The Hidden Dangers: Uncovering Risk Factors for Neonatal Hypoglycemia in Assisted Reproductive Technology Babies

The Hidden Dangers: Uncovering Risk Factors for Neonatal Hypoglycemia in Assisted Reproductive Technology Babies | 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 The Hidden Dangers: Uncovering Risk Factors for Neonatal Hypoglycemia in Assisted Reproductive Technology Babies Zhanar Nurgaliyeva, Sevara Ilmuratova, Vyacheslav Lokshin, Lyazzat Manzhuova, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4857683/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: 12 million children are born worldwide after assisted reproductive technologies (ART), but their health remains a significant area of research. Evidence suggests that neonatal hypoglycemia is more common among children conceived through ART. Our study aims to identify risk factors for neonatal hypoglycemia and the possibility of predicting it in ART-conceived children. Methods: In our study, 120 children born after ART were involved. The participants met specific criteria, including being born from a successful ART program resulting in single or multiple pregnancies. Those born using donor oocytes/sperm, intrauterine insemination, or surrogacy were not included. Data for the anamnesis were gathered and analyzed using IBM SPSS Statistics 26. Results: ART-conceived children were at greater risk of being born with neonatal hypoglycemia in cases of multiple pregnancies (OR=14.2; 95% CI: 1.71-117.67), isthmic-cervical insufficiency (OR=10.29; 95% CI: 1.47-71.98), premature birth (OR=13.39; 95% CI: 2.61-68.84), and uterine infertility (OR=10.29; 95% CI: 1.47-71.98). ART children had a higher incidence of neonatal hypoglycemia when they were late preterm (OR=16.95; 95% CI: 3.26-88), with fetal growth restriction (OR=13.38; 95% CI: 2.42-73.8), infantile asphyxia (OR=45; 95% CI: 7.86-257.64), congenital pneumonia (OR=16.96; 95% CI: 3.45-83.3), congenital infection (OR=18; 95% CI: 2.98-108.8), respiratory distress syndrome (OR=16.09; 95% CI: 3.6-72.03), and low or very low birth weight. A regression model that exhibited statistical significance encompassed late prematurity, neonatal asphyxia, congenital infection, and maternal hormone intake before pregnancy. Conclusions: Our study on ART-conceived children highlighted significant risk factors for neonatal hypoglycemia Our developed prognostic model enables early intervention and preventive measures. These findings are valuable for healthcare providers working with ART-conceived children and can improve their care. Trial registration: The protocol was registered on ClinicalTrials.gov (NCT01369355). Date of registration: October 18, 2023; date of enrollment of the first subject: October 23, 2023 assisted reproductive technology children neonatal hypoglycemia risk factors prediction model Figures Figure 1 Figure 2 1. Background Assisted reproductive technology (ART) has become a necessity in today's world, as every 6 couples suffer from infertility. Over 10 million children worldwide and over 35,000 children in Kazakhstan have been born through ART [1] . The development of modern reproductology in Kazakhstan dates back almost 30 years. The first ART laboratory opened in October 1995, and the first "test tube" baby in Kazakhstan was born on July 31, 1996 [2] . Researchers and clinicians worldwide are focusing on the impact of ART on child health, including the endocrine status[3]. In Kazakhstan, in 2022, the first research was launched to study the health status of ART-conceived children. One of the focus areas of this study was the endocrine system, specifically neonatal hypoglycemia (NH), which is significant in pediatric endocrinology. NH is a common metabolic disorder that can affect newborns and potentially cause brain damage. The definition of NH is debated. Our protocol defines it as <2.6 mmol/L. It can occur as a transient condition or due to pathological causes such as hyperinsulinism, metabolic diseases, or perinatal disorders. However, the prevalence of NH varies greatly due to the nonspecific nature of its symptoms and the lack of clear diagnostic criteria. Recent studies have shown that low blood glucose levels can have a significant impact on brain neurons, which has led to discussions about monitoring glycemia in the first few days of a newborn's life and developing strategies for managing newborns with hypoglycemic syndrome. When carbohydrate metabolism is disrupted in the neonatal period, the brain is the first to be affected. Children who experience NH are at increased risk of developing sensorineural impairment and neurological problems [4–6] . A study by Chi-Hong Ho et al. [7] reported that twins who conceived spontaneously had a greater incidence of NH than ART-conceived twins. However, Kouhkan, A. et al. reported that the risk of NH was greater in ART-conceived infants whose mothers had a history of gestational diabetes mellitus than in naturally conceived children [8, 9] . Despite the significant impact of NHs on the development of a child's nervous system, only a few studies have been conducted on this topic, especially concerning children who were conceived through ART. Our study aimed to identify risk factors associated with the development of NH and their predictive value in ART-conceived children. 2. Methods 2.1. Study population We selected the medical records of 96 women who had undergone successful in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatments between 2018 and 2022 at three leading reproductive clinics located in Almaty. We excluded records of those who had used donor oocytes/sperm or embryo recipients, intrauterine insemination, or surrogacy. The medical records of their 120 children were analyzed. 2.2. Statistical analysis Statistics were performed using IBM SPSS statistical software (version 26, SPSS Inc., USA). Comparisons between groups were carried out by Fisher’s exact test and the χ2 test. Odds ratios (ORs) with 95% confidence intervals (CIs) were computed for all maternal somatic, obstetric, and postnatal care history variables in the NH group of ART-conceived children. If the frequency of occurrence of a trait in one of the groups was 0, the Haldane–Enscombe correction was used to calculate the OR. The calculation was performed using an online calculator: https://www.medcalc.org/calc/odds_ratio.php. Binary logistic regression analysis was used to analyze 18 risk factors related to the incidence of NH. The analysis included parameters for which significant differences were found in the comparative study. To examine the impact of risk factors on NH, logistic regression analysis was performed to estimate crude ORs and adjusted odds ratios (adjusted ORs = aORs) with 95% CIs. Nigelkirk's coefficient of determination R2 served as a measure of certainty, indicating that part of the variance could be explained by logistic regression. To assess the diagnostic accuracy of the risk factors for NH, a receiver operating characteristic (ROC) analysis was conducted. ROC curves were generated to evaluate the sensitivity and specificity of the risk factors for distinguishing between patients with and without disease. The area under the curve (AUC) was calculated to determine the specificity and sensitivity of the model. The predictive value of the constructed models was characterized by their sensitivity (Se) and specificity (Sp). The limit of statistical significance was P ≤ 0.05. 2.3. Trial registration: The protocol was registered on ClinicalTrials.gov (NCT01369355). 2.4. Ethics approval This study complied with the Declaration of Helsinki and was approved by the local Ethics Committee of the "Scientific Center of Pediatrics and Pediatric Surgery" on April 13, 2022 (reference number: 2). Informed consent was obtained from all the legally authorized representatives of the research participants before enrollment in the trial. 3. Results We selected 120 ART-conceived children who met our inclusion criteria. According to the medical history, NH was diagnosed in 7.5% (9) ART-conceived children. 3.1. Maternal risk factors We compared the influence of maternal factors on the development of NH in ART-conceived children. The results are presented in Table 1. Based on the obstetric history analysis, children who were born from multiple pregnancies had a 14.2-fold greater risk of NH than did children born from singleton pregnancies (95% CI: 1.71-117.67). Compared with mothers whose mothers did not have isthmic-cervical insufficiency during pregnancy, newborns whose mothers suffered from isthmic-cervical insufficiency during pregnancy had a 10.29-fold greater risk of NH (95% CI: 1.47-71.98). Furthermore, NHs are more prevalent in children whose mothers have a preterm birth, with odds being 13.39 times greater than those in children born at full term (95% CI: 2.61-68.84). Additionally, the odds of developing NH in ART-conceived children increased 10.29 times in women with uterine infertility (95% CI: 1.47-71.98). 3.2. Risk Factors in Pediatric History We compared the frequency of NH-related pediatric factors in ART-conceived children (Table 2). Based on the analysis of pediatric history data, late preterm infants born between 34 and 36 weeks of gestation had a 16.95 times greater risk of NH than full-term infants (95% CI: 3.26-88). The risk of NH in children with fetal growth restriction (FGR) was 13.38 times greater than that in children without FGR (95% CI: 2.42-73.8). NH occurred 5.69 times statistically significantly more often in the group of children with low birth weight (95% CI: 1.4-23.09). Additionally, children with neonatal asphyxia were at a greater risk of NH, with odds increasing 45-fold (95% CI: 7.86-257.64). The risk of developing NH was 16.96 times greater in children with intrauterine pneumonia (95% CI: 3.45-83.3). Similarly, children with a history of intrauterine infection were 18 times more likely to develop NH (95% CI: 2.98–108.8). Furthermore, children with neonatal respiratory distress syndrome were 16.09 times more likely to develop NH (95% CI: 3.6-72.03). However, the study did not find any significant association between pathological hyperbilirubinemia and NH in ART-conceived children. Table 3 compares the frequency of NHs among ART-conceived children in different birth weight groups. After comparing groups based on birth weight and the frequency of NHs among ART-conceived children, it was found that there were statistically significant differences (p = 0.029). The differences were explained by a greater incidence of NH among children with low birth weight (p = 0.045) and very low birth weight (p = 0.013) than among children with normal weight. Development of a prediction model for NH in children with ART-conceived children . We created a prediction model using binary logistic regression to estimate the probability of NH in ART-conceived children. It was based on risk factors identified from the medical history. The relationship observed is defined by equation (1): P = 1 / (1 + e -z ) * 100% z = - 6,79 + 3,15* X LP + 3,63* X IA + 2,5* X CI + 3,25* X E+P (1) where P – the probability of NH in ART-conceived children (%), X LP –late preterm (0 – absence, 1 – presence), X IA – neonatal asphyxia (0 – absence, 1 – presence), X CI –congenital infection (0 – absence, 1 – presence), X E+P –taking estrogen and progesterone before pregnancy (0 – absence, 1 – presence). The resulting regression model was statistically significant ( p <0.001). Based on the Nigelkirk coefficient of determination, the model explained 60.6% of the observed variance in the presence of NH in ART-conceived children. According to the regression coefficients, certain factors, such as late preterm birth, infantile asphyxia, congenital infection, and a history of taking estrogen and progesterone before pregnancy, were found to be directly associated with the probability of NH in ART-conceived children. The characteristics of each factor are presented in Table 4. Figure 1 compares the values of the adjusted odds ratios with 95% CIs for the studied factors included in model (1). Figure 1 – Forest plot showing ORs with 95% CI for the predictors of NG in ART-conceived children. The cutoff value of the logistic function P was determined using the ROC curve analysis. The resulting curve is shown in Figure 2. Figure 2 – ROC-curve characterizing the dependence of NG in ART-conceived children on the values of P function (1) The area under the ROC curve was 0.9±0.09 (95% CI: 0.74–1). The threshold value of the logistic function (1) at the cutoff point was 25%. P values greater than or equal to 25% indicated a high risk of NH in ART-conceived children, and P values <25% indicated a low risk of NH in ART-conceived children. The sensitivity and specificity of this model (1) at this threshold were 88.9% and 97.3%, respectively. 4. Discussion The key findings of this study are as follows: (i) based on the history of maternal risk factors, ART-conceived children were at greater risk for NH in cases of multiple pregnancies, isthmic-cervical insufficiency, premature birth, and uterine infertility; (ii) based on the history of pediatric risk factors, the risk of NH in ART-conceived children was greater in the case of late prematurity of children, FGR, neonatal asphyxia, congenital pneumonia, congenital infection, respiratory distress syndrome of newborns, and low and very low birth weight; (iii) when constructing a statistically significant regression model taking into account all statistically significant risk factors, it was found that late preterm birth, infantile asphyxia, congenital infection and a history of taking estrogen and progesterone before pregnancy were directly associated with the probability of NH in ART-conceived children and may help predict the development of this condition. When analyzing maternal risk factors in ART-conceived children with NH, multiple pregnancies (95% CI: 4.25-118.16), isthmic-cervical insufficiency (95% CI: 1.47-71.98), preterm birth (95% CI: 1.56-27.99), and uterine infertility (95% CI: 1.47-71.98) had significant influences. Several previous studies have confirmed that multiple pregnancies and preterm births are associated with a high incidence of NH [10–14] . The presence of isthmic-cervical insufficiency usually has a direct connection with premature birth, which is associated with NH. In addition, a role for uterine infertility has been discovered, but further study is needed to better understand this relationship. Interestingly, in our study, maternal gestational diabetes was not a risk factor for NH in children. When analyzing pediatric risk factors, it was found that the odds of NH were 16.95 times greater among late preterm infants born between 34 and 36 weeks of gestation than among full-term infants (95% CI: 3.26-88). Additionally, the risk of NHs with a history of FGR increased by 13.38 times (95% CI: 2.42-73.8), neonatal asphyxia by 45 times (95% CI: 7.86-257.64), congenital pneumonia by 16.96 times (95% CI: 3.45-83.3), congenital infection by 18 times (95% CI: 2.98-108.8), respiratory distress syndrome by 16.09 times (95% CI: 3.6-72.03). Additionally, NHs were more common in low birth weight (p=0.045) and very low birth weight (p=0.013) infants than in normal-weight infants. Previous studies have also revealed the influence of prematurity, low birth weight, neonatal respiratory distress syndrome, and neonatal asphyxia on NH [15–17] . In addition, some studies have noted that children with FGR have a high risk of NH [18–20] . According to the regression model, the most significant factors were late prematurity [aOR: 23,38 (2,04-267,81)], neonatal asphyxia [aOR: 37,88 (1,49-963,68)], and congenital infection [aOR: 12,16 (0,82-180,83)]. Additionally, a history of taking estrogen and progesterone before pregnancy was also identified as a statistically significant risk factor [aOR:25,66 (1,41-465,921)]. It is important to note that placental progesterone and estrogens play a crucial role in controlling insulin sensitivity during pregnancy. These steroid hormones can lead to pancreatic hypertrophy, with progesterone reducing insulin-stimulated glucose uptake and stimulating appetite and fat deposition, while estrogen increases systemic insulin sensitivity [21] . Progesterone may have toxic effects on pancreatic β-cells by triggering apoptosis through an oxidative stress-dependent mechanism [22] . Furthermore, abnormal levels of steroid hormones during pregnancy have been strongly linked to the development of GDM [23] . Therefore, it is reasonable to conclude that there is a logical correlation between mothers’ use of estrogen and progesterone before pregnancy and the increased risk of NH in ART-conceived children. Multiple births, premature births, and low birth weight in children have been shown to increase the risk of NH. These risk factors are commonly observed in ART-conceived children. Consequently, it is logical to observe a higher prevalence of NH in ART-conceived children, which aligns with the findings of previous studies [8, 9] . Today, the use of ART allows for the identification and management of these risks, enabling healthcare professionals to provide appropriate counseling for women and pediatric care for their offspring. However, further research is essential to evaluate these findings and develop effective preventive strategies. Limitations: Several limitations of our study should be considered. First, because there are no registries of ART children in Kazakhstan, the size of this cohort could not have been representative of the wider population. Second, our study is limited by a short follow-up period due to the complexity and cost of longitudinal studies, which makes it impossible to assess the long-term effects of NH on the nervous system of ART-conceived children. Third, we assessed only some of the risk factors; however, infertility itself, drugs used for ovulation induction, pathology of the placenta, and other diseases may influence the incidence of NH in offspring. Fourth, this study included only a sample from Kazakhstan. It is necessary to expand the geography of studies to increase the sample size and increase the applicability of findings to other ethnic groups. 5. Conclusion In conclusion, while research on the risk factors for NH in ART-conceived children is limited, our study emphasizes the importance of addressing this specific group. Our retrospective study of ART-conceived children allowed us to identify significant risk factors for NH, including late prematurity, neonatal asphyxia, congenital infection, and maternal estrogen and progesterone intake before pregnancy. The developed prognostic model allows us to predict the probability of NH, providing an opportunity for early intervention and appropriate preventive measures. With ART becoming an increasingly utilized tool, it is essential to consider prognostic risks and intervene promptly to address potential health concerns in children. The findings from this study are valuable for reproductologists, neonatologists, and pediatricians because they provide valuable insights that can improve the care of ART-conceived children. Further research in this field has the potential to improve pregnancy and birth outcomes, as well as reduce the occurrence of newborn complications. Abbreviations ART: Assisted reproductive technology NG: neonatal hypoglycemia IVF: in vitro fertilization ICSI: intracytoplasmic sperm injection ORs: Odds ratios CIs: confidence intervals ROC: Receiver operating characteristic AUC: The area under the curve Declarations Ethics declarations Ethics approval and consent to participate This study complies with the Declaration of Helsinki and was approved by the local Ethics Committee of the "Scientific Center of Pediatrics and Pediatric Surgery" on April 13, 2022 (reference number: 2). The informed consent was obtained from all legally authorized representatives of research participants before enrolment in the trial. Consent for publication Not applicable. Availability of data and materials Datasets are available on request. The individual participants' data that underline the results reported in this article after deidentification (text, tables, figures, and appendices) will be made available to other researchers who provide a methodologically sound proposal for individual participants' data meta-analysis. The proposal should be directed to [email protected] . To gain access, data requesters need to sign a data access agreement with the Scientific Center of Pediatrics and Pediatric Surgery because intellectual property rights to the research results are collective and because the patent holder is the Scientific Center of Pediatrics and Pediatric Surgery. The study protocol will be available at ClinicalTrials.gov (NCT01369355). No end date. Competing interests The authors declare no competing interests. Funding No funding was received. Author Contributions ZN: Data Curation, Formal analysis, Investigation, Writing - Review & Editing. SI: Data Curation, Formal analysis, Investigation, Writing - Original Draft. VL: Conceptualization, Methodology, Data Curation, Resources, Writing - Review & Editing, Supervision. LM: Methodology, Project administration, Writing - Review & Editing, Funding acquisition, Resources. RS: Writing - Review & Editing. Acknowledgments We would like to thank all clinical and scientific staff of the International Clinical Center for Reproductology "PERSONA", Institute of Reproductive Medicine for their help with the recruitment of patients and the Scientific Center of Pediatrics and Pediatric Surgery for conducting clinical trial. References Lokshin VN, Ilmuratova SKH. COGNITIVE DEVELOPMENT AND NEUROPSYCHIC HEALTH OF CHILDREN CONCEIVED BY ASSISTED REPRODUCTIVE TECHNOLOGIES. Akusherstvo i Ginekologiya (Russian Federation). 2022;2022:31–6. Ilmuratova S, Manzhuova L, Lokshin V. Health status of children born after assisted reproductive technologies. Reproductive Medicine. 2022; 1(50):15–22. Lokshin VN, Ilmuratova SKH. COGNITIVE DEVELOPMENT AND NEUROPSYCHIC HEALTH OF CHILDREN CONCEIVED BY ASSISTED REPRODUCTIVE TECHNOLOGIES. Akusherstvo i Ginekologiya (Russian Federation). 2022;2022:31–6. Edwards T, Alsweiler JM, Gamble GD, Griffith R, Lin L, McKinlay CJD, et al. Neurocognitive Outcomes at Age 2 Years After Neonatal Hypoglycemia in a Cohort of Participants From the hPOD Randomized Trial. JAMA Netw Open. 2022;5:e2235989–e2235989. Shah R, Harding J, Brown J, Mckinlay C. Neonatal Glycaemia and Neurodevelopmental Outcomes: A Systematic Review and Meta-Analysis. Neonatology. 2019;115:116–26. Qiao LX, Wang J, Yan JH, Xu SX, Wang H, Zhu WY, et al. Follow-up study of neurodevelopment in 2-year-old infants who had suffered from neonatal hypoglycemia. BMC Pediatr. 2019;19:1–6. Ho CH, Peng FS, Chen HF, Lien YR, Chen SU, Yang YS. Twin Pregnancies Conceived by Assisted Reproductive Technology: Maternal and Perinatal Outcomes. Taiwan J Obstet Gynecol. 2005;44:332–7. Kouhkan A, Khamseh ME, Pirjani R, Moini A, Arabipoor A, Maroufizadeh S, et al. Obstetric and perinatal outcomes of singleton pregnancies conceived via assisted reproductive technology complicated by gestational diabetes mellitus: a prospective cohort study. BMC Pregnancy Childbirth. 2018;18. Kouhkan A, Hosseini R, Baradaran HR, Arabipoor A, Cheraghi R, Moini A, et al. Early Postpartum Glucose Intolerance, Metabolic Syndrome and Gestational Diabetes Mellitus Determinants after Assisted Conception: A Prospective Cohort Study. Int J Fertil Steril. 2022;16:172. Stomnaroska O, Petkovska E, Jancevska S, Danilovski D. Neonatal Hypoglycemia: Risk Factors and Outcomes. Pril (Makedon Akad Nauk Umet Odd Med Nauki). 2017;38:97–101. Bromiker R, Perry A, Kasirer Y, Einav S, Klinger G, Levy-Khademi F. Early neonatal hypoglycemia: incidence of and risk factors. A cohort study using universal point of care screening. The Journal of Maternal-Fetal & Neonatal Medicine. 2019;32:786–92. Ogunyemi D, Friedman P, Betcher K, Whitten A, Sugiyama N, Qu L, et al. Obstetrical correlates and perinatal consequences of neonatal hypoglycemia in term infants. The Journal of Maternal-Fetal & Neonatal Medicine. 2017;30:1372–7. D K SH. Pedunculated submucosal lipoleiomyoma projecting into endocervical canal. Journal of Medical Science And clinical Research. 2019;7. Mitchell NA, Grimbly C, Rosolowsky ET, O’Reilly M, Yaskina M, Cheung PY, et al. Incidence and Risk Factors for Hypoglycemia During Fetal-to-Neonatal Transition in Premature Infants. Front Pediatr. 2020;8:460807. Yunarto Y, Sarosa GI. Risk factors of neonatal hypoglycemia. Paediatr Indones. 2019;59:252–6. Qayum DS. Neonatal hypoglycaemia: Risk factors and clinical profile. Journal of Medical Science And clinical Research. 2019;7. Ansari A, Savaskar S V., Tamboli M, N. PS. Study of incidence, risk factors and immediate outcome of hypoglycemia in neonates admitted in NICU. Int J Contemp Pediatrics. 2023;10:1303–9. Manandhar T, Prashad B, Nath Pal M. Risk Factors for Intrauterine Growth Restriction and Its Neonatal Outcome. Gynecology & Obstetrics. 2018;08. Rattanasakol T, Kitsommart R. Factors associated with neonatal hyperinsulinemic hypoglycemia, a case-control study. Journal of Pediatric Endocrinology and Metabolism. 2024;37:243–9. Skovrlj R, Marks SD, Rodd C. Frequency and etiology of persistent neonatal hypoglycemia using the more stringent 2015 Pediatric Endocrine Society hypoglycemia guidelines. Paediatr Child Health. 2019;24:263–9. Babović IR, Dotlić J, Sparić R, Jovandaric MZ, Andjić M, Marjanović Cvjetićanin M, et al. Gestational Diabetes Mellitus and Antenatal Corticosteroid Therapy—A Narrative Review of Fetal and Neonatal Outcomes. Journal of Clinical Medicine 2023, Vol 12, Page 323. 2022;12:323. Nunes VA, Portioli-Sanches EP, Rosim MP, Araujo MS, Praxedes-Garcia P, Valle MMR, et al. Progesterone induces apoptosis of insulin-secreting cells: insights into the molecular mechanism. J Endocrinol. 2014;221:273–84. Yang N, Zhang W, Ji C, Ge J, Zhang X, Li M, et al. Metabolic alteration of circulating steroid hormones in women with gestational diabetes mellitus and the related risk factors. Front Endocrinol (Lausanne). 2023;14:1196935. Tables Table 1 Frequency of maternal factors influencing neonatal hypoglycemia in ART-conceived children. Maternal risk factors NH in medical history P value OR; 95% CI Presence (n=9) Absence (n=111) Smoking 1(11.1) 4(3.6) 0.327 3.34; 0.33-33.55 Multiple pregnancy 8(88.9) 40(36) 0.003* 14.2; 1.71-117.67 C-section 8(88.9) 76(68.5) 0.276 3.68; 0.44-30.6 Arterial hypertension 0(0) 5(4.5) 0.990 1.02; 0.05-19.87 Thyroid disease 1(11.1) 24(21.6) 0.683 0.45; 0.05-3.8 Chronic pyelonephritis 4(44.4) 19(17.1) 0.067 3.87; 0.95-15.78 GDM 0(0) 3(2.7) 0.752 1.63; 0.08-33.99 Anemia of pregnancy 4(44.4) 35(31.5) 0.470 1.74; 0.44-6.87 Preeclampsia 2(22.2) 8(7.2) 0.164 3.68; 0.65-20.71 Insuficiencia istmicocervical 2(22.2) 3(2.7) 0.045* 10.29; 1.47-71.98 Premature delivery 7(77.8) 23(20.7) 0.001* 13.39; 2.61-68.84 ART in medical history 6(66.7) 48(43.2) 0.296 2.63; 0.63-11.03 ICSI 4(44.4) 69(62.2) 0.311 0.49; 0.12-1.92 FET 7(77.8) 84(75.7) 1.000 1.13; 0.22-5.74 Taking progesterone before pregnancy 1(11.1) 20(18) 1.000 0.57; 0.07-4.81 Taking estrogen and progesterone before pregnancy 7(77.8) 50(45) 0.084 4.27; 0.85-21.48 Secondary infertility 3(33.3) 59(53.2) 0.312 0.44; 0.11-1.85 Tubal infertility 7(77.8) 65(58.6) 0.313 2.48; 0.49-12.47 Uterine infertility 2(22.2) 3(2.7) 0.045* 10.29; 1.47-71.98 Taking estrogen and progesterone during pregnancy 7(77.8) 58(52.3) 0.177 3.2; 0.64-16.08 Note: Data are expressed as n (%). P values were determined by using the Chi-square test or Fisher’s exact test for categorical data. OR = odds ratio; CI = confidence interval. Abbreviations: GDM - gestational diabetes mellitus; ART - assisted reproductive technology; ICSI - intracytoplasmic sperm injection; FET - frozen embryo transfer . * indicates statistical significance at p < 0.05. Table 2 - Frequency of pediatric factors influencing neonatal hypoglycemia in ART-conceived children. Pediatric risk factors NH in medical history P value OR; 95% CI Presence (n=9) Absence (n=111) Late preterm 7(77.8) 19(17.1) <0.001* 16.95; 3.26-88 Low birth weight 5(55.6) 20(18) 0.019* 5.69; 1.4-23.09 FGR 3(33.3) 4(3.6) 0.009* 13.38; 2.42-73.8 Infantile asphyxia 5(55.6) 3(2.7) <0.001* 45; 7.86-257.64 Congenital pneumonia 4(44.4) 5(4.5) 0.002* 16.96; 3.45-83.3 Congenital infection 3(33.3) 3(2.7) 0.005* 18; 2.98-108.8 Respiratory distress syndrome 5(55.6) 8(7.2) 0.001* 16.09; 3.6-72.03 Pathologic hyperbilirubinemia 6(66.7) 37(33.3) 0.068 4; 0.95-16.9 Note: Data are expressed as n (%). P values were determined by using the Chi-square test or Fisher’s exact test for categorical data. OR = odds ratio; CI = confidence interval. Abbreviations: FGR - fetal growth restriction. * indicates statistical significance at p < 0.05. Table 3 - Comparison of birth weight groups according to neonatal hypoglycemia status among ART-conceived children. Classification of prematurity categorized by birth weight P value Normal weight 2500-3999 g High birth weight (>4000 g) LBW VLBW ELBW NH(n=9) 3 (33.3) 1 (11.1) 4 (44.4) 1 (11.1) 0 (0) 0.029* p 1-3 =0.045* p 1-4 =0.013* Note: Data are expressed as n (%). P values were determined by using the Chi-square test or Fisher’s exact test for categorical data. Abbreviations: LBW - low birth weight (<2500 g = 1500–2499 g); VLBW - very low birth weight (<1500 = 1000–1499 g); ELBW - extremely low birth weight (<1000 g). * indicates statistical significance at p < 0.05. Table 4 –Relationship between predictors of model (1) and the probability of NG in ART-conceived children. Predictors Unadjusted Adjusted COR; 95% CI p AOR; 95% CI p Late preterm 16.95; 3.26-88 <0.001* 23.38; 2.04-267.81 0.011* Infantile asphyxia 45; 7.86-257.64 <0.001* 37.88; 1.49-963.68 0.028* Congenital infection 18; 2.98-108.8 0.005* 12.16; 0.82-180.83 0.070 Taking estrogen and progesterone before pregnancy 4.27; 0.85-21.48 0.084 25.66; 1.41-465.921 0.028* Note: P values were determined by using the Chi-square test or Fisher’s exact test for categorical data. Abbreviations: COR – crude odds ratio; AOR – adjusted odds ratio; CI - confidence interval. * indicates statistical significance at p < 0.05. 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. 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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-4857683","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":339285570,"identity":"9207eb6e-3974-4432-ade9-e1fa4195f50f","order_by":0,"name":"Zhanar Nurgaliyeva","email":"","orcid":"","institution":"Asfendiyarov Kazakh National Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhanar","middleName":"","lastName":"Nurgaliyeva","suffix":""},{"id":339285571,"identity":"d7e012d1-2e37-4af5-a47b-e676e591f15f","order_by":1,"name":"Sevara Ilmuratova","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACNnZk3gcMEWxamMGUAZhknIEQwQOQtTDzIERwAz5m7jTpipo/cgbHDzB/tvm1TZ6PmYHxw8ccfA7j3SZ55piBscGZBDbp3L7bhm3MDMySM7cR0NLAZpA4syGBjTm35zYjUAtIkJCWf0At/Q+YP1v23LYnTktjm0Fiv0QCgzTDj9uJxGjZbNnYZ2zML/GwTbK34XZyGzNjM16/yLf3brzZ8E1Ojo0/+fCHH39u285vbz744SMeLUiAsYGBsQ3KIAH8IUXxKBgFo2AUjBQAAJp0RT8DdwnXAAAAAElFTkSuQmCC","orcid":"","institution":"Kazakhstan Medical University “KSPH”","correspondingAuthor":true,"prefix":"","firstName":"Sevara","middleName":"","lastName":"Ilmuratova","suffix":""},{"id":339285572,"identity":"29b8beba-f4b4-48d0-ba32-5385c8f2a756","order_by":2,"name":"Vyacheslav Lokshin","email":"","orcid":"","institution":"International Clinical Centre of Reproduction “PERSONA”","correspondingAuthor":false,"prefix":"","firstName":"Vyacheslav","middleName":"","lastName":"Lokshin","suffix":""},{"id":339285573,"identity":"33ecb508-bd38-44fc-8b69-470c47fdf530","order_by":3,"name":"Lyazzat Manzhuova","email":"","orcid":"","institution":"Scientific Center of Pediatrics and Pediatric Surgery","correspondingAuthor":false,"prefix":"","firstName":"Lyazzat","middleName":"","lastName":"Manzhuova","suffix":""},{"id":339285574,"identity":"d38f6ea5-092e-4775-b04d-ae78b1dfc8c8","order_by":4,"name":"Roza Seisebayeva","email":"","orcid":"","institution":"Asfendiyarov Kazakh National Medical University","correspondingAuthor":false,"prefix":"","firstName":"Roza","middleName":"","lastName":"Seisebayeva","suffix":""}],"badges":[],"createdAt":"2024-08-04 16:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4857683/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4857683/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66116984,"identity":"6de3f810-39ad-452d-9ed5-b0a735be9025","added_by":"auto","created_at":"2024-10-08 00:51:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":107734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eForest plot showing ORs with 95% CI for the predictors of NG in ART-conceived children.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4857683/v1/e7c51763d4e7b888cc0435e2.png"},{"id":66116982,"identity":"36c0e3a3-1874-42aa-af82-86382ce0e2a7","added_by":"auto","created_at":"2024-10-08 00:51:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":116043,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eROC-curve characterizing the dependence of NG in ART-conceived children on the values of P function (1)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4857683/v1/0607cb2942aa61d96a460843.png"},{"id":74466950,"identity":"14be9a79-7772-4f55-b836-8a36183ea85a","added_by":"auto","created_at":"2025-01-22 14:24:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":837063,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4857683/v1/c428c2d1-f137-4d29-a4d4-cca7025080bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Hidden Dangers: Uncovering Risk Factors for Neonatal Hypoglycemia in Assisted Reproductive Technology Babies","fulltext":[{"header":"1. Background","content":"\u003cp\u003eAssisted\u0026nbsp;reproductive technology\u0026nbsp;(ART) has become a necessity in today\u0026apos;s world, as every 6 couples suffer from infertility. Over 10 million children worldwide and over 35,000 children in Kazakhstan have been born through ART\u003cspan lang=\"EN-US\"\u003e[1]\u003c/span\u003e. The development of modern reproductology in Kazakhstan dates back almost 30 years. The first ART laboratory opened in October 1995, and the first \u0026quot;test tube\u0026quot; baby in Kazakhstan was born on July 31, 1996\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e[2]\u003c/span\u003e. Researchers and clinicians worldwide are focusing on the impact of ART on child health, including the endocrine status[3]. In Kazakhstan, in 2022, the first research was launched to study the health status of ART-conceived children. One of the focus areas of this study was the endocrine system, specifically neonatal hypoglycemia (NH), which is significant in pediatric endocrinology.\u003c/p\u003e\n\u003cp\u003eNH\u0026nbsp;is a common metabolic disorder that can affect newborns and potentially cause brain damage. The definition of NH is debated. Our protocol defines it as \u0026lt;2.6 mmol/L.\u0026nbsp;It\u0026nbsp;can occur\u0026nbsp;as a transient condition or due to pathological causes such as hyperinsulinism, metabolic diseases, or perinatal disorders.\u0026nbsp;However, the prevalence of NH varies greatly due to the\u0026nbsp;nonspecific\u0026nbsp;nature of its symptoms and the lack of clear diagnostic criteria.\u0026nbsp;Recent studies have shown that low blood glucose levels can have a significant impact on brain neurons, which has led to discussions about monitoring glycemia in the first few days of a newborn\u0026apos;s life and developing strategies for managing newborns with hypoglycemic syndrome. When carbohydrate metabolism is disrupted in the neonatal period, the brain is the first to be affected. Children who experience NH are at increased risk of developing sensorineural impairment and neurological problems\u003cspan lang=\"EN-US\"\u003e[4\u0026ndash;6]\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eA study by Chi-Hong Ho et al.\u003cspan lang=\"EN-US\"\u003e[7]\u003c/span\u003e reported\u0026nbsp;that twins\u0026nbsp;who\u0026nbsp;conceived spontaneously had a\u0026nbsp;greater\u0026nbsp;incidence of NH\u0026nbsp;than\u0026nbsp;ART-conceived twins.\u0026nbsp;However, Kouhkan, A. et al.\u0026nbsp;reported\u0026nbsp;that the risk of NH was\u0026nbsp;greater\u0026nbsp;in ART-conceived\u0026nbsp;infants whose mothers had a history of gestational diabetes mellitus\u0026nbsp;than in\u0026nbsp;naturally conceived children\u003cspan lang=\"EN-US\"\u003e[8, 9]\u003c/span\u003e. Despite the significant impact of\u0026nbsp;NHs\u0026nbsp;on the development of a child\u0026apos;s nervous system, only a few studies\u0026nbsp;have been\u0026nbsp;conducted on this topic, especially concerning children who were conceived through ART.\u003c/p\u003e\n\u003cp\u003eOur study aimed to identify risk factors associated with the development of NH and their predictive value in ART-conceived children.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cem\u003e2.1.\u0026nbsp;Study population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe selected the medical records of 96 women who had undergone successful in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatments between 2018 and 2022 at three leading reproductive clinics located in Almaty. We excluded records of those who had used donor oocytes/sperm or embryo recipients, intrauterine insemination, or surrogacy.\u0026nbsp;The medical records of their 120 children were analyzed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2.\u0026nbsp;Statistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStatistics were performed using IBM SPSS statistical software (version 26, SPSS Inc., USA). Comparisons between groups were carried out by Fisher\u0026rsquo;s exact test and the \u0026chi;2 test. Odds ratios (ORs) with 95% confidence intervals (CIs) were computed for all maternal somatic, obstetric, and postnatal care history variables in the NH group of ART-conceived children. If the frequency of occurrence of a trait in one of the groups was 0, the Haldane\u0026ndash;Enscombe correction was used to calculate the OR. The calculation was performed using an online calculator: https://www.medcalc.org/calc/odds_ratio.php. Binary logistic regression analysis was used to analyze 18 risk factors related to the incidence of NH. The analysis included parameters for which significant differences were found in the comparative study. To examine the impact of risk factors on NH, logistic regression analysis was performed to estimate crude ORs and adjusted odds ratios (adjusted ORs\u0026thinsp;=\u0026thinsp;aORs) with 95% CIs. Nigelkirk\u0026apos;s coefficient of determination R2 served as a measure of certainty, indicating that part of the variance could be explained by logistic regression. To assess the diagnostic accuracy of the risk factors for NH, a receiver operating characteristic (ROC) analysis was conducted. ROC curves were generated to evaluate the sensitivity and specificity of the risk factors for distinguishing between patients with and without disease. The area under the curve (AUC) was calculated to determine the specificity and sensitivity of the model. The predictive value of the constructed models was characterized by their sensitivity (Se) and specificity (Sp). The limit of statistical significance was P \u0026le; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Trial registration:\u003c/em\u003e The protocol was registered on ClinicalTrials.gov (NCT01369355).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.4.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ethics approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u0026nbsp;complied\u0026nbsp;with the \u003cem\u003eDeclaration of Helsinki\u003c/em\u003e and was approved by the local Ethics Committee of the \u0026quot;Scientific Center of Pediatrics and Pediatric Surgery\u0026quot; on April 13, 2022 (reference number: 2). Informed consent was obtained from all the legally authorized representatives of the research participants before enrollment in the trial.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eWe selected 120 ART-conceived children who met our inclusion criteria. According to\u0026nbsp;the medical history, NH was diagnosed in 7.5% (9) ART-conceived children.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.1.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Maternal risk factors\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe compared the\u0026nbsp;influence\u0026nbsp;of maternal\u0026nbsp;factors\u0026nbsp;on the development of NH in\u0026nbsp;ART-conceived children. The results are presented in Table 1.\u003c/p\u003e\n\u003cp\u003eBased on\u0026nbsp;the\u0026nbsp;obstetric history analysis, children who were born from multiple\u0026nbsp;pregnancies had\u0026nbsp;a 14.2-fold greater\u0026nbsp;risk of NH\u0026nbsp;than did\u0026nbsp;children born from singleton\u0026nbsp;pregnancies\u0026nbsp;(95% CI: 1.71-117.67).\u0026nbsp;Compared with mothers whose mothers did not have isthmic-cervical insufficiency during pregnancy, newborns\u0026nbsp;whose mothers suffered from isthmic-cervical insufficiency during pregnancy had a 10.29-fold greater\u0026nbsp;risk of NH (95% CI: 1.47-71.98). Furthermore,\u0026nbsp;NHs are\u0026nbsp;more prevalent in children whose mothers\u0026nbsp;have\u0026nbsp;a preterm birth, with odds being 13.39 times\u0026nbsp;greater\u0026nbsp;than\u0026nbsp;those\u0026nbsp;in children born at full term (95% CI: 2.61-68.84). Additionally, the odds of developing NH in\u0026nbsp;ART-conceived children\u0026nbsp;increased 10.29 times in women\u0026nbsp;with uterine infertility\u0026nbsp;(95% CI: 1.47-71.98).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Risk Factors in Pediatric History\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe compared the frequency of\u0026nbsp;NH-related\u0026nbsp;pediatric factors in\u0026nbsp;ART-conceived children\u0026nbsp;(Table 2).\u003c/p\u003e\n\u003cp\u003eBased on the analysis of\u0026nbsp;pediatric\u0026nbsp;history data, late preterm infants born between 34\u0026nbsp;and\u0026nbsp;36 weeks of gestation had a 16.95 times\u0026nbsp;greater\u0026nbsp;risk of NH\u0026nbsp;than\u0026nbsp;full-term infants (95% CI: 3.26-88).\u0026nbsp;The risk of NH in children with \u003cem\u003efetal growth restriction (FGR)\u003c/em\u003e was 13.38 times\u0026nbsp;greater\u0026nbsp;than\u0026nbsp;that in\u0026nbsp;children without \u003cem\u003eFGR\u003c/em\u003e (95% CI: 2.42-73.8). NH occurred 5.69 times statistically significantly more often in the group of children with low birth weight (95% CI: 1.4-23.09). Additionally, children with neonatal asphyxia were at a\u0026nbsp;greater\u0026nbsp;risk of NH, with odds increasing 45-fold (95% CI: 7.86-257.64). The risk of developing NH was 16.96 times\u0026nbsp;greater\u0026nbsp;in children with intrauterine pneumonia (95% CI: 3.45-83.3). Similarly, children with a history of intrauterine infection were 18 times more likely to develop NH (95% CI: 2.98\u0026ndash;108.8). Furthermore, children with neonatal respiratory distress syndrome\u0026nbsp;were\u0026nbsp;16.09 times\u0026nbsp;more likely to develop\u0026nbsp;NH (95% CI: 3.6-72.03). However, the study did not find any significant association between pathological hyperbilirubinemia and NH in\u0026nbsp;ART-conceived children.\u003c/p\u003e\n\u003cp\u003eTable 3 compares the frequency of\u0026nbsp;NHs among\u0026nbsp;ART-conceived children\u0026nbsp;in\u0026nbsp;different birth weight groups.\u003c/p\u003e\n\u003cp\u003eAfter comparing groups based on birth weight and the frequency of\u0026nbsp;NHs among\u0026nbsp;ART-conceived children, it was found that there were statistically significant differences (p = 0.029). The differences were explained by a\u0026nbsp;greater\u0026nbsp;incidence of NH among children with low birth weight (p = 0.045) and very low birth weight (p = 0.013)\u0026nbsp;than among\u0026nbsp;children with normal weight.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDevelopment of a prediction model for NH in children with ART-conceived children\u003c/em\u003e\u003cem\u003e.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe created a prediction model using binary logistic regression to estimate the probability of NH in ART-conceived children. It was based on risk factors identified from the medical history. The relationship observed is defined by equation (1):\u003c/p\u003e\n\u003cp\u003eP = 1 / (1 + e\u003csup\u003e-z\u003c/sup\u003e) * 100%\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ez = - 6,79 + 3,15* X\u003csub\u003eLP\u003c/sub\u003e+ 3,63* X\u003csub\u003eIA\u003c/sub\u003e + 2,5* X\u003csub\u003eCI\u003c/sub\u003e + 3,25* X\u003csub\u003eE+P\u003c/sub\u003e\u0026nbsp; (1)\u003c/p\u003e\n\u003cp\u003ewhere P \u0026ndash; the probability of NH in ART-conceived children (%), X\u003csub\u003eLP\u003c/sub\u003e \u0026ndash;late preterm (0 \u0026ndash; absence, 1 \u0026ndash; presence), X\u003csub\u003eIA\u003c/sub\u003e \u0026ndash; neonatal asphyxia (0 \u0026ndash; absence, 1 \u0026ndash; presence), X\u003csub\u003eCI\u003c/sub\u003e\u0026nbsp; \u0026ndash;congenital infection (0 \u0026ndash; absence, 1 \u0026ndash; presence), X\u003csub\u003eE+P\u003c/sub\u003e\u0026nbsp; \u0026ndash;taking estrogen and progesterone before pregnancy (0 \u0026ndash; absence, 1 \u0026ndash; presence).\u003c/p\u003e\n\u003cp\u003eThe resulting regression model was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). Based on the Nigelkirk coefficient of determination, the model explained\u0026nbsp;60.6% of the observed variance in the presence of\u0026nbsp;NH in ART-conceived children.\u0026nbsp;According to the regression coefficients, certain factors,\u0026nbsp;such as late preterm birth, infantile asphyxia, congenital infection, and a history of taking estrogen and progesterone before pregnancy,\u0026nbsp;were found to be directly associated with the\u0026nbsp;probability\u0026nbsp;of NH in ART-conceived children.\u0026nbsp;The characteristics of each factor are presented in Table 4.\u003c/p\u003e\n\u003cp\u003eFigure 1 compares the values of the adjusted odds ratios with 95% CIs for the studied factors included in model (1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure 1 \u0026ndash; Forest plot showing ORs with 95% CI for the predictors of NG in ART-conceived children.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe cutoff\u0026nbsp;value of the logistic function P was determined using the ROC curve analysis. The resulting curve is shown in Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure 2 \u0026ndash; ROC-curve characterizing the dependence of NG in ART-conceived children on the values of P function (1)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe area under the ROC curve was 0.9\u0026plusmn;0.09 (95% CI: 0.74\u0026ndash;1). The threshold value of the logistic function (1) at the cutoff point was 25%. P values greater than or equal to 25% indicated a high risk of NH in ART-conceived children, and P values \u0026lt;25% indicated a low risk of NH in ART-conceived children. The sensitivity and specificity of this model (1) at this threshold were 88.9% and 97.3%, respectively.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe key findings of this study are as follows:\u0026nbsp;(i) based on the history of maternal risk factors, ART-conceived children were at\u0026nbsp;greater\u0026nbsp;risk for NH in cases of multiple pregnancies, isthmic-cervical insufficiency, premature birth, and uterine infertility;\u0026nbsp;(ii) based on the history of pediatric risk factors, the risk of NH in\u0026nbsp;ART-conceived children\u0026nbsp;was\u0026nbsp;greater\u0026nbsp;in the case of late prematurity of children, FGR, neonatal asphyxia, congenital pneumonia, congenital infection, respiratory distress syndrome of newborns,\u0026nbsp;and\u0026nbsp;low and very low birth weight; (iii) when constructing a statistically significant regression model taking into account all statistically significant risk factors, it was\u0026nbsp;found\u0026nbsp;that late preterm\u0026nbsp;birth, infantile asphyxia, congenital infection and a history of taking estrogen and progesterone before pregnancy\u0026nbsp;were\u0026nbsp;directly associated with the probability of NH in\u0026nbsp;ART-conceived children\u0026nbsp;and may help predict the development of this condition.\u003c/p\u003e\n\u003cp\u003eWhen analyzing maternal risk factors in ART-conceived children with NH, multiple pregnancies (95% CI: 4.25-118.16), isthmic-cervical insufficiency (95% CI: 1.47-71.98), preterm birth (95% CI: 1.56-27.99), and uterine infertility (95% CI: 1.47-71.98) had significant\u0026nbsp;influences.\u003c/p\u003e\n\u003cp\u003eSeveral\u0026nbsp;previous studies have confirmed that multiple pregnancies and preterm births are associated with a high incidence of NH\u003cspan lang=\"EN-US\"\u003e[10\u0026ndash;14]\u003c/span\u003e. The presence of isthmic-cervical insufficiency usually has a direct connection with premature birth, which is associated with NH. In addition, a role for uterine infertility has been discovered,\u0026nbsp;but\u0026nbsp;further study\u0026nbsp;is needed\u0026nbsp;to better understand\u0026nbsp;this\u0026nbsp;relationship. Interestingly, in our study, maternal gestational diabetes\u0026nbsp;was not\u0026nbsp;a risk factor for NH in children.\u003c/p\u003e\n\u003cp\u003eWhen\u0026nbsp;analyzing pediatric\u0026nbsp;risk factors, it was found that the odds of NH were 16.95 times\u0026nbsp;greater\u0026nbsp;among late preterm infants born between 34 and 36 weeks of gestation\u0026nbsp;than among\u0026nbsp;full-term infants (95% CI: 3.26-88).\u0026nbsp;Additionally, the risk of\u0026nbsp;NHs\u0026nbsp;with a history of FGR increased by 13.38 times (95% CI: 2.42-73.8), neonatal asphyxia by 45 times (95% CI: 7.86-257.64), congenital pneumonia by 16.96 times (95% CI: 3.45-83.3), congenital infection by 18 times (95% CI: 2.98-108.8), respiratory distress syndrome by 16.09 times (95% CI: 3.6-72.03). Additionally,\u0026nbsp;NHs were\u0026nbsp;more common in low birth weight (p=0.045) and very low birth weight (p=0.013) infants\u0026nbsp;than in\u0026nbsp;normal-weight infants.\u003c/p\u003e\n\u003cp\u003ePrevious studies have also\u0026nbsp;revealed\u0026nbsp;the influence of prematurity, low birth weight, neonatal respiratory distress syndrome, and neonatal asphyxia on NH\u003cspan lang=\"EN-US\"\u003e[15\u0026ndash;17]\u003c/span\u003e. In addition, some studies have noted that children with FGR have a high risk of NH\u003cspan lang=\"EN-US\"\u003e[18\u0026ndash;20]\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eAccording to the\u0026nbsp;regression model, the most significant factors were late prematurity [aOR: 23,38\u0026nbsp;(2,04-267,81)], neonatal asphyxia [aOR: 37,88\u0026nbsp;(1,49-963,68)],\u0026nbsp;and\u0026nbsp;congenital infection [aOR: 12,16\u0026nbsp;(0,82-180,83)]. Additionally, a history of taking estrogen and progesterone before pregnancy was also identified as a statistically significant risk factor [aOR:25,66\u0026nbsp;(1,41-465,921)]. It is important to note that placental progesterone and estrogens play a crucial role in controlling insulin sensitivity during pregnancy. These steroid hormones can lead to pancreatic hypertrophy, with progesterone reducing insulin-stimulated glucose uptake and stimulating appetite and fat deposition, while estrogen increases systemic insulin sensitivity\u003cspan lang=\"EN-US\"\u003e[21]\u003c/span\u003e. Progesterone may have toxic effects on pancreatic \u0026beta;-cells by triggering apoptosis through an oxidative stress-dependent mechanism\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e[22]\u003c/span\u003e. Furthermore, abnormal levels of steroid hormones during pregnancy have been strongly linked to the development of GDM\u003cspan lang=\"EN-US\"\u003e[23]\u003c/span\u003e. Therefore, it is reasonable to conclude that there is a logical correlation between\u0026nbsp;mothers\u0026rsquo;\u0026nbsp;use of estrogen and progesterone before pregnancy and the increased risk of NH in ART-conceived children.\u003c/p\u003e\n\u003cp\u003eMultiple births, premature births, and low birth weight in children have been shown to increase the risk of NH. These risk factors are commonly\u0026nbsp;observed\u0026nbsp;in ART-conceived children. Consequently, it is logical to observe a higher prevalence of NH in ART-conceived children, which aligns with the findings of previous studies\u003cspan lang=\"EN-US\"\u003e[8, 9]\u003c/span\u003e. Today, the use of ART allows for the identification and management of these risks, enabling healthcare professionals to provide appropriate counseling for women and pediatric care for their offspring. However, further research is essential to evaluate these findings and develop effective preventive strategies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimitations:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations of our study should be considered. First, because there are no registries of ART children in Kazakhstan, the size of this cohort could not have been representative of the wider population. Second, our study is limited by a short follow-up period due to the complexity and cost of longitudinal studies, which makes it impossible to assess the long-term effects of NH on the nervous system of ART-conceived children. Third, we assessed only some of the risk factors; however, infertility itself, drugs used for ovulation induction, pathology of the placenta, and other diseases may influence the incidence of NH in offspring. Fourth, this study included only a sample from Kazakhstan. It is necessary to expand the geography of studies to increase the sample size and increase the applicability of findings to other ethnic groups.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, while research on the risk factors for NH in ART-conceived children is limited, our study emphasizes the importance of addressing this specific group. Our retrospective study of ART-conceived children allowed us to identify significant risk factors for NH, including late prematurity, neonatal asphyxia, congenital infection, and maternal estrogen and progesterone intake before pregnancy. The developed prognostic model allows us to predict the probability of NH, providing an opportunity for early intervention and appropriate preventive measures. With ART becoming an increasingly utilized tool, it is essential to consider prognostic risks and intervene promptly to address potential health concerns in children. The findings from this study are valuable for reproductologists, neonatologists, and pediatricians because they provide valuable insights that can improve the care of ART-conceived children. Further research in this field has the potential to improve pregnancy and birth outcomes, as well as reduce the occurrence of newborn complications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eART:\u003c/strong\u003e Assisted reproductive technology\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNG:\u003c/strong\u003e neonatal hypoglycemia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIVF:\u003c/strong\u003e in vitro fertilization \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICSI:\u003c/strong\u003e intracytoplasmic sperm injection\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eORs:\u003c/strong\u003e Odds ratios\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCIs:\u003c/strong\u003e confidence intervals\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eROC:\u003c/strong\u003e Receiver operating characteristic\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUC:\u003c/strong\u003e The area under the curve\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study complies with the Declaration of Helsinki and was approved by the local Ethics Committee of the \u0026quot;Scientific Center of Pediatrics and Pediatric Surgery\u0026quot; on April 13, 2022 (reference number: 2). The informed consent was obtained from all legally authorized representatives of research participants before enrolment in the trial.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatasets are available on request. The individual participants\u0026apos; data that underline the results reported in this article after deidentification (text, tables, figures, and appendices) will be made available to other researchers who provide a methodologically sound proposal for individual participants\u0026apos; data meta-analysis. The proposal should be directed to [email protected]. To gain access, data requesters need to sign a data access agreement with the Scientific Center of Pediatrics and Pediatric Surgery because intellectual property rights to the research results are collective and because the patent holder is the Scientific Center of Pediatrics and Pediatric Surgery. The study protocol will be available at ClinicalTrials.gov (NCT01369355). No end date.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\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\u003eNo funding was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZN:\u003c/strong\u003e Data Curation, Formal analysis, Investigation, Writing - Review \u0026amp; Editing. \u003cstrong\u003eSI:\u003c/strong\u003e Data Curation, Formal analysis, Investigation, Writing - Original Draft. \u003cstrong\u003eVL:\u003c/strong\u003e Conceptualization, Methodology, Data Curation, Resources, Writing - Review \u0026amp; Editing, Supervision. \u003cstrong\u003eLM:\u003c/strong\u003e Methodology, Project administration, Writing - Review \u0026amp; Editing, Funding acquisition, Resources. \u003cstrong\u003eRS:\u003c/strong\u003e Writing - Review \u0026amp; Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all clinical and scientific staff of the International Clinical Center for Reproductology \u0026quot;PERSONA\u0026quot;, Institute of Reproductive Medicine for their help with the recruitment of patients and the Scientific Center of Pediatrics and Pediatric Surgery for conducting clinical trial.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLokshin VN, Ilmuratova SKH. COGNITIVE DEVELOPMENT AND NEUROPSYCHIC HEALTH OF CHILDREN CONCEIVED BY ASSISTED REPRODUCTIVE TECHNOLOGIES. Akusherstvo i Ginekologiya (Russian Federation). 2022;2022:31\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eIlmuratova S, Manzhuova L, Lokshin V. Health status of children born after assisted reproductive technologies. Reproductive Medicine. 2022; 1(50):15\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eLokshin VN, Ilmuratova SKH. COGNITIVE DEVELOPMENT AND NEUROPSYCHIC HEALTH OF CHILDREN CONCEIVED BY ASSISTED REPRODUCTIVE TECHNOLOGIES. Akusherstvo i Ginekologiya (Russian Federation). 2022;2022:31\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eEdwards T, Alsweiler JM, Gamble GD, Griffith R, Lin L, McKinlay CJD, et al. Neurocognitive Outcomes at Age 2 Years After Neonatal Hypoglycemia in a Cohort of Participants From the hPOD Randomized Trial. JAMA Netw Open. 2022;5:e2235989\u0026ndash;e2235989.\u003c/li\u003e\n\u003cli\u003eShah R, Harding J, Brown J, Mckinlay C. Neonatal Glycaemia and Neurodevelopmental Outcomes: A Systematic Review and Meta-Analysis. Neonatology. 2019;115:116\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eQiao LX, Wang J, Yan JH, Xu SX, Wang H, Zhu WY, et al. Follow-up study of neurodevelopment in 2-year-old infants who had suffered from neonatal hypoglycemia. BMC Pediatr. 2019;19:1\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eHo CH, Peng FS, Chen HF, Lien YR, Chen SU, Yang YS. Twin Pregnancies Conceived by Assisted Reproductive Technology: Maternal and Perinatal Outcomes. Taiwan J Obstet Gynecol. 2005;44:332\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eKouhkan A, Khamseh ME, Pirjani R, Moini A, Arabipoor A, Maroufizadeh S, et al. Obstetric and perinatal outcomes of singleton pregnancies conceived via assisted reproductive technology complicated by gestational diabetes mellitus: a prospective cohort study. BMC Pregnancy Childbirth. 2018;18.\u003c/li\u003e\n\u003cli\u003eKouhkan A, Hosseini R, Baradaran HR, Arabipoor A, Cheraghi R, Moini A, et al. Early Postpartum Glucose Intolerance, Metabolic Syndrome and Gestational Diabetes Mellitus Determinants after Assisted Conception: A Prospective Cohort Study. Int J Fertil Steril. 2022;16:172.\u003c/li\u003e\n\u003cli\u003eStomnaroska O, Petkovska E, Jancevska S, Danilovski D. Neonatal Hypoglycemia: Risk Factors and Outcomes. Pril (Makedon Akad Nauk Umet Odd Med Nauki). 2017;38:97\u0026ndash;101.\u003c/li\u003e\n\u003cli\u003eBromiker R, Perry A, Kasirer Y, Einav S, Klinger G, Levy-Khademi F. Early neonatal hypoglycemia: incidence of and risk factors. A cohort study using universal point of care screening. The Journal of Maternal-Fetal \u0026amp; Neonatal Medicine. 2019;32:786\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eOgunyemi D, Friedman P, Betcher K, Whitten A, Sugiyama N, Qu L, et al. Obstetrical correlates and perinatal consequences of neonatal hypoglycemia in term infants. The Journal of Maternal-Fetal \u0026amp; Neonatal Medicine. 2017;30:1372\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eD K SH. Pedunculated submucosal lipoleiomyoma projecting into endocervical canal. Journal of Medical Science And clinical Research. 2019;7.\u003c/li\u003e\n\u003cli\u003eMitchell NA, Grimbly C, Rosolowsky ET, O\u0026rsquo;Reilly M, Yaskina M, Cheung PY, et al. Incidence and Risk Factors for Hypoglycemia During Fetal-to-Neonatal Transition in Premature Infants. Front Pediatr. 2020;8:460807.\u003c/li\u003e\n\u003cli\u003eYunarto Y, Sarosa GI. Risk factors of neonatal hypoglycemia. Paediatr Indones. 2019;59:252\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eQayum DS. Neonatal hypoglycaemia: Risk factors and clinical profile. Journal of Medical Science And clinical Research. 2019;7.\u003c/li\u003e\n\u003cli\u003eAnsari A, Savaskar S V., Tamboli M, N. PS. Study of incidence, risk factors and immediate outcome of hypoglycemia in neonates admitted in NICU. Int J Contemp Pediatrics. 2023;10:1303\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eManandhar T, Prashad B, Nath Pal M. Risk Factors for Intrauterine Growth Restriction and Its Neonatal Outcome. Gynecology \u0026amp; Obstetrics. 2018;08.\u003c/li\u003e\n\u003cli\u003eRattanasakol T, Kitsommart R. Factors associated with neonatal hyperinsulinemic hypoglycemia, a case-control study. Journal of Pediatric Endocrinology and Metabolism. 2024;37:243\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eSkovrlj R, Marks SD, Rodd C. Frequency and etiology of persistent neonatal hypoglycemia using the more stringent 2015 Pediatric Endocrine Society hypoglycemia guidelines. Paediatr Child Health. 2019;24:263\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eBabović IR, Dotlić J, Sparić R, Jovandaric MZ, Andjić M, Marjanović Cvjetićanin M, et al. Gestational Diabetes Mellitus and Antenatal Corticosteroid Therapy\u0026mdash;A Narrative Review of Fetal and Neonatal Outcomes. Journal of Clinical Medicine 2023, Vol 12, Page 323. 2022;12:323.\u003c/li\u003e\n\u003cli\u003eNunes VA, Portioli-Sanches EP, Rosim MP, Araujo MS, Praxedes-Garcia P, Valle MMR, et al. Progesterone induces apoptosis of insulin-secreting cells: insights into the molecular mechanism. J Endocrinol. 2014;221:273\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003eYang N, Zhang W, Ji C, Ge J, Zhang X, Li M, et al. Metabolic alteration of circulating steroid hormones in women with gestational diabetes mellitus and the related risk factors. Front Endocrinol (Lausanne). 2023;14:1196935.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u0026nbsp;Table 1 Frequency of maternal factors influencing neonatal\u0026nbsp;hypoglycemia\u0026nbsp;in\u0026nbsp;ART-conceived children.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\" rowspan=\"2\"\u003e\n \u003cp\u003eMaternal risk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.17817014446228%\" colspan=\"2\"\u003e\n \u003cp\u003eNH in medical history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" rowspan=\"2\"\u003e\n \u003cp\u003eOR; 95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.44237918215613%\"\u003e\n \u003cp\u003ePresence (n=9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.55762081784387%\"\u003e\n \u003cp\u003eAbsence (n=111)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e1(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e4(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e3.34; 0.33-33.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eMultiple pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e8(88.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e40(36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e14.2; 1.71-117.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\" valign=\"top\"\u003e\n \u003cp\u003eC-section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e8(88.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e76(68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e3.68; 0.44-30.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eArterial hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e5(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e1.02; 0.05-19.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eThyroid disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e1(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e24(21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e0.45; 0.05-3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eChronic pyelonephritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e19(17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e3.87; 0.95-15.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e3(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e1.63; 0.08-33.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eAnemia of pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e35(31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e1.74; 0.44-6.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e2(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e8(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e3.68; 0.65-20.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eInsuficiencia istmicocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e2(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e3(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.045*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e10.29; 1.47-71.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003ePremature delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e7(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e23(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e13.39; 2.61-68.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eART in medical history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e6(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e48(43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e2.63; 0.63-11.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eICSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e69(62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\"\u003e\n \u003cp\u003e0.49; 0.12-1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eFET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e7(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e84(75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e1.13; 0.22-5.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eTaking progesterone before pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e1(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e20(18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e0.57; 0.07-4.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eTaking estrogen and progesterone before pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e7(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e50(45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e4.27; 0.85-21.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eSecondary infertility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e59(53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e0.44; 0.11-1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eTubal infertility\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e7(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e65(58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e2.48; 0.49-12.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\"\u003e\n \u003cp\u003eUterine infertility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\"\u003e\n \u003cp\u003e2(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\"\u003e\n \u003cp\u003e3(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.045*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e10.29; 1.47-71.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\" valign=\"top\"\u003e\n \u003cp\u003eTaking estrogen and progesterone during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.348314606741575%\" valign=\"top\"\u003e\n \u003cp\u003e7(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.829855537720707%\" valign=\"top\"\u003e\n \u003cp\u003e58(52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e3.2; 0.64-16.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData are expressed as\u003c/em\u003e\u003cem\u003e\u0026nbsp;n (%).\u0026nbsp;P values were determined by using the Chi-square test or Fisher\u0026rsquo;s exact test for categorical data. OR = odds ratio; CI = confidence interval.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: GDM - gestational diabetes mellitus;\u003c/em\u003e\u003cem\u003e\u0026nbsp;ART\u003c/em\u003e\u003cem\u003e\u0026nbsp;- assisted reproductive technology;\u003c/em\u003e\u003cem\u003e\u0026nbsp;ICSI - intracytoplasmic sperm injection; FET - frozen embryo transfer\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e* indicates statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 - Frequency of\u0026nbsp;pediatric\u0026nbsp;factors influencing neonatal hypoglycemia in\u0026nbsp;ART-conceived children.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.398073836276083%\" rowspan=\"2\"\u003e\n \u003cp\u003ePediatric risk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.17817014446228%\" colspan=\"2\"\u003e\n \u003cp\u003eNH in medical history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" rowspan=\"2\"\u003e\n \u003cp\u003eOR; 95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.62686567164179%\"\u003e\n \u003cp\u003ePresence (n=9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.37313432835821%\"\u003e\n \u003cp\u003eAbsence (n=111)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003eLate preterm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\" valign=\"top\"\u003e\n \u003cp\u003e7(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\" valign=\"top\"\u003e\n \u003cp\u003e19(17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\" valign=\"top\"\u003e\n \u003cp\u003e16.95; 3.26-88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003eLow birth weight\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\"\u003e\n \u003cp\u003e5(55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\"\u003e\n \u003cp\u003e20(18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e0.019*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\"\u003e\n \u003cp\u003e5.69; 1.4-23.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003eFGR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\" valign=\"top\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\" valign=\"top\"\u003e\n \u003cp\u003e4(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\" valign=\"top\"\u003e\n \u003cp\u003e13.38; 2.42-73.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003eInfantile asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\" valign=\"top\"\u003e\n \u003cp\u003e5(55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\" valign=\"top\"\u003e\n \u003cp\u003e3(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\" valign=\"top\"\u003e\n \u003cp\u003e45; 7.86-257.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003eCongenital pneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\" valign=\"top\"\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\" valign=\"top\"\u003e\n \u003cp\u003e5(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\" valign=\"top\"\u003e\n \u003cp\u003e16.96; 3.45-83.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003eCongenital infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\" valign=\"top\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\" valign=\"top\"\u003e\n \u003cp\u003e3(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\" valign=\"top\"\u003e\n \u003cp\u003e18; 2.98-108.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory distress syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\" valign=\"top\"\u003e\n \u003cp\u003e5(55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\" valign=\"top\"\u003e\n \u003cp\u003e8(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\" valign=\"top\"\u003e\n \u003cp\u003e16.09; 3.6-72.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.437299035369776%\" valign=\"top\"\u003e\n \u003cp\u003ePathologic hyperbilirubinemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.382636655948552%\" valign=\"top\"\u003e\n \u003cp\u003e6(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.70418006430868%\" valign=\"top\"\u003e\n \u003cp\u003e37(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.57556270096463%\" valign=\"top\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.90032154340836%\" valign=\"top\"\u003e\n \u003cp\u003e4; 0.95-16.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData are expressed as\u003c/em\u003e\u003cem\u003e\u0026nbsp;n (%).\u0026nbsp;P values were determined by using the Chi-square test or Fisher\u0026rsquo;s exact test for categorical data. OR = odds ratio; CI = confidence interval.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u0026nbsp;\u003c/em\u003e\u003cem\u003eFGR\u0026nbsp;- fetal growth restriction.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e* indicates statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 - Comparison of birth weight groups\u0026nbsp;according to\u0026nbsp;neonatal hypoglycemia\u0026nbsp;status among\u0026nbsp;ART-conceived children.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.561983471074381%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.24793388429752%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eClassification of prematurity categorized by birth weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.1900826446281%\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.470588235294116%\"\u003e\n \u003cp\u003eNormal weight 2500-3999 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.470588235294116%\"\u003e\n \u003cp\u003eHigh birth weight (\u0026gt;4000 g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.529411764705882%\"\u003e\n \u003cp\u003eLBW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eVLBW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.529411764705882%\"\u003e\n \u003cp\u003eELBW\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.561983471074381%\"\u003e\n \u003cp\u003eNH(n=9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.1900826446281%\" valign=\"top\"\u003e\n \u003cp\u003e3 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.1900826446281%\" valign=\"top\"\u003e\n \u003cp\u003e1 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\" valign=\"top\"\u003e\n \u003cp\u003e4 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e1 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.1900826446281%\"\u003e\n \u003cp\u003e0.029*\u003c/p\u003e\n \u003cp\u003ep\u003csub\u003e1-3\u003c/sub\u003e=0.045*\u003c/p\u003e\n \u003cp\u003ep\u003csub\u003e1-4\u003c/sub\u003e=0.013*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData are expressed as\u003c/em\u003e\u003cem\u003e\u0026nbsp;n (%).\u0026nbsp;P values were determined by using the Chi-square test or Fisher\u0026rsquo;s exact test for categorical data.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u0026nbsp;\u003c/em\u003e\u003cem\u003eLBW\u0026nbsp;- low birth weight\u0026nbsp;(\u0026lt;2500 g = 1500\u0026ndash;2499 g); VLBW - very low birth weight (\u0026lt;1500 = 1000\u0026ndash;1499 g); ELBW -\u0026nbsp;extremely low birth weight (\u0026lt;1000 g).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e* indicates statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 \u0026ndash;Relationship between predictors of model (1) and the probability of NG in\u0026nbsp;ART-conceived children.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePredictors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003eCOR; 95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.481927710843372%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.80722891566265%\" valign=\"top\"\u003e\n \u003cp\u003eAOR; 95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.386837881219904%\" valign=\"top\"\u003e\n \u003cp\u003eLate preterm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.74317817014446%\" valign=\"top\"\u003e\n \u003cp\u003e16.95; 3.26-88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e23.38; 2.04-267.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.038523274478331%\" valign=\"top\"\u003e\n \u003cp\u003e0.011*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.386837881219904%\" valign=\"top\"\u003e\n \u003cp\u003eInfantile asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.74317817014446%\" valign=\"top\"\u003e\n \u003cp\u003e45; 7.86-257.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e37.88; 1.49-963.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.038523274478331%\" valign=\"top\"\u003e\n \u003cp\u003e0.028*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.386837881219904%\" valign=\"top\"\u003e\n \u003cp\u003eCongenital infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.74317817014446%\" valign=\"top\"\u003e\n \u003cp\u003e18; 2.98-108.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" valign=\"top\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e12.16; 0.82-180.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.038523274478331%\" valign=\"top\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.386837881219904%\" valign=\"top\"\u003e\n \u003cp\u003eTaking estrogen and progesterone before pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.74317817014446%\" valign=\"top\"\u003e\n \u003cp\u003e4.27; 0.85-21.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.643659711075442%\" valign=\"top\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.187800963081862%\" valign=\"top\"\u003e\n \u003cp\u003e25.66; 1.41-465.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.038523274478331%\" valign=\"top\"\u003e\n \u003cp\u003e0.028*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eP values were determined by using the Chi-square test or Fisher\u0026rsquo;s exact test for categorical data.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u0026nbsp;\u003c/em\u003e\u003cem\u003eCOR \u0026ndash; crude odds ratio; AOR \u0026ndash; adjusted odds ratio; CI - confidence interval.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e* indicates statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\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":"assisted reproductive technology, children, neonatal hypoglycemia, risk factors, prediction model","lastPublishedDoi":"10.21203/rs.3.rs-4857683/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4857683/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e 12 million children are born worldwide after assisted reproductive technologies (ART), but their health remains a significant area of research. Evidence suggests that neonatal hypoglycemia is more common among children conceived through ART. Our study aims to identify risk factors for neonatal hypoglycemia and the possibility of predicting it in ART-conceived children.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e In our study, 120 children born after ART were involved. The participants met specific criteria, including being born from a successful ART program resulting in single or multiple pregnancies. Those born using donor oocytes/sperm, intrauterine insemination, or surrogacy were not included. Data for the anamnesis were gathered and analyzed using IBM SPSS Statistics 26.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e ART-conceived children were at greater risk of being born with neonatal hypoglycemia in cases of multiple pregnancies (OR=14.2; 95% CI: 1.71-117.67), isthmic-cervical insufficiency (OR=10.29; 95% CI: 1.47-71.98), premature birth (OR=13.39; 95% CI: 2.61-68.84), and uterine infertility (OR=10.29; 95% CI: 1.47-71.98). ART children had a higher incidence of neonatal hypoglycemia when they were late preterm (OR=16.95; 95% CI: 3.26-88), with fetal growth restriction (OR=13.38; 95% CI: 2.42-73.8), infantile asphyxia (OR=45; 95% CI: 7.86-257.64), congenital pneumonia (OR=16.96; 95% CI: 3.45-83.3), congenital infection (OR=18; 95% CI: 2.98-108.8), respiratory distress syndrome (OR=16.09; 95% CI: 3.6-72.03), and low or very low birth weight. A regression model that exhibited statistical significance encompassed late prematurity, neonatal asphyxia, congenital infection, and maternal hormone intake before pregnancy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Our study on ART-conceived children highlighted significant risk factors for neonatal hypoglycemia Our developed prognostic model enables early intervention and preventive measures. These findings are valuable for healthcare providers working with ART-conceived children and can improve their care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration: \u003c/strong\u003eThe protocol was registered on ClinicalTrials.gov (NCT01369355). Date of registration: October 18, 2023; date of enrollment of the first subject: October 23, 2023\u003c/p\u003e","manuscriptTitle":"The Hidden Dangers: Uncovering Risk Factors for Neonatal Hypoglycemia in Assisted Reproductive Technology Babies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-08 00:51:38","doi":"10.21203/rs.3.rs-4857683/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":"cf407de0-1fd4-4ef4-b3ca-353ca3ad7a96","owner":[],"postedDate":"October 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-22T14:24:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-08 00:51:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4857683","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4857683","identity":"rs-4857683","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}