Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

BACKGROUND:There is a significant correlation between sperm DNA fragmentation index and fertilization,embryonic development potential,embryo implantation,miscarriage,and offspring safety.However,its clinical reference value is affected by many factors,resulting in extremely limited clinical significance.This study took live birth as the outcome,corrected other confounding factors through propensity score matching,constructed the best clinical cutoff value of sperm DNA fragmentation index and live birth,and conducted internal and external tests on it,which has good predictive value and clinical application efficiency. OBJECTIVE:To investigate the reference threshold and offspring short-term security of in vitro fertilization-embryo transfer sperm DNA fragmentation index based on live birth. METHODS:A total of 1 921 patients who received in vitro fertilization and embryo transfer in Changzhou Maternal and Child Health Area Hospital from May 2019 to May 2021 were selected.On the basis of tendency matching tolerance of 0.02 and propensity score matching of 1:1,540 cases were successfully matched in each live birth group and non-live birth group,and the model group was established.135 patients who received in vitro fertilization and embryo transfer in Nanxishan Hospital of Guangxi Zhuang Autonomous Region were selected as the external validation group.The optimal clinical cutoff value of sperm DNA fragmentation index for live birth was investigated by the receiver operating characteristic curve.The accuracy and clinical application efficacy of the cutoff value were evaluated by restricted cubic spline curve,standard curve,clinical decision curve,clinical impact curve and internal and external validation tests. RESULTS AND CONCLUSION:(1)The DNA fragmentation index of sperm in the non-live birth group was significantly higher than that in the live birth group and had a significant negative correlation with live birth(r=-0.444,P<0.001).(2)Receiver operating characteristic curve results showed that the optimal cut-off value of DNA fragmentation index for live birth was 24.33%;the area under the curve was 0.775(0.746,0.804);the specificity was 72.60%;the sensitivity was 78.90%,and the accuracy was 75.70%.(3)Restricted cubic spline curve fitting the results of Logistic regression showed that when the sperm DNA fragmentation index was greater than 24.57%,the risk of clinical non-live birth increased.(4)The probability of Logistic regression analysis results showed that sperm DNA fragmentation index was a risk factor for live birth[OR(95%CI)=0.916(0.904,0.928),P<0.001],and when sperm DNA fragmentation index was greater than 27.78%,the probability of clinical live birth would be less than 50%.With the increase of sperm DNA fragmentation index by 1 unit,the probability of a live birth fell by 8.4%.(5)Internal and external to the validation of the clinical cutoff value showed that the cutoff point had certain clinical predictive value and accuracy.(6)Clinical decision curve and clinical impact curve results exhibited that the prediction model based on the clinical cut-off value had the maximum clinical net benefit value when the threshold probability was 0.22-0.73,and the ratio of loss to gain within the threshold probability range was always less than 1,which confirmed that the prediction model had good clinical application effectiveness.(7)The results of sperm DNA fragmentation index and offspring short-term security analysis showed that sperm DNA fragmentation index had no significant differences with preterm birth,body weight,deformity and sex.(8)These findings suggest that the optimal clinical cut-off value of sperm DNA fragmentation index for in vitro fertilization-embryo transfer live birth was 24.33%.The established clinical prediction model has good differentiation,accuracy and clinical application effectiveness.Sperm DNA fragmentation index has no significant impact on offspring short-term security,but large samples and long-term follow-up evaluation are still needed.

BACKGROUND:A large number of previous studies have confirmed that a high concentration of metabolites is significantly correlated with embryo quality and clinical outcome,and the theory of silencing embryo development indicates that normally developed embryos maintain a low level of material exchange with the outside world during in vitro culture,while embryos often show abnormal metabolic activity due to stress repair mechanism when DNA damage occurs. OBJECTIVE:To establish and verify an embryo quality prediction model based on the third-day 340 nm absorbance embryo cultures to provide the basis for a more objective and accurate embryo quality assessment. METHODS:269 patients at the Nanxishan Hospital of Guangxi Zhuang Autonomous Region for in vitro fertilization and embryo transplantation from November 2019 to December 2021 were retrospectively analyzed.Among them,on day 3,162 cases who had 873 optimal embryos and 214 high-quality blastocysts were included in the high-quality embryo group.On day 3,107 cases who had 859 non-optimal embryos and 214 non-high-quality blastocysts were included in the non-high-quality embryo group.Lambert-beer law was used to screen out the characteristic wavelength with distinguishing degree between superior and non-superior embryos,analyze its correlation and influence trend with high-quality embryos,and establish the clinical prediction model and validation of absorbance for high-quality and non-high-quality embryos at this wavelength. RESULTS AND CONCLUSION:(1)There was a significant difference in absorbance between high-quality and non-high-quality embryos at 340 nm on day 3(P<0.001),and a negative correlation was found with the formation of high-quality embryos on day 3(r=-0.486,P<0.001).The absorbance of high-quality and non-high-quality blastocyst at 340 nm was significantly different(P<0.05),and was negatively correlated with the formation of high-quality blastocyst(r=-0.642,P<0.001).(2)The optimal cut-off value of absorbance at 340 nm between high-quality and non-high-quality embryos on day 3 was 0.235.The area under the curve was 0.799.Sensitivity was 62.9%.Specificity was 78.0%.Accuracy was 70.5%.The optimum cutoff value of high-quality and non-high-quality blastocysts of absorbance at 340 nm was 0.175.The area under the curve was 0.871.Sensitivity was 74.3%.Specificity was 89.1%.Accuracy was 82.2%.(3)Restricted cubic spline curve analysis showed that when the absorbance of the culture medium at 340 nm was greater than 0.221,there was a significant positive trend on the formation of non-high-quality embryos at day 3,and when the absorbance of the culture medium at 340 nm was greater than 0.160,there was a significant positive trend on the formation of non-high-quality blastocysts.(4)The clinical decision curve and clinical influence curve showed that the absorbance of the culture medium at 340 nm had the maximum clinical net benefit for the prediction models of high-quality embryos and high-quality blastocysts on the third day when the valve probability was 0.18-0.95 and 0.16-1.00,respectively,and the ratio of loss to gain within the valve probability range was always less than 1.It is proven that the prediction model has good efficacy in clinical applications.The results of embryo transfer showed that the absorbance of embryo culture medium at 340 nm in non-pregnant patients was significantly higher than that in clinical pregnancy,biochemical pregnancy and early abortion patients(P<0.05).(5)The high-quality and non-high-quality embryo culture in 340 nm absorbance has a significant difference with correlation.The embryo quality prediction model has a certain clinical value and application effectiveness.The joint embryo morphology evaluation to a certain extent improves the objectivity and accuracy of embryo quality evaluation.

BACKGROUND:Reducing the rate of abnormal fertilization is an effective approach to improving the efficacy of in vitro fertilization and reducing patients'financial strain.However,the current research on abnormal fertilization has focused on exploring the types of prokaryotic nuclei and their generation mechanisms,as well as analyzing embryos formed by abnormal fertilization,chromosomal ploidy and utilization value.There is a lack of clinical prediction models for abnormal fertilization based on retrospective studies. OBJECTIVE:To construct a nomogram model to predict abnormal female factors in in vitro fertilization. METHODS:A total of 5 075 patients undergoing treatment for conventional in vitro fertilization at Nanxishan Hospital of Guangxi Zhuang Autonomous Region from March 2017 to March 2022 were retrospectively analyzed.The male confounders were calibrated on a 1:1 propensity score with a match tolerance of 0.02,and 1 672 cases were successfully matched.According to the Vienna Consensus,patients with≥60%normal fertilization capacity were included in the normal fertilization group(n=836)and those with<60%normal fertilization capacity were included in the abnormal fertilization group(n=836).The model and validation groups were obtained by random sampling at a ratio of 7:3.Factors related to the occurrence of abnormal fertilization following conventional in vitro fertilization in the model group were screened using univariate analysis and the best matching factors were selected using the Least Absolute Shrinkage and Selection Operator(LASSO)and included in a multifactorial forward stepwise Logistic regression to identify their independent influencing factors and plot a nomogram.Finally,the prediction model was validated for discrimination,accuracy and clinical application efficacy using receiver operating characteristic curves,calibration curves,clinical decision curves and clinical impact curves. RESULTS AND CONCLUSION:The univariate analysis indicated the factors influencing the occurrence of abnormal fertilization were age,controlled ovarian hyperstimulation protocol,number of assisted pregnancies,years of infertility,infertility factors,anti-mullerian hormone,sinus follicle count,basal luteinizing hormone,luteinizing hormone concentration on the human chorionic gonadotropin day,and estradiol level on human chorionic gonadotropin injection day(P<0.05).LASSO regression further identified the best matching factors,including age,microstimulation protocol,number of assisted pregnancies,years of infertility,anti-mullerian hormone,luteinizing hormone level on human chorionic gonadotropin injection day,and estradiol level on human chorionic gonadotropin injection day(P<0.05).Multifactorial forward stepwise Logistic regression results showed that age,microstimulation protocol,number of assisted conceptions,years of infertility,anti-mullerian hormone,and estradiol level on human chorionic gonadotropin injection day were independent influencing factors for the occurrence of abnormal fertilization following conventional in vitro fertilization.The receiver operating characteristic curves showed an area under the curve of 0.761(0.746,0.777)for the model group and 0.767(0.733,0.801)for the validation group,indicating that the model has good discrimination.The mean absolute error of the calibration curve was 0.044,and the Hosmer-Lemeshow test indicated that there was no significant difference between the predicted probability of abnormal fertilization and the actual probability of abnormal fertilization(P>0.05),indicating the prediction model has good consistency and accuracy.The clinical decision curves and clinical impact curves showed that the model and validation groups had the maximum net clinical benefit at valve probability values of 0.00-0.52 and 0.00-0.48,respectively,and there was a good clinical application efficacy in this valve probability range.To conclude,the nomogram model has good discrimination and accuracy as well as clinical application efficacy for predicting the occurrence of abnormal fertilization in women undergoing conventional in vitro fertilization based on age,microstimulation protocol,number of assisted conceptions,years of infertility,anti-mullerian hormone,and estradiol level on human chorionic gonadotropin injection day.

BACKGROUND:Unexplained infertility is associated with a higher abortion rate and lower fertilization rate,implantation rate,clinical pregnancy rate and cumulative live birth rate.It is urgent to establish a clinical prediction model related to infertility of unknown cause to solve the problems of clinical prognosis and individualized medical services,and finally achieve the purpose of increasing the cumulative live birth rate of patients with infertility of unknown cause. OBJECTIVE:To construct and verify the prediction model of high-quality blastocyst formation in patients with unexplained infertility during in vitro fertilization. METHODS:A total of 419 patients with unknown infertility who underwent in vitro fertilization in the Assisted Reproduction Department of Changzhou Maternal and Child Health Care Hospital from March 2017 to June 2022 were retrospectively analyzed,including 317 patients with high-quality blastocysts and 102 patients without high-quality blastocysts.A prediction model was established and used as the model group.The model group was sampled 1 000 times by the Bootstrap method as the validation group.Firstly,the univariate analysis was used to screen the influencing factors of high-quality blastocyst formation of unknown infertility,and the best matching factors were selected by the least absolute shrinkage and selection operator(LASSO)algorithm.Multiple factors were included in the progressive Logistic regression to find out the independent influencing factors and draw a column graph.Finally,the subject working curve,calibration curve,clinical decision curve and clinical impact curve were used to verify the differentiation and accuracy of the prediction model as well as the clinical application efficiency. RESULTS AND CONCLUSION:(1)Univariate analysis of the factors influencing the formation of high-quality blastocyst of unknown infertility were age,insemination method,antimullerian hormone level,basal follicle-stimulating hormone level,basal luteinizing hormone level,human chorionic gonadotropin injection day follicle-stimulating hormone level,human chorionic gonadotropin day estradiol level,progesterone level on human chorionic gonadotropin day,the number of high-quality cleavage embryo(day 3)and the number of blastocyst formation(P<0.05).(2)The best matching factors further screened by LASSO regression were age,insemination method,antimullerian hormone level,basal luteinizing hormone level,human chorionic gonadotropin injection day follicle-stimulating hormone level,human chorionic gonadotropin day estradiol level,the number of high-quality cleavage embryo(day 3)and the number of blastocyst formation(P<0.05).Multifactor stepwise Logistic regression results showed that independent influencing factors on the formation of high-quality blastocysts for unexplained infertility were age,insemination method,antimullerian hormone level,the number of high-quality cleavage embryo(day 3),and the number of blastocyst formation.(3)Receiver operating characteristic curve exhibited that the area under the curve was 0.880(0.834,0.926)in the model group and 0.889(0.859,0.918)in the validation group.It showed that the prediction model had good differentiation.The average absolute error of the calibration curve was 0.036,indicating that the model had good accuracy.The Hosmer-Lemeshow test showed that there was no statistical difference between the prediction probability of blastocyst formation and the actual probability of blastocyst formation(P>0.05).The clinical decision curve and clinical impact curve showed that the model group and the validation group had the maximum clinical net benefit when the threshold probability value was(0.16-0.96)and(0.08-0.93),respectively,and had better clinical application efficacy within the threshold probability range.These findings concluded that age,insemination method,antimullerian hormone,the number of high-quality cleavage embryos(day 3),and the number of blastocyst formation were independent factors influencing the formation of the fine blastocyst in patients with unexplained infertility.The clinical prediction model constructed by these factors has good clinical prediction value and clinical application efficiency and can provide a basis for clinical prognosis and intervention as well as the formulation of individual medical programs.

BACKGROUND:The impact of the endometrium's structure and spiral artery blood flow parameters on the pregnancy rate of artificial insemination by husband remains unclear.This study identified the independent factors and constructed a prediction model with good clinical application efficacy after calibration of other confounding factors. OBJECTIVE:To construct and validate a clinical pregnancy prediction model for artificial insemination by husband based on endometrial structure and uterine spiral artery blood flow parameters. METHODS:A retrospective analysis was conducted on 1 299 patients who underwent artificial insemination by husband treatment at Changzhou Maternal and Child Health Hospital from January 2017 to January 2021.The non-pregnancy group consisted of 1 182 patients,while the pregnancy group included 117 patients.Out of these patients,93 cases were successfully matched between the pregnancy and non-pregnancy groups using a 1∶1 propensity score matching method.Single-factor and multi-factor analyses were used to screen the endometrial structure and uterine spiral artery blood flow parameters to determine their influence on artificial insemination by husband outcomes.The optimal cutoff value was established for each independent influencing factor through receiver operating curve analysis and their risk trend affecting artificial insemination by husband pregnancy outcomes was analyzed using a restricted cubic spline.The clinical efficacy of this combined forecast model was tested by using clinical decision curve and clinical influence curve methods. RESULTS AND CONCLUSION:(1)There was no statistical significance in non-endometrial factors between the pregnancy group and the non-pregnancy group,and the data had a good balance by propensity score matching(P>0.05).(2)Single-factor analysis identified several subendometrial parameters as significant influencing factors of artificial insemination by husband pregnancy outcomes,including vascularization index,flow index,vascular flow index,resistance index,pulsatility index,maximum systolic velocity/end-diastolic velocity,thickness of average junction zone and maximum junction zone from the basal endometrium to the outer myometrium inner layer(P<0.05).(3)Multivariate logistic regression analysis revealed that thickness of average junction zone,pulsatility index,and vascular flow index were independent influencing factors of pregnancy outcomes of artificial insemination by husband,vascular flow index>thickness of average junction zone>pulsatility index.(4)Receiver operating characteristic curve analysis indicated that the area under receiver operating characteristic curve of vascular flow index was 0.704(0.629,0.779),and the optimal cutoff value was 6.26;the area under receiver operating characteristic curve of thickness of average junction zone was 0.660(0.582,0.739),and the optimal cutoff value was 6.38;the area under receiver operating characteristic curve of pulsatility index was 0.642(0.563,0.721),and the optimal cutoff value was 1.18.(5)The restricted cubic spline analysis revealed that artificial insemination by husband pregnancy outcomes were significantly positively affected when the vascular flow index was>6.24 or the thickness of average junction zone was≤6.55 mm,while a negative risk was associated with pulsatility index>1.27.(6)The clinical decision curve and clinical influence curve analyses exhibited that the combined prediction model had the maximum clinical net benefit at the threshold probability value of 0.17-0.93,and the ratio of loss to benefit was consistently less than 1 in the threshold probability range,indicating that the model had good clinical efficacy.(7)It is concluded that after adjusting for other confounding factors outside of the endometrium using propensity score matching and multifactorial logistic regression,the thickness of average junction zone,pulsatility index and vascular flow index were independent factors that influenced pregnancy outcomes of artificial insemination by husband.Through determining their optimal cutoff values and assessing their risk trends,it was confirmed that the combined prediction model had good predictive value and clinical efficacy.

Objective:To explore the risk factors and their interation in the incidence of monozygotic twins dur-ing in vitro fertilization-embryo transfer(IVF-ET).Methods:The cohort for this investigation comprised 4537 pa-tients who underwent IVF-ET with single embryo transfer,resulting in live births at Changzhou Maternal and Child Health Care Hospital spanning from January 2011 to December 2021.Among this cohort,76 paitients with monozygotic twins were enrolled in the monozygotic twin group.Employing a 5∶1 propensity score matching strategy,380 patients with monozygotic singletons were enrolled in monozygotic singleton group.Using single fac-tor and Lasso regression analysis to correct for the influencing factors of monozygotic twins,using multiple factor Logistic regression to screen for independent risk factors of monozygotic twins and analyze their impact weights,and then performing multiplication and addition interaction analysis on them.Results:The results of univariate analysis showed that there were statistically significant differences(P＜0.05)between the two groups of patients in terms of age,fertilization method,assisted hatching,embryo type for transfer,embryo transfer method,embryo culture duration,and HCG day estradiol(E2)level.The results of multivariate Logistic regression showed that blas-tocyst transfer(OR 2.847,95％CI 1.559-5.199),frozen-thawed embryo transfer(OR 2.640,95％CI 1.354-5.145),and HCG day E2 level(OR 1.783,95％CI 1.033-3.077)were independent risk factors for monozygotic twins(P＜0.05),demonstrating a hierarchical impact sequence of blastocyst transfer(11.60)＞frozen-thawed embryo transfer(6.54)＞HCG day E2(4.32)level.Notably,there was a significant positive additive interaction between embryo transfer type and HCG day E2 level,with an interaction index(S)of 4.690(95％CI 1.896-11.598),relative excess risk due to interaction(RERI)of 4.128(95％CI 2.236-6.019),and attributable propor-tion due to interaction(AP)of 0.661(95％CI 0.536-0.786).Conclusions:Blastocyst transfer,frozen-thawed embryo transfer,and HCG day E2 level are risk factors for monozygotic twins,and there is a significant positive additive interaction between embryo transfer type and HCG day E2 level.

Objective:To explore the risk factors and their interation in the incidence of monozygotic twins dur-ing in vitro fertilization-embryo transfer(IVF-ET).Methods:The cohort for this investigation comprised 4537 pa-tients who underwent IVF-ET with single embryo transfer,resulting in live births at Changzhou Maternal and Child Health Care Hospital spanning from January 2011 to December 2021.Among this cohort,76 paitients with monozygotic twins were enrolled in the monozygotic twin group.Employing a 5∶1 propensity score matching strategy,380 patients with monozygotic singletons were enrolled in monozygotic singleton group.Using single fac-tor and Lasso regression analysis to correct for the influencing factors of monozygotic twins,using multiple factor Logistic regression to screen for independent risk factors of monozygotic twins and analyze their impact weights,and then performing multiplication and addition interaction analysis on them.Results:The results of univariate analysis showed that there were statistically significant differences(P＜0.05)between the two groups of patients in terms of age,fertilization method,assisted hatching,embryo type for transfer,embryo transfer method,embryo culture duration,and HCG day estradiol(E2)level.The results of multivariate Logistic regression showed that blas-tocyst transfer(OR 2.847,95％CI 1.559-5.199),frozen-thawed embryo transfer(OR 2.640,95％CI 1.354-5.145),and HCG day E2 level(OR 1.783,95％CI 1.033-3.077)were independent risk factors for monozygotic twins(P＜0.05),demonstrating a hierarchical impact sequence of blastocyst transfer(11.60)＞frozen-thawed embryo transfer(6.54)＞HCG day E2(4.32)level.Notably,there was a significant positive additive interaction between embryo transfer type and HCG day E2 level,with an interaction index(S)of 4.690(95％CI 1.896-11.598),relative excess risk due to interaction(RERI)of 4.128(95％CI 2.236-6.019),and attributable propor-tion due to interaction(AP)of 0.661(95％CI 0.536-0.786).Conclusions:Blastocyst transfer,frozen-thawed embryo transfer,and HCG day E2 level are risk factors for monozygotic twins,and there is a significant positive additive interaction between embryo transfer type and HCG day E2 level.

Objective:To explore the risk factors and their interation in the incidence of monozygotic twins dur-ing in vitro fertilization-embryo transfer(IVF-ET).Methods:The cohort for this investigation comprised 4537 pa-tients who underwent IVF-ET with single embryo transfer,resulting in live births at Changzhou Maternal and Child Health Care Hospital spanning from January 2011 to December 2021.Among this cohort,76 paitients with monozygotic twins were enrolled in the monozygotic twin group.Employing a 5∶1 propensity score matching strategy,380 patients with monozygotic singletons were enrolled in monozygotic singleton group.Using single fac-tor and Lasso regression analysis to correct for the influencing factors of monozygotic twins,using multiple factor Logistic regression to screen for independent risk factors of monozygotic twins and analyze their impact weights,and then performing multiplication and addition interaction analysis on them.Results:The results of univariate analysis showed that there were statistically significant differences(P＜0.05)between the two groups of patients in terms of age,fertilization method,assisted hatching,embryo type for transfer,embryo transfer method,embryo culture duration,and HCG day estradiol(E2)level.The results of multivariate Logistic regression showed that blas-tocyst transfer(OR 2.847,95％CI 1.559-5.199),frozen-thawed embryo transfer(OR 2.640,95％CI 1.354-5.145),and HCG day E2 level(OR 1.783,95％CI 1.033-3.077)were independent risk factors for monozygotic twins(P＜0.05),demonstrating a hierarchical impact sequence of blastocyst transfer(11.60)＞frozen-thawed embryo transfer(6.54)＞HCG day E2(4.32)level.Notably,there was a significant positive additive interaction between embryo transfer type and HCG day E2 level,with an interaction index(S)of 4.690(95％CI 1.896-11.598),relative excess risk due to interaction(RERI)of 4.128(95％CI 2.236-6.019),and attributable propor-tion due to interaction(AP)of 0.661(95％CI 0.536-0.786).Conclusions:Blastocyst transfer,frozen-thawed embryo transfer,and HCG day E2 level are risk factors for monozygotic twins,and there is a significant positive additive interaction between embryo transfer type and HCG day E2 level.

Objective:To explore the risk factors and their interation in the incidence of monozygotic twins dur-ing in vitro fertilization-embryo transfer(IVF-ET).Methods:The cohort for this investigation comprised 4537 pa-tients who underwent IVF-ET with single embryo transfer,resulting in live births at Changzhou Maternal and Child Health Care Hospital spanning from January 2011 to December 2021.Among this cohort,76 paitients with monozygotic twins were enrolled in the monozygotic twin group.Employing a 5∶1 propensity score matching strategy,380 patients with monozygotic singletons were enrolled in monozygotic singleton group.Using single fac-tor and Lasso regression analysis to correct for the influencing factors of monozygotic twins,using multiple factor Logistic regression to screen for independent risk factors of monozygotic twins and analyze their impact weights,and then performing multiplication and addition interaction analysis on them.Results:The results of univariate analysis showed that there were statistically significant differences(P＜0.05)between the two groups of patients in terms of age,fertilization method,assisted hatching,embryo type for transfer,embryo transfer method,embryo culture duration,and HCG day estradiol(E2)level.The results of multivariate Logistic regression showed that blas-tocyst transfer(OR 2.847,95％CI 1.559-5.199),frozen-thawed embryo transfer(OR 2.640,95％CI 1.354-5.145),and HCG day E2 level(OR 1.783,95％CI 1.033-3.077)were independent risk factors for monozygotic twins(P＜0.05),demonstrating a hierarchical impact sequence of blastocyst transfer(11.60)＞frozen-thawed embryo transfer(6.54)＞HCG day E2(4.32)level.Notably,there was a significant positive additive interaction between embryo transfer type and HCG day E2 level,with an interaction index(S)of 4.690(95％CI 1.896-11.598),relative excess risk due to interaction(RERI)of 4.128(95％CI 2.236-6.019),and attributable propor-tion due to interaction(AP)of 0.661(95％CI 0.536-0.786).Conclusions:Blastocyst transfer,frozen-thawed embryo transfer,and HCG day E2 level are risk factors for monozygotic twins,and there is a significant positive additive interaction between embryo transfer type and HCG day E2 level.