Maternal Adverse Events Associated with Antenatal Corticosteroids under Betamimetic Tocolysis in Preterm Birth Before 34 Weeks: An 11-Year Nationwide Database Study

Maternal Adverse Events Associated with Antenatal Corticosteroids under Betamimetic Tocolysis in Preterm Birth Before 34 Weeks: An 11-Year Nationwide Database Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Maternal Adverse Events Associated with Antenatal Corticosteroids under Betamimetic Tocolysis in Preterm Birth Before 34 Weeks: An 11-Year Nationwide Database Study Ayako Fudono, Mikayo Toba, Mutsuko Moriwaki, Masayuki Kakehashi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8892829/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Antenatal corticosteroids (ACS) are effective in improving the prognosis of preterm infants; however, their use rate in Japan is low, and large-scale studies on maternal safety are lacking. Therefore, this study aimed to clarify the association between ACS use and adverse maternal events in preterm births before 34 weeks of gestation treated with ritodrine hydrochloride (ritodrine). Methods Using nationwide data from fiscal year 2012 to 2022, we investigated 43,824 pregnant women who received ritodrine and experienced preterm births before 34 weeks of pregnancy. We calculated the trend in ACS implementation rates and examined their association with adverse maternal events using multivariate logistic regression analysis. Results The ACS implementation rates increased significantly from 26.9% to 59.8%, but the disparities between facilities widened. The ACS group had significantly higher rates of side effects of ritodrine listed in the package insert (listed adverse events; LAEs), heart failure, and pulmonary oedema. Multivariate analysis revealed that pulmonary oedema (adjusted odds ratio [aOR]: 2.45, 95% confidence interval [CI]: 1.82–3.30), heart failure (aOR: 1.55, 95% CI: 1.22–1.96), and LAEs (aOR: 1.17, 95% CI: 1.05–1.31) were associated with ACS use. However, when caesarean section was added as an adjustment variable, only the association with pulmonary oedema (aOR: 1.92, 95% CI: 1.25–2.95) remained significant. Conclusions Although the implementation rate of ACS is increasing, the differences between facilities are widening, making standardisation an urgent issue. Furthermore, because ACS use with ritodrine administration is strongly associated with pulmonary oedema independent of maternal severity, strict monitoring of vital signs, including respiratory rate, and appropriate information provision are essential. Trial Registration Not applicable. antenatal corticosteroids pulmonary oedema maternal adverse events betamimetics preterm birth Figures Figure 1 Figure 2 Figure 3 Background Antenatal corticosteroid (ACS) administration in women at risk of preterm birth is a well-established critical intervention. ACS not only promotes foetal lung maturation and prevents neonatal respiratory distress syndrome but also significantly reduces the risk of intraventricular haemorrhage, necrotising enterocolitis, and perinatal or neonatal mortality [ 1 , 2 ]. The clinical efficacy of ACS is maximised when administered to women at less than 34 weeks of gestation and within 7 days prior to delivery [ 3 – 6 ]. Although ACS has substantially improved short-term neonatal outcomes, concerns remain about how varying dosages and gestational ages at administration may influence long-term developmental outcomes [ 7 ]. Furthermore, several studies have highlighted the association between ACS and maternal adverse events, including pulmonary oedema, heart failure, sepsis, gastrointestinal haemorrhage, and hyperglycaemia [ 8 – 10 ]. Japan maintains world-leading perinatal and neonatal mortality rates—3.3 and 0.8 per 1,000 births, respectively which are among the lowest globally, as reported in the OECD Health Statistics 2023 [ 11 , 12 ]. However, the implementation rate of ACS in Japan remains low at approximately 40–49%, a striking contrast to other developed nations [ 13 , 14 ]. There is another aspect of preterm birth management in which Japan differs from other countries. Major international guidelines from organisations such as the World Health Organization, National Institute for Health and Care Excellence, and American College of Obstetricians and Gynecologists recommend ‘acute tocolysis’. This approach limits tocolytic therapy for preterm labour to a maximum of 48 hours—only long enough to facilitate the full effect of ACS—owing to concerns over severe maternal cardiovascular side effects [ 4 , 15 ]. Conversely, ‘maintenance tocolysis’, involving the long-term administration of the betamimetic ritodrine hydrochloride beyond 48 hours, remains a conventional clinical practice in Japan [ 16 , 17 ]. It is worth noting that only ritodrine and magnesium sulphate are approved as tocolytic agents in Japan. Beta-mimetics cause serious cardiorespiratory complications, such as pulmonary oedema and heart failure. Critically, these conditions are also recognised as side effects of ACS, and evidence has suggested that ACS administration with betamimetic therapy may synergistically increase the risks of maternal heart failure and pulmonary oedema [ 18 ]. Given the prevalence of ritodrine in Japan despite global shifts, assessing maternal risk is critical. However, to date, investigations into the association between ACS and maternal adverse events under betamimetic therapy have been limited to case reports or single-centre studies [ 19 , 20 ]. In recent years, the lack of individualised dosing protocols for ACS has become a major clinical concern. While research on optimising ACS administration to minimise neonatal risks while maximising lung maturation is ongoing [ 21 , 22 ], the discourse remains heavily weighted towards neonatal outcomes. There is an urgent need to reevaluate ACS optimisation from the perspective of maternal safety. Therefore, this study aimed to clarify the current implementation status of ACS in preterm births before 34 weeks of gestation and quantify the impact of ACS on maternal adverse events, particularly heart failure and pulmonary oedema, under betamimetic therapy. By using a nationwide database, we sought to provide robust evidence to enhance maternal and neonatal safety and contribute to the overall quality of perinatal care. Methods Study design This retrospective cohort study, which investigated the current implementation status of ACS in preterm births before 34 weeks of gestation and assessed the impact of ACS on maternal adverse events, used data from the Diagnosis Procedure Combination (DPC) database in Japan. The DPC is a prospective payment system based on a diagnostic classification applied to acute care institutions [ 23 ]. Approximately 1,000 hospitals contribute data to the database, covering over 8 million inpatient admissions annually and representing approximately 50% of all acute care inpatients in Japan. We obtained data from the DPC database, including demographic data, diagnoses, comorbidities, complications, dates of admission and discharge, gestational age at admission, patient age, body weight, height, and details of the medications and procedures. The diagnoses, comorbidities, and complications were recorded according to the International Classification of Diseases Tenth Revision (ICD-10) codes and text data in Japanese. This study was approved by the Institutional Review Board of the Institute of Science Tokyo. The requirement for individual informed consent was waived as the data did not contain any personally identifiable information (approval number: M2000-788). Study population We included women who received a betamimetic ritodrine hydrochloride injection and had preterm delivery before 34 weeks of gestation between 1 April 2012 and 31 March 2023. This study examined the implementation of ACS and maternal adverse events in cases of preterm birth before 34 weeks of gestation for which ACS administration was considered appropriate. We excluded patients who had been transported from another institution because the medical treatment at the previous institution was unknown. Patients who had stayed in institutions < 3 days, women with anthropometric measurements that substantially deviated from the normal range — specifically, those with height ≥ 200 cm or < 120 cm or missing body weight — were also excluded [ 24 ]. Outcomes Eight adverse events described as ‘clinically significant adverse reactions’ in the ritodrine package insert were defined as listed adverse events (LAEs): liver dysfunction (ICD-10: K71.9, K76.9, and O26.6), arrhythmia (I48 and I49), heart failure (I50 and O99.4), pulmonary oedema (J81), hypokalaemia (E87.6), foetal arrhythmia (O68.0), rhabdomyolysis (M62.8), and neutropenia (D70). The primary outcome was the influence of ACS on the occurrence of LAEs, with a specific focus on heart failure and pulmonary oedema. Variables The variables used for analysis were maternal age, gestational age at admission, body mass index (BMI), obstetric complications (preterm premature rupture of membranes [pPROM], multiple pregnancy, placenta previa, cervical insufficiency, gestational diabetes mellitus, and hypertensive disorders of pregnancy), Charlson Comorbidity Index [ 25 ], fiscal year of admission, and duration of tocolysis (classified as acute or maintenance). Statistical analysis We compared baseline characteristics and outcomes between the ACS and non-ACS groups. Continuous variables were compared using the Mann–Whitney U test, and discrete variables were compared using chi-square test. Multivariate logistic regression analysis was performed to estimate the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for the occurrence of LAEs. Furthermore, to identify specific risks, separate regression models were constructed for heart failure and pulmonary oedema as individual outcomes. The Jonckheere–Terpstra test was employed to evaluate the chronological trends in ACS implementation rates. To assess the association between ACS administration and maternal adverse events, logistic regression analysis was performed. We constructed models with LAEs, heart failure, and pulmonary oedema as the dependent variables. These models were adjusted for potential confounders, including maternal age, BMI, obstetric complications, use of magnesium sulphate, and duration of tocolysis. Owing to the clinical significance of the mode of delivery, adjustments for caesarean sections were also performed. All statistical analyses were performed using SPSS (version 30; IBM Corp., Armonk, NY, USA). Statistical significance was defined as p < 0.05 (two-tailed). Results In total, 43,824 patients from 672 institutions were included in the analysis (Fig. 1 ). The numbers of patients in the ACS and the non-ACS group were 20,870 and 22,954, respectively. Table 1 presents the demographic and clinical characteristics of the study population. Although the ACS group showed statistically higher age, BMI, and gestational age at admission (all p < 0.001), the effect sizes were small (SMDs = 0.06–0.15), indicating that these differences were not significant. Notably, compared with the non-ACS group, the ACS group had a significantly higher proportion of high-risk patients managed at academic and perinatal medical centres. Additionally, the use of magnesium sulphate and rate of caesarean sections were higher in the ACS group than in the non-ACS, reflecting a more intensive management approach. Table 1 Characteristics of the participants according to antenatal corticosteroid administration (N = 43,824) ACS *1 N = 20,870 Non-ACS*1 N = 22,954 SMD*2 p*3 Maternal characteristics of admission Age, mean, SD*4, Week 32.22 5.33 31.58 5.46 0.12 < 0.001 Gestational age, mean, SD*4, Week 27.47 4.01 26.81 4.65 0.15 < 0.001 Gestational age, median, IQR*5, Week 28.00 7.00 28.00 8.00 - < 0.001 BMI*6, mean, SD*4, kg/m 2 23.27 3.83 23.04 3.71 0.06 < 0.001 pPROM*7, n, % 7,393 35.42 2,969 12.93 0.54 < 0.001 Multiple pregnancy, n, % 2,784 13.34 2,316 10.09 0.10 < 0.001 Placenta previa, n, % 1,733 8.30 1,234 5.38 0.12 < 0.001 Cervical insufficiency, n, % 1,689 8.09 3,088 13.45 0.17 < 0.001 Gestational diabetes mellitus 1,093 5.24 1,065 4.64 0.03 0.004 Hypertensive disorders of pregnancy, n, % 1,259 6.03 822 3.58 0.11 =, n, % 717 3.44 761 3.32 0.01 0.486 Institution Academic hospital, n, % 8,468 40.57 6,413 27.94 0.27 < 0.001 Perinatal medical center, n, % 13,285 63.66 9,676 42.15 0.44 < 0.001 Fiscal year 2012, n, % 742 3.56 2,021 8.80 0.22 < 0.001 2013, n, % 823 3.94 2,147 9.35 0.22 2014, n, % 1,473 7.06 2,547 11.10 0.14 2015, n, % 1,434 6.87 2,288 9.97 0.11 2016, n, % 1,583 7.59 1,975 8.60 0.04 2017, n, % 1,597 7.65 1,731 7.54 0.00 2018, n, % 1,914 9.17 1,854 8.08 0.04 2019, n, % 2,715 13.01 2,291 9.98 0.10 2020, n, % 2,794 13.39 2,113 9.21 0.13 2021, n, % 3,052 14.62 2,140 9.32 0.16 2022, n, % 2,743 13.14 1,847 8.05 0.17 Preterm labor management Acute tocolysis with ritodrine*9, n, % 5,105 24.46 4,687 20.42 0.10 < 0.001 Magnesium sulphate hydrate, n, % 10,923 52.34 4,954 21.58 0.67 < 0.001 Caesarean section, n, % 11,956 57.29 5,088 22.17 0.77 < 0.001 Week of Delivery, mean, SD*4, Week 29.49 3.24 27.89 5.37 0.11 < 0.001 Week of Delivery, median, IQR*5, Week 30.00 5.00 29.00 7.00 - < 0.001 Length of stay, mean, SD*4, Week 25.83 21.84 26.34 22.68 0.02 0.077 Length of stay, median, IQR*5, day 17.00 25.00 18.00 26.00 - 0.077 *1 antenatal corticosteroid *2 standardized mean difference *3 continuous variable: Mann-Whitney U test, discrete variable: chi-square test *4 standard deviation *5 interquartile range *6 body mass index *7 preterm premature rupture of membranes *8 Charlson comorbidity index *9 < = 2days [Insert Table 1 here] ACS implementation rates in perinatal and non-perinatal centres increased annually (Fig. 2 a). As shown in the box plot in Fig. 2 b, ACS use rates varied substantially depending on the facility. Notably, while the variation among perinatal centres narrowed over time, the disparity among non-perinatal centres widened (Additional File 1a and 1b). A comparison of the incidence of maternal adverse events between the two groups is shown in Table 2 . The rates of heart failure and pulmonary oedema were significantly higher in the ACS group than in the non-ACS group (both p < 0.001). Overall, the incidence of LAEs was significantly higher in the ACS group than in the non-ACS group. Table 2 Comparison of Maternal adverse event Incidence Based on the Antenatal Corticosteroid Administration (N = 43,824) ACS *1 N = 20,870 non-ACS*1 N = 22,954 p*2 LAEs*3, n,% 453 2.17 299 1.30 < 0.001 Liver dysfunction, n,% 71 0.34 73 0.32 0.685 Arrhythmia, n, % 72 0.34 61 0.27 0.115 Heart failure, n, % 141 0.68 61 0.27 < 0.001 Pulmonary oedema, n,% 115 0.55 35 0.15 < 0.001 Hypokalemia, n, % 53 0.25 43 0.19 0.136 Fetal arrhythmia, n, % 20 0.10 21 0.09 0.882 Rhabdomyolysis, n, % 11 0.05 6 0.03 0.158 Neutropenia, n, % 12 0.06 8 0.03 0.268 Gestational diabetes mellitus*4, n,% 260 1.25 256 1.12 0.206 Sepsis, n,% 30 0.14 35 0.15 0.812 Maternal death, n,% 3 0.01 1 0.00 0.273 *1 antenatal corticosteroid *2 continuous variable: Mann-Whitney U test, discrete variable: chi-square test *3 LAEs: liver dysfunction, arrhythmia, heart failure, pulmonary oedema, hypokalemia, fetal arrhythmia, rhabdomyolysis, and neutropenia. *4 onset during hospitalization In contrast, there were no significant differences between the two groups in terms of other complications, such as sepsis and gestational diabetes mellitus. There were also no significant differences in maternal mortality. A multivariate logistic regression analysis was performed to assess the independent association between ACS administration and maternal adverse events (Fig. 3 and Additional File 2). In Model 1 (adjusted for baseline maternal and institutional characteristics), ACS administration was significantly associated with pulmonary oedema (aOR: 2.45, 95% CI: 1.82–3.30, p < 0.001), heart failure (aOR: 1.55, 95% CI: 1.22–1.96, p < 0.001), and LAEs (aOR: 1.17, 95% CI: 1.05–1.31, p = 0.006). However, in Model 2, which was further adjusted for the mode of delivery, the association between ACS and heart failure was attenuated and became less pronounced. Similarly, the association with any LAEs weakened after adjustment. In contrast, the significant risk of pulmonary oedema remained robust and was not affected by adjustment for caesarean sections. Stratified analysis by the mode of delivery clarified these associations (Additional File 3). For pulmonary oedema, the incidence was consistently higher in the ACS group than in the non-ACS group, regardless of the delivery mode (0.24% vs. 0.07% in vaginal delivery; 0.79% vs. 0.45% in caesarean section). However, for heart failure and LAEs the differences between the ACS and non-ACS groups were minimal among patients undergoing caesarean section (Heart failure: 1.02% vs. 0.85%; LAEs: 2.78% vs. 2.50%). These findings suggest that the risks of heart failure and LAEs were primarily driven by the mode of delivery or the underlying clinical severity requiring surgical intervention, rather than the ACS administration. Discussion Main findings This study used a large-scale national database to clarify the current trends in ACS implementation and the associated maternal risks under betamimetic (ritodrine)-based management in Japan. We found that although ACS implementation rates have increased significantly across all facility types over the past decade, a substantial disparity in clinical practice persists, particularly among non-perinatal centres. Furthermore, our multivariate analysis revealed that ACS administration was independently associated with a more than two-fold increase in the risk of pulmonary oedema, even after adjusting for potential confounders, including the mode of delivery. While the association between ACS and heart failure was partially attenuated by the inclusion of caesarean section in the model, the risk of pulmonary oedema remained robust, highlighting a specific safety concern in the unique Japanese context of long-term tocolysis. Trends in ACS implementation rates We evaluated the implementation status of ACS in preterm birth cases at less than 34 weeks of gestation, where ACS use was clinically indicated. While the implementation rate increased from fiscal year 2012 to 2022, it remains low compared with international standards [ 13 ]. Previous studies have shown that the organisational structure and functional capacity of healthcare facilities influence ACS implementation rates [ 26 ]. The observed disparity in ACS implementation rates among non-perinatal centres is particularly evident, given that our study population only included cases that eventually resulted in preterm delivery before 34 weeks. In cases where the clinical necessity for ACS is high, the widening variation in utilisation suggests institutional barriers beyond simple diagnoses. One important factor is the timing of the decision to administer ACS. In non-perinatal centres, emergent maternal transport may be the primary clinical priority, which can result in the deferral of ACS administration to the receiving tertiary care centre. In addition, the package insert for injectable betamethasone specifies that when betamethasone is administered as an antenatal corticosteroid, it should be given in settings where perinatal management at a higher-level medical facility is available. This may contribute to the reluctance to administer ACS in primary care settings. The lack of information on the clinical urgency of preterm labour in the DPC database, the second factor, may have influenced the ACS administration rate, as cases where labour progressed more rapidly than anticipated and the opportunity to administer ACS was missed were classified as non-ACS. Despite these limitations, the ACS implementation rate has exhibited a distinct chronological shift. Prior to 2014, the Japan Society of Obstetrics and Gynecology guidelines limited ACS indications to preterm labour before 34 weeks and pPROM before 32 weeks. This was expanded in 2017 to include all cases of threatened preterm labour or pPROM before 34 weeks of gestation. The median implementation rate remained at 0% until 2016, indicating that half of the medical institutions had not used ACS. However, a significant increase was observed after the 2017 revision. This strongly suggests that the promotion of standardised preterm care and dissemination of knowledge through guidelines directly prompted behavioural changes among physicians, leading to improved ACS implementation. The impact of delivery mode on heart failure and LAEs In the multivariate logistic regression model (Model 1), pulmonary oedema, heart failure, and LAEs were significantly associated with ACS. However, after adjusting for the mode of delivery (Model 2), the association between heart failure and LAEs lost statistical significance, whereas the association with pulmonary oedema remained robust. We also confirmed significant associations between magnesium sulphate or hypertensive disorders of pregnancy and pulmonary oedema, heart failure, and LAEs, as reported in previous studies [ 27 – 30 ]. These results suggest that the association between ACS and heart failure/LAEs is strongly confounded by delivery mode. Generally, vaginal delivery is preferred in pregnancies complicated by heart disease to avoid sudden haemodynamic shifts; however, caesarean section is often necessitated by haemodynamic instability or treatment-resistant heart failure [ 31 – 33 ]. In preterm births (before 34 weeks of gestation), patients who develop heart failure prior to delivery are highly likely to undergo caesarean section. Thus, the primary risk factor for heart failure may not be ACS administration, but rather the underlying clinical severity that necessitates caesarean section. Because LAEs are also associated with maternal vulnerability and severity, the loss of significance of ACS in this context is consistent. Direct pharmacological association between ACS and pulmonary oedema In contrast, the association between ACS and pulmonary oedema remained significant, with little change in the odds ratio after adjusting for caesarean section. This indicates that the underlying mechanisms and risk factors for pulmonary oedema differ from those for heart failure. High-dose corticosteroids may increase pulmonary capillary pressure by altering vascular reactivity, thereby potentially increasing the risk of pulmonary oedema [ 34 ]. In addition, by upregulating β-adrenergic receptor expression, high-dose corticosteroids may enhance the adverse effects of ritodrine, including increased cardiac output and fluid retention [ 35 ]. Indeed, an increased risk of pulmonary oedema has been reported with the concomitant use of ritodrine and ACS [ 20 ]. In Japan, where ACS is frequently administered concurrently with betamimetics that independently cause pulmonary oedema, this synergistic effect requires heightened vigilance. Early detection of pulmonary oedema requires strict monitoring of vital signs. However, the measurement rate of Early Warning Score components, particularly respiratory rate, is low in Japanese obstetric settings [ 36 ]. International studies have suggested that systems, such as the Maternal Early Warning Trigger or the Modified Obstetric Early Warning Score, significantly improve the outcomes of severe complications, including pulmonary oedema [ 37 , 38 ]. To mitigate the risks identified in this study, it is essential to implement systematic vital sign monitoring with a specific focus on respiratory rate and fluid balance, alongside comprehensive patient education. Recognising early symptoms of fluid overload is paramount for the safe administration of ACS under tocolytic management. Strengths and limitations A major strength of this study is that it is the first to quantitatively evaluate the impact of ACS on maternal adverse events under high-risk conditions typical of clinical practice (i.e., concurrent tocolytic therapy) using a nationwide database. By limiting the cohort to patients receiving ritodrine, we maintained the effect of betamimetics, allowing us to isolate the additional risks posed by ACS and effectively adjust for confounding factors. Furthermore, the divergent results for pulmonary oedema versus heart failure/LAEs after adjustment demonstrated the separation of statistical confounding factors from pharmacological effects, enhancing the biological plausibility of our findings. These results are highly applicable in clinical settings using the betamimetic tocolytic strategy worldwide. Nevertheless, this study has some limitations must be considered. The DPC database lacks detailed clinical parameters, such as cervical dilation, cardiotocography findings, or laboratory data (e.g., B-type natriuretic peptide or inflammatory markers). The absence of granular data may preclude a definitive assessment of the clinical severity of preterm labour or the precise timing of ACS administration. Because our analysis relied on the ICD-10 diagnostic codes, we could not evaluate the clinical severity or specific diagnostic criteria used for heart failure or pulmonary oedema at individual institutions. Although the DPC database has been validated for the accuracy of major diagnoses, misclassification or under-reporting remains possible. Finally, because this was a retrospective observational study, the possibility of unmeasured confounding factors, such as specific fluid management protocols at each hospital, cannot be entirely excluded. To address these limitations, prospective studies are warranted to assess clinical severity and the precise timing of ACS administration, which are not captured in the DPC database. Prospective collection of detailed information on maternal conditions and treatments before and after ACS administration would enable more robust evaluation of causal relationships. Moreover, improved assessment of the severity of threatened preterm labour may help identify reasons for non-administration and inform strategies for increasing ACS implementation rates. Conclusions While the ACS implementation rate in Japan has been increasing over the past decade, institutional disparities are widening, particularly in non-perinatal centres. Our findings demonstrate that ACS administration is independently associated with an increased risk of pulmonary oedema under ritodrine-based management, even after accounting for delivery mode. To ensure maternal safety, clinicians must implement rigorous monitoring, specifically focusing on the respiratory rate and fluid balance, for the early detection and management of fluid overload in this high-risk population. The optimisation of ACS administration by balancing maternal risks with the primary goal of improving neonatal outcomes remains a critical challenge. Abbreviations ACS antenatal corticosteroid DPC Diagnosis Procedure Combination ICD-10 International Classification of Diseases Tenth Revision LAEs listed adverse events BMI body mass index pPROM preterm premature rupture of membranes aORs adjusted odds ratios CIs confidence intervals Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board of the Institute of Science, Tokyo (approval number: M2000-788). The requirement for individual informed consent was waived as the data did not contain any personally identifiable information. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding The study was supported by the Sasakawa Health Foundation (2025-07). The funders had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript. The funding source had no role in the design of the study, data collection, analysis, interpretation, or writing of the manuscript. No medical writer or editor was involved in the preparation of this manuscript. Author Contribution Ayako Fudono and Mikayo Toba wrote the main manuscript text. Mikayo Toba performed the analysis and prepared the figures and tables. Mutsuko Moriwaki was responsible for the methodology and overall structure of the manuscript. Masayuki Kakehashi supervised the statistical analysis. Rie Oi reviewed and revised the entire manuscript. Kiyohide Fushimi provided the data resources. Naoyuki Miyasaka was responsible for overall supervision. All authors reviewed the manuscript. Acknowledgement The authors thank Shunji Shimoda from the National Hospital Organization Headquarters for providing technical support in the extraction and management of patient data. Data Availability The datasets generated and/or analysed during the current study are not publicly available because the datasets contain personal information but are available from the corresponding author on reasonable request. References McGoldrick E, Stewart F, Parker R, Dalziel SR. Antenatal corticosteroids for accelerating fetal lung maturation for women at risk of preterm birth. Cochrane Database Syst Rev. 2020;12:CD004454. Effect of corticosteroids for fetal maturation on perinatal outcomes. February 28–March 2, 1994. Consensus Dev Panel. 1995;173:246–52. Am J Obstet Gynecol. National Institutes of Health (NIH). Melamed N, Shah J, Soraisham A, Yoon EW, Lee SK, Shah PS, et al. 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Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173:676–82. Yang WC, Arsenault C, Fan VY, Ali NB, Alwy Al-Beity FM, Smith ER. Factors affecting antenatal corticosteroid use in low- and middle-income countries: Facility characteristics, structural readiness, and past performance of CEmONC signal functions. PLOS Glob Public Health. 2025;5:e0003989. Sciscione AC, Ivester T, Largoza M, Manley J, Shlossman P, Colmorgen GH. Acute pulmonary edema in pregnancy. Obstet Gynecol. 2003;101:511–5. Mersha AG, Abegaz TM, Seid MA. Maternal and perinatal outcomes of hypertensive disorders of pregnancy in Ethiopia: systematic review and meta-analysis. BMC Pregnancy Childbirth. 2019;19:458. Goldstein SA, Pagidipati NJ. Hypertensive Disorders of Pregnancy and Heart Failure Risk. Curr Hypertens Rep. 2022;24(7):205–13. Barasa A, Rosengren A, Sandström TZ, Ladfors L, Schaufelberger M. Heart Failure in Late Pregnancy and Postpartum: Incidence and Long-Term Mortality in Sweden From 1997 to 2010. J Card Fail. 2017;23:370–8. Regitz-Zagrosek V, Roos-Hesselink JW, Bauersachs J, Blomström-Lundqvist C, Cífková R, De Bonis M, et al. 2018 ESC Guidelines for the management of cardiovascular diseases during pregnancy. Eur Heart J. 2018;39:3165–241. JCS. Guideline on Indication and Management of Pregnancy and Delivery in Women with Heart Disease; 2018. DeFilippis EM, Bhagra C, Casale J, Ging P, Macera F, Punnoose L, et al. Cardio-obstetrics and heart failure: JACC: Heart failure state-of-the-art review. JACC Heart Fail. 2023;11:1165–80. Araujo JEDS, Miguel-Dos-Santos R, Macedo FN, Cunha PS, Fontes MT, Murata GM, et al. Effects of high doses of glucocorticoids on insulin-mediated vasodilation in the mesenteric artery of rats. PLoS ONE. 2020;15:e0230514. Mak JC, Nishikawa M, Barnes PJ. Glucocorticosteroids increase beta 2-adrenergic receptor transcription in human lung. Am J Physiol. 1995;268(1 Pt 1):L41–6. Hamada O, Tsutsumi T, Tsunemitsu A, Sasaki N, Imanaka Y. Improving respiratory rate monitoring in general wards following implementation of a rapid response system: A quality improvement initiative. BMJ Open Qual. 2025;14:e003218. Shields LE, Wiesner S, Klein C, Pelletreau B, Hedriana HL. Use of Maternal Early Warning Trigger tool reduces maternal morbidity. Am J Obstet Gynecol. 2016;214:e5271–6. Arnolds DE, Smith A, Banayan JM, Holt R, Scavone BM. National partnership for maternal safety recommended maternal early warning criteria are associated with maternal morbidity. Anesth Analg. 2019;129:1621–6. Additional Declarations No competing interests reported. Supplementary Files AddFile1.tif AdditionalFile2.xlsx AdditionalFile3.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 07 May, 2026 Reviews received at journal 27 Mar, 2026 Reviewers agreed at journal 26 Mar, 2026 Reviewers invited by journal 04 Mar, 2026 Editor invited by journal 18 Feb, 2026 Editor assigned by journal 16 Feb, 2026 Submission checks completed at journal 16 Feb, 2026 First submitted to journal 16 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8892829","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":602808746,"identity":"515f51f8-c1be-4963-aa9c-bd7922a69099","order_by":0,"name":"Ayako Fudono","email":"","orcid":"","institution":"Institute of Science Tokyo Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ayako","middleName":"","lastName":"Fudono","suffix":""},{"id":602808747,"identity":"e7ac9793-5ede-48cc-b757-3b1dcb4df131","order_by":1,"name":"Mikayo Toba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYFACHjApB8QGIAYzERogWox5SNaS2APVQhjYs/ce/PBzz7b0/WKHNzD8qGFgNydoC8+5ZMmeZ7dze6TTChh7jjEwWzYQ0iKRYyDNcACkJceAgbeBgdngAGEtxr+BWtJ5gFoY/xKpxQxkSwJICzNxtpw5l2bZc+C2Yc/ttILDMsckCPuFvb338I0fB27Ls89O3vjwTY1NMsEQQwFAJ0kkExk7SMCOdC2jYBSMglEw3AEAbEQ6OizGC5IAAAAASUVORK5CYII=","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":true,"prefix":"","firstName":"Mikayo","middleName":"","lastName":"Toba","suffix":""},{"id":602808750,"identity":"6de2c89c-78ad-4a6e-bb66-e3a2717f2a06","order_by":2,"name":"Mutsuko Moriwaki","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Mutsuko","middleName":"","lastName":"Moriwaki","suffix":""},{"id":602808752,"identity":"5cb6b362-ef16-4446-b7c9-132ff401e42d","order_by":3,"name":"Masayuki Kakehashi","email":"","orcid":"","institution":"Hiroshima University","correspondingAuthor":false,"prefix":"","firstName":"Masayuki","middleName":"","lastName":"Kakehashi","suffix":""},{"id":602808753,"identity":"d7947daa-6202-4537-8b7b-df9f975e5db4","order_by":4,"name":"Rie Oi","email":"","orcid":"","institution":"Tokyo Metropolitan Ohtsuka Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rie","middleName":"","lastName":"Oi","suffix":""},{"id":602808754,"identity":"515f9e5b-aff9-410f-839c-ef6739971c85","order_by":5,"name":"Kiyohide Fushimi","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Kiyohide","middleName":"","lastName":"Fushimi","suffix":""},{"id":602808759,"identity":"aa4b305c-fad3-41f0-9e7f-31c71d22deca","order_by":6,"name":"Naoyuki Miyasaka","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Naoyuki","middleName":"","lastName":"Miyasaka","suffix":""}],"badges":[],"createdAt":"2026-02-16 11:39:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8892829/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8892829/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104374204,"identity":"ed970cc1-6799-42cb-9eb8-6afc22963fff","added_by":"auto","created_at":"2026-03-11 06:06:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3371930,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of participant selection.\u003c/p\u003e\n\u003cp\u003eThe study population included women who received a betamimetic ritodrine hydrochloride injection and had a preterm delivery before 34 weeks of gestation during the study period.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8892829/v1/ceef9a35d2cc978738e15462.png"},{"id":104374202,"identity":"7151a166-9f00-47a3-b0f7-36cab8913a0e","added_by":"auto","created_at":"2026-03-11 06:06:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4462867,"visible":true,"origin":"","legend":"\u003cp\u003e2a. Trends in the implementation rates of antenatal corticosteroids (ACS) at perinatal and non-perinatal centres.\u003c/p\u003e\n\u003cp\u003eImplementation rates are shown for each fiscal year (2012–2022), and the implementation rate has increased significantly since 2012 in both centre types (p-value for trend \u0026lt; 0.001). Statistical significance was determined using the Jonckheere–Terpstra test.\u003c/p\u003e\n\u003cp\u003eFig 2b. Trends of ACS use rates by institution (n=762).\u003c/p\u003e\n\u003cp\u003eTrends in ACS use rates by institution are shown in a box plot. Cross marks indicate the average, and vertical lines in the box indicate the median use rate. There is a large difference between facilities in their ACS use rates, and this variation increases every year.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8892829/v1/2ae6bacc6af5d1b8e542974c.png"},{"id":104374201,"identity":"ef849814-3779-444f-908c-75765808e7c2","added_by":"auto","created_at":"2026-03-11 06:06:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2248318,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate logistic regression analysis of factors associated with maternal adverse events.\u003c/p\u003e\n\u003cp\u003eThe left side of the forest plot shows maternal adverse events related to antenatal corticosteroid (ACS) administration. The horizontal axis represents the odds ratio and the horizontal lines through the dots indicate the 95% confidence intervals (CIs). Pulmonary oedema (adjusted odds ratio [aOR]: 2.45, 95% CI: 1.82–3.30, p \u0026lt; 0.001), heart failure (aOR: 1.55, 95% CI: 1.22–1.96, p \u0026lt; 0.001), and listed adverse events (LAEs) (aOR: 1.17, 95% CI: 1.05–1.31, p = 0.006) are significantly associated with ACS administration (Model 1). After adjustment for caesarean section, only pulmonary oedema remained significant (aOR: 1.92, 95% CI: 1.25–2.95, p \u0026lt; 0.001) (refer to Additional File 2).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8892829/v1/c43c9aed24a518eb8675591d.png"},{"id":104374217,"identity":"ef6588a0-9110-489e-80ef-2356873161fe","added_by":"auto","created_at":"2026-03-11 06:06:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":38172187,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8892829/v1/c1f227a7-9d2d-44ba-b857-272fa8e96410.pdf"},{"id":104374199,"identity":"43b75537-4274-4193-bb7c-2b49e37cc2ba","added_by":"auto","created_at":"2026-03-11 06:06:15","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":269640,"visible":true,"origin":"","legend":"","description":"","filename":"AddFile1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8892829/v1/5d1cb3c915d2de1a8073fcf2.tif"},{"id":104374200,"identity":"c8b411a5-da2c-4552-9a73-9311c8881c8d","added_by":"auto","created_at":"2026-03-11 06:06:15","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22969,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalFile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8892829/v1/460295eaa06495d8c05377ea.xlsx"},{"id":104374203,"identity":"e9a3ea1a-8190-4679-95e6-61aac41b0507","added_by":"auto","created_at":"2026-03-11 06:06:15","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11059,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalFile3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8892829/v1/efce96bbbdef8d3dbf703ebf.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maternal Adverse Events Associated with Antenatal Corticosteroids under Betamimetic Tocolysis in Preterm Birth Before 34 Weeks: An 11-Year Nationwide Database Study","fulltext":[{"header":"Background","content":"\u003cp\u003eAntenatal corticosteroid (ACS) administration in women at risk of preterm birth is a well-established critical intervention. ACS not only promotes foetal lung maturation and prevents neonatal respiratory distress syndrome but also significantly reduces the risk of intraventricular haemorrhage, necrotising enterocolitis, and perinatal or neonatal mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The clinical efficacy of ACS is maximised when administered to women at less than 34 weeks of gestation and within 7 days prior to delivery [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although ACS has substantially improved short-term neonatal outcomes, concerns remain about how varying dosages and gestational ages at administration may influence long-term developmental outcomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, several studies have highlighted the association between ACS and maternal adverse events, including pulmonary oedema, heart failure, sepsis, gastrointestinal haemorrhage, and hyperglycaemia [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eJapan maintains world-leading perinatal and neonatal mortality rates\u0026mdash;3.3 and 0.8 per 1,000 births, respectively which are among the lowest globally, as reported in the OECD Health Statistics 2023 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, the implementation rate of ACS in Japan remains low at approximately 40\u0026ndash;49%, a striking contrast to other developed nations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. There is another aspect of preterm birth management in which Japan differs from other countries. Major international guidelines from organisations such as the World Health Organization, National Institute for Health and Care Excellence, and American College of Obstetricians and Gynecologists recommend \u0026lsquo;acute tocolysis\u0026rsquo;. This approach limits tocolytic therapy for preterm labour to a maximum of 48 hours\u0026mdash;only long enough to facilitate the full effect of ACS\u0026mdash;owing to concerns over severe maternal cardiovascular side effects [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Conversely, \u0026lsquo;maintenance tocolysis\u0026rsquo;, involving the long-term administration of the betamimetic ritodrine hydrochloride beyond 48 hours, remains a conventional clinical practice in Japan [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It is worth noting that only ritodrine and magnesium sulphate are approved as tocolytic agents in Japan.\u003c/p\u003e \u003cp\u003eBeta-mimetics cause serious cardiorespiratory complications, such as pulmonary oedema and heart failure. Critically, these conditions are also recognised as side effects of ACS, and evidence has suggested that ACS administration with betamimetic therapy may synergistically increase the risks of maternal heart failure and pulmonary oedema [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Given the prevalence of ritodrine in Japan despite global shifts, assessing maternal risk is critical. However, to date, investigations into the association between ACS and maternal adverse events under betamimetic therapy have been limited to case reports or single-centre studies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In recent years, the lack of individualised dosing protocols for ACS has become a major clinical concern. While research on optimising ACS administration to minimise neonatal risks while maximising lung maturation is ongoing [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], the discourse remains heavily weighted towards neonatal outcomes. There is an urgent need to reevaluate ACS optimisation from the perspective of maternal safety.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to clarify the current implementation status of ACS in preterm births before 34 weeks of gestation and quantify the impact of ACS on maternal adverse events, particularly heart failure and pulmonary oedema, under betamimetic therapy. By using a nationwide database, we sought to provide robust evidence to enhance maternal and neonatal safety and contribute to the overall quality of perinatal care.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study, which investigated the current implementation status of ACS in preterm births before 34 weeks of gestation and assessed the impact of ACS on maternal adverse events, used data from the Diagnosis Procedure Combination (DPC) database in Japan. The DPC is a prospective payment system based on a diagnostic classification applied to acute care institutions [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Approximately 1,000 hospitals contribute data to the database, covering over 8\u0026nbsp;million inpatient admissions annually and representing approximately 50% of all acute care inpatients in Japan. We obtained data from the DPC database, including demographic data, diagnoses, comorbidities, complications, dates of admission and discharge, gestational age at admission, patient age, body weight, height, and details of the medications and procedures. The diagnoses, comorbidities, and complications were recorded according to the International Classification of Diseases Tenth Revision (ICD-10) codes and text data in Japanese. This study was approved by the Institutional Review Board of the Institute of Science Tokyo. The requirement for individual informed consent was waived as the data did not contain any personally identifiable information (approval number: M2000-788).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eWe included women who received a betamimetic ritodrine hydrochloride injection and had preterm delivery before 34 weeks of gestation between 1 April 2012 and 31 March 2023. This study examined the implementation of ACS and maternal adverse events in cases of preterm birth before 34 weeks of gestation for which ACS administration was considered appropriate. We excluded patients who had been transported from another institution because the medical treatment at the previous institution was unknown. Patients who had stayed in institutions\u0026thinsp;\u0026lt;\u0026thinsp;3 days, women with anthropometric measurements that substantially deviated from the normal range \u0026mdash; specifically, those with height\u0026thinsp;\u0026ge;\u0026thinsp;200 cm or \u0026lt;\u0026thinsp;120 cm or missing body weight \u0026mdash; were also excluded [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eEight adverse events described as \u0026lsquo;clinically significant adverse reactions\u0026rsquo; in the ritodrine package insert were defined as listed adverse events (LAEs): liver dysfunction (ICD-10: K71.9, K76.9, and O26.6), arrhythmia (I48 and I49), heart failure (I50 and O99.4), pulmonary oedema (J81), hypokalaemia (E87.6), foetal arrhythmia (O68.0), rhabdomyolysis (M62.8), and neutropenia (D70). The primary outcome was the influence of ACS on the occurrence of LAEs, with a specific focus on heart failure and pulmonary oedema.\u003c/p\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eThe variables used for analysis were maternal age, gestational age at admission, body mass index (BMI), obstetric complications (preterm premature rupture of membranes [pPROM], multiple pregnancy, placenta previa, cervical insufficiency, gestational diabetes mellitus, and hypertensive disorders of pregnancy), Charlson Comorbidity Index [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], fiscal year of admission, and duration of tocolysis (classified as acute or maintenance).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe compared baseline characteristics and outcomes between the ACS and non-ACS groups. Continuous variables were compared using the Mann\u0026ndash;Whitney U test, and discrete variables were compared using chi-square test. Multivariate logistic regression analysis was performed to estimate the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for the occurrence of LAEs. Furthermore, to identify specific risks, separate regression models were constructed for heart failure and pulmonary oedema as individual outcomes.\u003c/p\u003e \u003cp\u003eThe Jonckheere\u0026ndash;Terpstra test was employed to evaluate the chronological trends in ACS implementation rates. To assess the association between ACS administration and maternal adverse events, logistic regression analysis was performed. We constructed models with LAEs, heart failure, and pulmonary oedema as the dependent variables. These models were adjusted for potential confounders, including maternal age, BMI, obstetric complications, use of magnesium sulphate, and duration of tocolysis. Owing to the clinical significance of the mode of delivery, adjustments for caesarean sections were also performed.\u003c/p\u003e \u003cp\u003eAll statistical analyses were performed using SPSS (version 30; IBM Corp., Armonk, NY, USA). Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn total, 43,824 patients from 672 institutions were included in the analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The numbers of patients in the ACS and the non-ACS group were 20,870 and 22,954, respectively. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the demographic and clinical characteristics of the study population. Although the ACS group showed statistically higher age, BMI, and gestational age at admission (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the effect sizes were small (SMDs\u0026thinsp;=\u0026thinsp;0.06\u0026ndash;0.15), indicating that these differences were not significant. Notably, compared with the non-ACS group, the ACS group had a significantly higher proportion of high-risk patients managed at academic and perinatal medical centres. Additionally, the use of magnesium sulphate and rate of caesarean sections were higher in the ACS group than in the non-ACS, reflecting a more intensive management approach.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the participants according to antenatal corticosteroid administration (N\u0026thinsp;=\u0026thinsp;43,824)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eACS *1\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;20,870\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNon-ACS*1\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;22,954\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eSMD*2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep*3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaternal characteristics of admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, mean, SD*4, Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e5.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age, mean, SD*4, Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age, median, IQR*5, Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI*6, mean, SD*4, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epPROM*7, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e12.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple pregnancy, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e10.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacenta previa, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e5.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical insufficiency, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e13.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational diabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertensive disorders of pregnancy, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e3.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI*8, 1\u0026gt;=, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInstitution\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic hospital, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e27.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerinatal medical center, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e42.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFiscal year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2012, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e8.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2013, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e9.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e11.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2015, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e9.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e8.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e7.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e8.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e9.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e9.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e9.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e8.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePreterm labor management\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute tocolysis with ritodrine*9, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e20.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium sulphate hydrate, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e21.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaesarean section, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e22.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeek of Delivery, mean, SD*4, Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e5.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeek of Delivery, median, IQR*5, Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay, mean, SD*4, Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e22.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay, median, IQR*5, day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e26.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*1 antenatal corticosteroid\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*2 standardized mean difference\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*3 continuous variable: Mann-Whitney U test, discrete variable: chi-square test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*4 standard deviation\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*5 interquartile range\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*6 body mass index\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*7 preterm premature rupture of membranes\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*8 Charlson comorbidity index\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*9\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;2days\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e \u003cp\u003eACS implementation rates in perinatal and non-perinatal centres increased annually (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). As shown in the box plot in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, ACS use rates varied substantially depending on the facility. Notably, while the variation among perinatal centres narrowed over time, the disparity among non-perinatal centres widened (Additional File 1a and 1b).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA comparison of the incidence of maternal adverse events between the two groups is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The rates of heart failure and pulmonary oedema were significantly higher in the ACS group than in the non-ACS group (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Overall, the incidence of LAEs was significantly higher in the ACS group than in the non-ACS group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Maternal adverse event Incidence Based on the Antenatal Corticosteroid Administration (N\u0026thinsp;=\u0026thinsp;43,824)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eACS *1\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;20,870\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003enon-ACS*1\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;22,954\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep*2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAEs*3, n,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver dysfunction, n,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArrhythmia, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary oedema, n,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypokalemia, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetal arrhythmia, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRhabdomyolysis, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutropenia, n, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational diabetes mellitus*4, n,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis, n,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal death, n,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*1 antenatal corticosteroid\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*2 continuous variable: Mann-Whitney U test, discrete variable: chi-square test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*3 LAEs: liver dysfunction, arrhythmia, heart failure, pulmonary oedema, hypokalemia, fetal arrhythmia, rhabdomyolysis, and neutropenia.\u003c/p\u003e \u003cp\u003e*4 onset during hospitalization\u003c/p\u003e \u003cp\u003eIn contrast, there were no significant differences between the two groups in terms of other complications, such as sepsis and gestational diabetes mellitus. There were also no significant differences in maternal mortality.\u003c/p\u003e \u003cp\u003eA multivariate logistic regression analysis was performed to assess the independent association between ACS administration and maternal adverse events (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Additional File 2). In Model 1 (adjusted for baseline maternal and institutional characteristics), ACS administration was significantly associated with pulmonary oedema (aOR: 2.45, 95% CI: 1.82\u0026ndash;3.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), heart failure (aOR: 1.55, 95% CI: 1.22\u0026ndash;1.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and LAEs (aOR: 1.17, 95% CI: 1.05\u0026ndash;1.31, p\u0026thinsp;=\u0026thinsp;0.006). However, in Model 2, which was further adjusted for the mode of delivery, the association between ACS and heart failure was attenuated and became less pronounced. Similarly, the association with any LAEs weakened after adjustment. In contrast, the significant risk of pulmonary oedema remained robust and was not affected by adjustment for caesarean sections.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStratified analysis by the mode of delivery clarified these associations (Additional File 3). For pulmonary oedema, the incidence was consistently higher in the ACS group than in the non-ACS group, regardless of the delivery mode (0.24% vs. 0.07% in vaginal delivery; 0.79% vs. 0.45% in caesarean section). However, for heart failure and LAEs the differences between the ACS and non-ACS groups were minimal among patients undergoing caesarean section (Heart failure: 1.02% vs. 0.85%; LAEs: 2.78% vs. 2.50%). These findings suggest that the risks of heart failure and LAEs were primarily driven by the mode of delivery or the underlying clinical severity requiring surgical intervention, rather than the ACS administration.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMain findings\u003c/h2\u003e \u003cp\u003eThis study used a large-scale national database to clarify the current trends in ACS implementation and the associated maternal risks under betamimetic (ritodrine)-based management in Japan. We found that although ACS implementation rates have increased significantly across all facility types over the past decade, a substantial disparity in clinical practice persists, particularly among non-perinatal centres. Furthermore, our multivariate analysis revealed that ACS administration was independently associated with a more than two-fold increase in the risk of pulmonary oedema, even after adjusting for potential confounders, including the mode of delivery. While the association between ACS and heart failure was partially attenuated by the inclusion of caesarean section in the model, the risk of pulmonary oedema remained robust, highlighting a specific safety concern in the unique Japanese context of long-term tocolysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTrends in ACS implementation rates\u003c/h2\u003e \u003cp\u003eWe evaluated the implementation status of ACS in preterm birth cases at less than 34 weeks of gestation, where ACS use was clinically indicated. While the implementation rate increased from fiscal year 2012 to 2022, it remains low compared with international standards [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Previous studies have shown that the organisational structure and functional capacity of healthcare facilities influence ACS implementation rates [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe observed disparity in ACS implementation rates among non-perinatal centres is particularly evident, given that our study population only included cases that eventually resulted in preterm delivery before 34 weeks. In cases where the clinical necessity for ACS is high, the widening variation in utilisation suggests institutional barriers beyond simple diagnoses. One important factor is the timing of the decision to administer ACS. In non-perinatal centres, emergent maternal transport may be the primary clinical priority, which can result in the deferral of ACS administration to the receiving tertiary care centre. In addition, the package insert for injectable betamethasone specifies that when betamethasone is administered as an antenatal corticosteroid, it should be given in settings where perinatal management at a higher-level medical facility is available. This may contribute to the reluctance to administer ACS in primary care settings. The lack of information on the clinical urgency of preterm labour in the DPC database, the second factor, may have influenced the ACS administration rate, as cases where labour progressed more rapidly than anticipated and the opportunity to administer ACS was missed were classified as non-ACS.\u003c/p\u003e \u003cp\u003eDespite these limitations, the ACS implementation rate has exhibited a distinct chronological shift. Prior to 2014, the Japan Society of Obstetrics and Gynecology guidelines limited ACS indications to preterm labour before 34 weeks and pPROM before 32 weeks. This was expanded in 2017 to include all cases of threatened preterm labour or pPROM before 34 weeks of gestation. The median implementation rate remained at 0% until 2016, indicating that half of the medical institutions had not used ACS. However, a significant increase was observed after the 2017 revision. This strongly suggests that the promotion of standardised preterm care and dissemination of knowledge through guidelines directly prompted behavioural changes among physicians, leading to improved ACS implementation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe impact of delivery mode on heart failure and LAEs\u003c/h2\u003e \u003cp\u003eIn the multivariate logistic regression model (Model 1), pulmonary oedema, heart failure, and LAEs were significantly associated with ACS. However, after adjusting for the mode of delivery (Model 2), the association between heart failure and LAEs lost statistical significance, whereas the association with pulmonary oedema remained robust. We also confirmed significant associations between magnesium sulphate or hypertensive disorders of pregnancy and pulmonary oedema, heart failure, and LAEs, as reported in previous studies [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese results suggest that the association between ACS and heart failure/LAEs is strongly confounded by delivery mode. Generally, vaginal delivery is preferred in pregnancies complicated by heart disease to avoid sudden haemodynamic shifts; however, caesarean section is often necessitated by haemodynamic instability or treatment-resistant heart failure [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In preterm births (before 34 weeks of gestation), patients who develop heart failure prior to delivery are highly likely to undergo caesarean section. Thus, the primary risk factor for heart failure may not be ACS administration, but rather the underlying clinical severity that necessitates caesarean section. Because LAEs are also associated with maternal vulnerability and severity, the loss of significance of ACS in this context is consistent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDirect pharmacological association between ACS and pulmonary oedema\u003c/h2\u003e \u003cp\u003eIn contrast, the association between ACS and pulmonary oedema remained significant, with little change in the odds ratio after adjusting for caesarean section. This indicates that the underlying mechanisms and risk factors for pulmonary oedema differ from those for heart failure. High-dose corticosteroids may increase pulmonary capillary pressure by altering vascular reactivity, thereby potentially increasing the risk of pulmonary oedema [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition, by upregulating β-adrenergic receptor expression, high-dose corticosteroids may enhance the adverse effects of ritodrine, including increased cardiac output and fluid retention [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Indeed, an increased risk of pulmonary oedema has been reported with the concomitant use of ritodrine and ACS [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In Japan, where ACS is frequently administered concurrently with betamimetics that independently cause pulmonary oedema, this synergistic effect requires heightened vigilance.\u003c/p\u003e \u003cp\u003eEarly detection of pulmonary oedema requires strict monitoring of vital signs. However, the measurement rate of Early Warning Score components, particularly respiratory rate, is low in Japanese obstetric settings [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. International studies have suggested that systems, such as the Maternal Early Warning Trigger or the Modified Obstetric Early Warning Score, significantly improve the outcomes of severe complications, including pulmonary oedema [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. To mitigate the risks identified in this study, it is essential to implement systematic vital sign monitoring with a specific focus on respiratory rate and fluid balance, alongside comprehensive patient education. Recognising early symptoms of fluid overload is paramount for the safe administration of ACS under tocolytic management.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eA major strength of this study is that it is the first to quantitatively evaluate the impact of ACS on maternal adverse events under high-risk conditions typical of clinical practice (i.e., concurrent tocolytic therapy) using a nationwide database. By limiting the cohort to patients receiving ritodrine, we maintained the effect of betamimetics, allowing us to isolate the additional risks posed by ACS and effectively adjust for confounding factors. Furthermore, the divergent results for pulmonary oedema versus heart failure/LAEs after adjustment demonstrated the separation of statistical confounding factors from pharmacological effects, enhancing the biological plausibility of our findings. These results are highly applicable in clinical settings using the betamimetic tocolytic strategy worldwide.\u003c/p\u003e \u003cp\u003eNevertheless, this study has some limitations must be considered. The DPC database lacks detailed clinical parameters, such as cervical dilation, cardiotocography findings, or laboratory data (e.g., B-type natriuretic peptide or inflammatory markers). The absence of granular data may preclude a definitive assessment of the clinical severity of preterm labour or the precise timing of ACS administration. Because our analysis relied on the ICD-10 diagnostic codes, we could not evaluate the clinical severity or specific diagnostic criteria used for heart failure or pulmonary oedema at individual institutions. Although the DPC database has been validated for the accuracy of major diagnoses, misclassification or under-reporting remains possible. Finally, because this was a retrospective observational study, the possibility of unmeasured confounding factors, such as specific fluid management protocols at each hospital, cannot be entirely excluded. To address these limitations, prospective studies are warranted to assess clinical severity and the precise timing of ACS administration, which are not captured in the DPC database. Prospective collection of detailed information on maternal conditions and treatments before and after ACS administration would enable more robust evaluation of causal relationships. Moreover, improved assessment of the severity of threatened preterm labour may help identify reasons for non-administration and inform strategies for increasing ACS implementation rates.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWhile the ACS implementation rate in Japan has been increasing over the past decade, institutional disparities are widening, particularly in non-perinatal centres. Our findings demonstrate that ACS administration is independently associated with an increased risk of pulmonary oedema under ritodrine-based management, even after accounting for delivery mode. To ensure maternal safety, clinicians must implement rigorous monitoring, specifically focusing on the respiratory rate and fluid balance, for the early detection and management of fluid overload in this high-risk population. The optimisation of ACS administration by balancing maternal risks with the primary goal of improving neonatal outcomes remains a critical challenge.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eantenatal corticosteroid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiagnosis Procedure Combination\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICD-10\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Classification of Diseases Tenth Revision\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLAEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elisted adverse events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003epPROM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epreterm premature rupture of membranes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eaORs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadjusted odds ratios\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was approved by the Institutional Review Board of the Institute of Science, Tokyo (approval number: M2000-788). The requirement for individual informed consent was waived as the data did not contain any personally identifiable information.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe study was supported by the Sasakawa Health Foundation (2025-07). The funders had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript. The funding source had no role in the design of the study, data collection, analysis, interpretation, or writing of the manuscript. No medical writer or editor was involved in the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAyako Fudono and Mikayo Toba wrote the main manuscript text. Mikayo Toba performed the analysis and prepared the figures and tables. Mutsuko Moriwaki was responsible for the methodology and overall structure of the manuscript. Masayuki Kakehashi supervised the statistical analysis. Rie Oi reviewed and revised the entire manuscript. Kiyohide Fushimi provided the data resources. Naoyuki Miyasaka was responsible for overall supervision. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank Shunji Shimoda from the National Hospital Organization Headquarters for providing technical support in the extraction and management of patient data.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available because the datasets contain personal information but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcGoldrick E, Stewart F, Parker R, Dalziel SR. Antenatal corticosteroids for accelerating fetal lung maturation for women at risk of preterm birth. Cochrane Database Syst Rev. 2020;12:CD004454.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEffect of corticosteroids for fetal maturation on perinatal outcomes. 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Authorea [Preprint]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.22541/au.176589198.88944514/v1\u003c/span\u003e\u003cspan address=\"10.22541/au.176589198.88944514/v1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 2025 Dec 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurata T, Kyozuka H, Shiraiwa A, Isogami H, Fukuda T, Kanno A, et al. Maternal pulmonary edema after 46 h of ritodrine hydrochloride administration: A case report. Case Rep Womens Health. 2020;25:e00173.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNishikawa T, Fukuhara K. Betamethasone use and risk factors for pulmonary edema during the perinatal period: A single-center retrospective cohort study in Japan. BMC Pregnancy Childbirth. 2022;22:636.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarter SWD, Fee EL, Usuda H, Oguz G, Ramasamy A, Amin Z, et al. 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Acute pulmonary edema in pregnancy. Obstet Gynecol. 2003;101:511\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMersha AG, Abegaz TM, Seid MA. Maternal and perinatal outcomes of hypertensive disorders of pregnancy in Ethiopia: systematic review and meta-analysis. BMC Pregnancy Childbirth. 2019;19:458.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldstein SA, Pagidipati NJ. Hypertensive Disorders of Pregnancy and Heart Failure Risk. Curr Hypertens Rep. 2022;24(7):205\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarasa A, Rosengren A, Sandstr\u0026ouml;m TZ, Ladfors L, Schaufelberger M. Heart Failure in Late Pregnancy and Postpartum: Incidence and Long-Term Mortality in Sweden From 1997 to 2010. J Card Fail. 2017;23:370\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRegitz-Zagrosek V, Roos-Hesselink JW, Bauersachs J, Blomstr\u0026ouml;m-Lundqvist C, C\u0026iacute;fkov\u0026aacute; R, De Bonis M, et al. 2018 ESC Guidelines for the management of cardiovascular diseases during pregnancy. Eur Heart J. 2018;39:3165\u0026ndash;241.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJCS. Guideline on Indication and Management of Pregnancy and Delivery in Women with Heart Disease; 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeFilippis EM, Bhagra C, Casale J, Ging P, Macera F, Punnoose L, et al. Cardio-obstetrics and heart failure: JACC: Heart failure state-of-the-art review. JACC Heart Fail. 2023;11:1165\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAraujo JEDS, Miguel-Dos-Santos R, Macedo FN, Cunha PS, Fontes MT, Murata GM, et al. Effects of high doses of glucocorticoids on insulin-mediated vasodilation in the mesenteric artery of rats. PLoS ONE. 2020;15:e0230514.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMak JC, Nishikawa M, Barnes PJ. Glucocorticosteroids increase beta 2-adrenergic receptor transcription in human lung. Am J Physiol. 1995;268(1 Pt 1):L41\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamada O, Tsutsumi T, Tsunemitsu A, Sasaki N, Imanaka Y. Improving respiratory rate monitoring in general wards following implementation of a rapid response system: A quality improvement initiative. BMJ Open Qual. 2025;14:e003218.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShields LE, Wiesner S, Klein C, Pelletreau B, Hedriana HL. Use of Maternal Early Warning Trigger tool reduces maternal morbidity. Am J Obstet Gynecol. 2016;214:e5271\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArnolds DE, Smith A, Banayan JM, Holt R, Scavone BM. National partnership for maternal safety recommended maternal early warning criteria are associated with maternal morbidity. Anesth Analg. 2019;129:1621\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"antenatal corticosteroids, pulmonary oedema, maternal adverse events, betamimetics, preterm birth","lastPublishedDoi":"10.21203/rs.3.rs-8892829/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8892829/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAntenatal corticosteroids (ACS) are effective in improving the prognosis of preterm infants; however, their use rate in Japan is low, and large-scale studies on maternal safety are lacking. Therefore, this study aimed to clarify the association between ACS use and adverse maternal events in preterm births before 34 weeks of gestation treated with ritodrine hydrochloride (ritodrine).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing nationwide data from fiscal year 2012 to 2022, we investigated 43,824 pregnant women who received ritodrine and experienced preterm births before 34 weeks of pregnancy. We calculated the trend in ACS implementation rates and examined their association with adverse maternal events using multivariate logistic regression analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe ACS implementation rates increased significantly from 26.9% to 59.8%, but the disparities between facilities widened. The ACS group had significantly higher rates of side effects of ritodrine listed in the package insert (listed adverse events; LAEs), heart failure, and pulmonary oedema. Multivariate analysis revealed that pulmonary oedema (adjusted odds ratio [aOR]: 2.45, 95% confidence interval [CI]: 1.82\u0026ndash;3.30), heart failure (aOR: 1.55, 95% CI: 1.22\u0026ndash;1.96), and LAEs (aOR: 1.17, 95% CI: 1.05\u0026ndash;1.31) were associated with ACS use. However, when caesarean section was added as an adjustment variable, only the association with pulmonary oedema (aOR: 1.92, 95% CI: 1.25\u0026ndash;2.95) remained significant.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAlthough the implementation rate of ACS is increasing, the differences between facilities are widening, making standardisation an urgent issue. Furthermore, because ACS use with ritodrine administration is strongly associated with pulmonary oedema independent of maternal severity, strict monitoring of vital signs, including respiratory rate, and appropriate information provision are essential.\u003c/p\u003e\u003ch2\u003eTrial Registration\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Maternal Adverse Events Associated with Antenatal Corticosteroids under Betamimetic Tocolysis in Preterm Birth Before 34 Weeks: An 11-Year Nationwide Database Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-11 06:05:52","doi":"10.21203/rs.3.rs-8892829/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"59472777894894196925070457931881112315","date":"2026-05-07T06:38:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-27T06:54:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"320085779563476758351780494894828371775","date":"2026-03-26T16:24:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-05T04:17:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-18T17:21:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-17T00:12:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-17T00:11:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2026-02-16T11:32:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c285548-c656-4ae5-a501-23348e8b7d7f","owner":[],"postedDate":"March 11th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"59472777894894196925070457931881112315","date":"2026-05-07T06:38:50+00:00","index":111,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-11T06:05:53+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-11 06:05:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8892829","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8892829","identity":"rs-8892829","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}