed based on variables selected from multivariate logistic regression analysis. Discrimination and calibration of the model was evaluated by area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration curve.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFemale age, type of fertilization, fertilization rate, cleavage rate, number of Day 3 embryo extended culture to blastocyst stage, high-quality rate of Day 3 embryos extended culture to blastocyst stage, were predictors of usable blastocysts formation on Day 5. Results showed AUC in the training cohort was 0.874 (95% CI 0.862\u0026ndash;0.887) and AUC in validation cohort was 0.886 (95% CI 0.867\u0026ndash;0.905), indicating the good discrimination ability of the model. And the calibration curves in training and validation cohorts were both close to the ideal diagonal line, reflecting good accuracy of the model.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis model provides an intuitive and simple tool for predicting the probability of usable blastocysts formation on Day 5, and it may be helpful to reduce the cancellation rate of blastocyst transfer.\u003c/p\u003e","manuscriptTitle":"Development of nomogram to predict the probability of blastocyst formation on day 5: a retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-04-27 13:28:32","doi":"10.21203/rs.3.rs-2721055/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e6096cb7-c8ce-4b42-879b-88b5073b285b","owner":[],"postedDate":"April 27th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-08-28T06:59:33+00:00","versionOfRecord":[],"versionCreatedAt":"2023-04-27 13:28:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2721055","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2721055","identity":"rs-2721055","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}