Aim: We aimed to identify factors associated with massive post-partum bleeding in pregnancies with placenta previa and to establish a scoring model to predict post-partum severe bleeding. Methods: A retrospective cohort study was performed in 506 healthy singleton pregnancies with placenta previa from 2006 to 2016. Cases with intraoperative blood loss (≥2000 mL), packed red blood cells transfusion (≥4), uterine artery embolization, or hysterectomy were defined as massive bleeding. After performing multivariable analysis, using the adjusted odds ratios (aOR), we formulated a scoring model. Results: Seventy-three women experienced massive post-partum bleeding (14.4%). After multivariable analysis, seven variables were associated with massive bleeding: maternal old age (≥35 years; aOR 1.79, 95% confidence interval [CI] 1.00-3.20, P = 0.049), antepartum bleeding (aOR 4.76, 95%CI 2.01-11.02, P < 0.001), non-cephalic presentation (aOR 3.41, 95%CI 1.40-8.30, P = 0.007), complete placenta previa (aOR 1.93, 95% CI 1.05-3.54, P = 0.034), anterior placenta (aOR 2.74, 95%CI 1.54-4.89, P = 0.001), multiple lacunae (≥4; aOR 2.77, 95%CI 1.54-4.99, P = 0.001), and uteroplacental hypervascularity (aOR 4.51, 95%CI 2.30-8.83, P < 0.001). We formulated a scoring model including maternal old age (<35: 0, ≥35: 1), antepartum bleeding (no: 0, yes: 2), fetal non-cephalic presentation (no: 0, yes: 2), placenta previa type (incomplete: 0, complete: 1), placenta location (posterior: 0, anterior: 1), uteroplacental hypervascularity (no: 0, yes: 2), and multiple lacunae (no: 0, yes: 1) to predict post-partum massive bleeding. According to our scoring model, a score of 5/10 had a sensitivity of 81% and a specificity of 77% for predicting massive post-partum bleeding. The area under the receiver-operator curve was 0.856 (P < 0.001). The negative predictive value was 95.9%. Conclusion: Our scoring model might provide useful information for prediction of massive post-partum bleeding in pregnancies with placenta previa.
ProblemMaternal inflammation leads to preterm birth and perinatal brain injury. Melatonin, through its anti‐inflammatory effects, has been shown to be protective against inflammation‐induced perinatal adverse effects. However, the immunomodulatory effects of melatonin on preterm birth and prematurity‐related morbidity remain unknown. We wanted to investigate the effects of maternally administered melatonin on preterm birth and perinatal brain injury in a mouse model of maternal inflammation.Method of studyA model of maternal inflammation employing lipopolysaccharide (LPS) was used to mimic the most common clinical scenario of preterm birth, that of maternal inflammation. Mice were randomly divided into the following groups: control, LPS, and LPS with melatonin pre‐treatment. Doppler ultrasonography was used to obtain fetal and maternal hemodynamic measurements in utero. Placenta and fetal brains were harvested and analyzed for proinflammatory markers and signs of perinatal brain injury, respectively. Surviving offspring were assessed for neuromotor outcomes.ResultsMelatonin pre‐treatment lowered the level of proinflammatory cytokines in the uterus and the placenta, significantly improved LPS‐induced acute fetal neuroinflammation and perinatal brain injury, as well as significantly upregulated the SIRT1/Nrf2 signaling pathway to reduce LPS‐induced inflammation. Melatonin also prevented adverse neuromotor outcomes in offspring exposed to maternal inflammation.ConclusionMaternally administered melatonin modulated immune responses to maternal inflammation and decreased preterm birth and perinatal brain injury. These results suggest that melatonin, a safe treatment during pregnancy, may be used as an experimental therapeutic in clinical trials.
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