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(1) Background: Although the diagnostic criteria for massive hemorrhage with organ dysfunction, such as disseminated intravascular coagulation associated with delivery, have been empirically established based on clinical findings, strict logic has yet to be used to establish numerical criteria. (2) Methods: A dataset of 107 deliveries with >2000 mL of blood loss, among 13,368 deliveries, was obtained from nine national perinatal centers in Japan between 2020 and 2023. Twenty-three patients had fibrinogen levels <170 mg/dL, which is the initiation of coagulation system failure, according to our previous reports. Three of these patients had hematuria. We used six machine learning methods to identify the borderline criteria dividing the fibrinogen/fibrin/fibrinogen degradation product (FDP) planes, using 15 coagulation fibrinolytic factors. (3) Results: The boundaries of hematuria development on a two-dimensional plane of fibrinogen and FDP were obtained. A positive FDP–fibrinogen/3–60 (mg/dL) value indicates hematuria; otherwise, the case is nonhematuria, as demonstrated by the support vector machine method that seemed the most appropriate. (4) Conclusions: Using artificial intelligence, the borderline criterion was obtained, which divides the fibrinogen/FDP plane for patients with hematuria that could be considered organ dysfunction in massive hemorrhage during delivery; this method appears to be useful. [ABSTRACT FROM AUTHOR]

Aims/Introduction: In Japan, the increasing frequency of underweight among women of reproductive age and the accompanying increase in the rate of low birth weight (LBW) are social issues. The study aimed to establish a prospective registry system for gestational diabetes mellitus (GDM) in Japan and to clarify the actual status of GDM according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Materials and Methods: Pregnant women with gestational diabetes mellitus and those in the normal glucose tolerance (NGT) group were enrolled in the Diabetes and Pregnancy Outcome for Mother and Baby study from October 2015. Pregnant women with positive glucose screening in early and mid‐to‐late pregnancy underwent a 75 g oral glucose tolerance test by gestational week 32. Gestational diabetes mellitus was diagnosed according to IADPSG criteria. Women with a positive glucose screening test at mid‐to‐late pregnancy but NGT were enrolled as references (NGT group). Treatment for gestational diabetes mellitus and maternal and neonatal pregnancy data were prospectively collected on outcomes. Results: In total 1,795 singleton pregnancies (878 women with GDM and 824 NGT women) were analyzed. The risk of LBW and small‐for‐gestational age in the GDM group was significantly higher than in the NGT group. A similar relationship was found for LBW risk in the non‐overweight/obese group but not in the overweight/obese group. Conclusions: We established a prospective GDM registry system in Japan. In the management of GDM in Japan, suppression of maternal weight gain may be associated with reduced fetal growth, especially in non‐overweight/obese women with GDM; however, further investigation is required. [ABSTRACT FROM AUTHOR]

Amniotic fluid infection with Ureaplasma urealyticum or Mycoplasma hominis can cause chorioamnionitis and preterm birth. The aim of this study was to examine whether vaginal Ureaplasma urealyticum/Mycoplasma hominis colonization is predictive of preterm delivery in patients exhibiting signs of threatened preterm birth or those with asymptomatic short cervix. The present retrospective study, which was performed in a perinatal tertiary center, included patients carrying a singleton pregnancy who were referred to the emergency Ob/Gyn unit because of regular preterm uterine contractions and/or short cervical length (<20 mm) at 22–33 weeks of gestation, and in whom a vaginal U. urealyticum/M. hominis examination (Urea-arginine LYO-2, BioMerieux®) was performed. Univariate and multivariate analyses were performed to assess the association between vaginal U. urealyticum or M. hominis and chorioamnionitis or preterm delivery. The median gestational age of the 94 enrolled patients was 29.9 weeks, and 54 (57%) of the patients were vaginal U. urealyticum/M. hominis-positive. The preterm delivery rate in the positive group was higher than in the negative group (53 versus 25%; p =.007). Vaginal U. urealyticum/M. hominis positivity was found to be an independent risk factor for preterm birth at <37 weeks of gestation (adjusted odds ratio = 4.0, 95% confidence interval, 1.1–15.3) in a multivariate analysis adjusted for age, history of preterm delivery and conization, gestational age, cervical length, presence of vaginal bleeding, vaginal fetal fibronectin and serum C-reactive protein at test. U. urealyticum/M. hominis positivity was not associated with delivery at <34 weeks or chorioamnionitis. A positive vaginal U. urealyticum/M. hominis culture is an independent predictive factor for preterm birth in patients with symptomatic threatened preterm labor and/or short cervix. [ABSTRACT FROM AUTHOR]

The aim of this study was to compare the benefits and hemodynamic side effects of oxytocin between intravenous infusion with and without a bolus injection during a caesarean section. Women with singleton pregnancies who underwent caesarean sections under spinal anaesthesia were included. Oxytocin was administered by an iv bolus injection (5 U) followed by an intravenous infusion (10 U of oxytocin in 500 mL normal saline); this was switched to just an intravenous infusion. The amount of blood loss did not differ between the groups. In a multivariate analysis, the adjusted odds ratios for the risk of hypotension (≥20% reduction of systolic BP) and tachycardia (heart rate ≥100 bpm) were 4.5 (95% confidence interval [CI], 1.6–12.5) and 3.7 (95%CI 1.9–7.2) in the iv bolus group, respectively, compared with the just the infusion group. The oxytocin administration by iv bolus injection did not decrease blood loss and increased the rate of hemodynamic side effects. What is already known on this subject? Oxytocin is used as the first-line uterotonic treatment to prevent a postpartum haemorrhage in women undergoing Caesarean Sections. Oxytocin is known to relax vascular smooth muscle, which can cause hypotension and tachycardia. The protocols for administering oxytocin during CS vary by institution. What do the results of this study add? Combined treatment with oxytocin by iv bolus injection (5 U) followed by iv infusion (10 U of oxytocin in 500 mL normal saline) during CS increased the risk of developing adverse hemodynamic side effects, including hypotension, tachycardia, and the need for vasopressors, without any benefit in the control of intraoperative blood loss in comparison to iv infusion alone. What are the implications of these findings for clinical practice and/or further research? We should abandon the iv bolus injection of oxytocin during CS, especially for women undergoing an elective CS who are not in labour. [ABSTRACT FROM AUTHOR]

Aim: To investigate the feasibility of a novel method using artificial intelligence (AI), in which the fibrinogen criterion was determined by the quantitative relation between the distributions of fibrin/fibrinogen degradation products (FDPs) and fibrinogen. Methods: A dataset of 154 deliveries comprising more than 2000 g of blood lost due to hemorrhage, excluding disseminated intravascular coagulation (DIC), among patients from eight national perinatal centers in Japan from 2011 to 2015 were obtained. The fibrinogen threshold criterion was identified by using the function that best fit the distributions of FDP as determined by AI. FDP production was described by differential equations using a dataset containing fibrinogen levels less than the fibrinogen criterion and solved numerically. Results: A fibrinogen level of 237 mg/dL as the threshold criterion was obtained. The FDP threshold criteria were 2.0 and 8.5 mg/dL for no coagulopathy and a failed coagulation system, respectively. Conclusion: The fibrinogen threshold criterion for patients with massive hemorrhage excluding DIC at delivery were obtained by selecting the functions that best fit the distributions of FDP data by using AI. [ABSTRACT FROM AUTHOR]