Maternal death analysis based on data from the nationwide registration system in Japan (2010-2018)

Clinical Prediction of Retained Products of Conception: Combining Obstetric History and Ultrasound for Improved Accuracy in Severe Postpartum Hemorrhage

Background The current challenge is how to improve the management of postpartum hemorrhage (PPH) to reduce the maternal mortality rate further. This study aimed to investigate whether a combined specific obstetric history and ultrasonographic findings can improve the predictive accuracy of retained products of conception (RPOC) with severe PPH. Methods This retrospective study included 56 patients who were diagnosed with RPOC. We extracted the following clinical data: obstetric history of second-trimester miscarriage, the time at which there was clinical suspicion of RPOC after the previous pregnancy (TIME), grayscale ultrasonographic finding (RPOC long-axis length [SIZE]), and color Doppler ultrasonographic finding based on the Gutenberg classification (RPOC hypervascularity). In this study, we defined cases requiring blood transfusion therapy or transcatheter arterial embolization as severe PPH. The patients were divided into two groups according to the presence or absence of severe PPH. The predictors of severe PPH were evaluated using logistic regression models. Model A comprised a combination of second-trimester miscarriage and TIME, Model B comprised a combination of Model A and long-axis SIZE, and Model C comprised a combination of Model B and RPOC hypervascularity. Results The multivariable analysis showed that long-axis SIZE was the only significant predictor of severe PPH (odds ratio [OR], 10.38; 95% confidence interval [CI], 2.06-63.86) independent of second-trimester miscarriage, TIME, and RPOC hypervascularity. The c-statistic was higher in Model C (OR, 0.863; 95% CI, 0.731-0.936) than in Model A (OR, 0.723; 95% CI, 0.551-0.847) and Model B (OR, 0.834; 95% CI, 0.677-0.923). Conclusion Combining a specific obstetric history (second-trimester miscarriage and TIME) and ultrasonographic findings (long-axis SIZE and RPOC hypervascularity) improves the predictive accuracy of RPOC with severe PPH. This prediction model may be a useful clinical screening tool for RPOC with severe PPH.

Massive platelet-rich thrombus formation in small pulmonary vessels in amniotic fluid embolism: An autopsy study

OBJECTIVE

To identify pulmonary/uterine thrombus formation in amniotic fluid embolism (AFE).

DESIGN

Retrospective, observational.

SETTING

Nationwide.

POPULATION

Eleven autopsy cases of AFE and control cases.

METHODS

We assessed pulmonary and uterine thrombus formation and thrombus area in AFE and pulmonary thromboembolism (PTE) as a control. The area of platelet glycoprotein IIb/IIIa, fibrin, neutrophil elastase, citrullinated histone H3 (a neutrophil extracellular trap marker) and mast cell chymase immunopositivity was measured in 90 pulmonary emboli, 15 uterine thrombi and 14 PTE.

MAIN OUTCOME MEASURES

Pathological evidence of thrombus formation and its components in AFE.

RESULTS

Amniotic fluid embolism lung showed massive thrombus formation, with or without amniotic emboli in small pulmonary arteries and capillaries. The median pulmonary thrombus size in AFE (median, 0.012 mm2 ; P < 0.0001) was significantly smaller than that of uterine thrombus in AFE (0.61 mm2 ) or PTE (29 mm2 ). The median area of glycoprotein IIb/IIIa immunopositivity in pulmonary thrombi in AFE (39%; P < 0.01) was significantly larger than that of uterine thrombi in AFE (23%) and PTE (15%). The median area of fibrin (0%; P < 0.001) and citrullinated histone H3 (0%; P < 0.01) immunopositivity in pulmonary thrombi in AFE was significantly smaller than in uterine thrombi (fibrin: 26%; citrullinated histone H3: 1.1%) and PTE (fibrin: 42%; citrullinated histone H3: 0.4%). No mast cells were identified in pulmonary thrombi.

CONCLUSIONS

Amniotic fluid may induce distinct thrombus formation in the uterus and lung. Pulmonary and uterine thrombi formation may contribute to cardiorespiratory collapse and/or consumptive coagulopathy in AFE.

Fatal amniotic fluid embolism: incidence, risk factors and influence on perinatal outcome

PURPOSE

This study aimed to estimate the incidence of fatal amniotic fluid embolism, describe its risk factors, and analyze perinatal outcomes.

METHODS

Maternity cases and newborn records of amniotic fluid embolism were collected from the Zhejiang Maternal Surveillance System from October 2006 to October 2019. This study strictly limited the diagnostic criteria for AFE and excluded suspicious cases in order to minimize false-positive AFE cases. The risk factors of fatal amniotic fluid embolism and the relationship between perinatal prognosis and AFE were investigated using logistic regression analysis, estimating the adjusted odds ratios (aORs) and 95% confidence intervals (CIs).

RESULTS

149 cases of amniotic fluid embolism were registered, of which 80 cases were fatal. The estimated fatal AFE incidence was 0.99 per 100,000. The occurrence of fatal AFE was significantly correlated with spontaneous vaginal delivery (aOR 12.3, 95% CI 3.3-39.2) and cardiac arrest (aOR 64.8, 95% CI 14.6-287.8). The average diagnosis time of fatal AFE is 85.51 min, and the peak period of female death is 1-12 h after the onset of the disease, accounting for 60% (48/80) of cases. Fatal amniotic embolism is a cause of intrauterine fetal death and fetal death during delivery (aOR 11.957, 95% CI 1.457-96.919; aOR 13.152, 95% CI 1.636-105.723). Of the 149 confirmed AFE cases, 11 cases of stillbirth occurred, 12 cases were stillborn, and 7 cases of neonatal death were reported. The perinatal mortality rate was 202 per 1000.

CONCLUSIONS

Early detection, diagnosis, and treatment of amniotic fluid embolism are essential to avoiding fatal AFE. Clinicians should fully evaluate the pros and cons of choosing the delivery method for pregnant women. When cardiac arrest occurs in women with amniotic fluid embolism, obstetricians should be particularly careful and provide timely and effective treatment to minimize the fatality rate. The outcome of AFE is not only related to maternal survival but also plays a decisive role in the prognosis of the infant over the perinatal period.

Machine learning prediction models for postpartum depression: A multicenter study in Japan

AIM

Postpartum depression (PPD) and perinatal mental health care are of growing importance worldwide. Here we aimed to develop and validate machine learning models for the prediction of PPD, and to evaluate the usefulness of the recently adopted 2-week postpartum checkup in some parts of Japan for the identification of women at high risk of PPD.

METHODS

A multicenter retrospective study was conducted using the clinical data of 10 013 women who delivered at ≥35 weeks of gestation at 12 maternity care hospitals in Japan. PPD was defined as an Edinburgh Postnatal Depression Scale score of ≥9 points at 4 weeks postpartum. We developed prediction models using conventional logistic regression and four machine learning algorithms based on the information that can be routinely collected in daily clinical practice. The model performance was evaluated using the area under the receiver operating characteristic curve (AUROC).

RESULTS

In the machine learning models developed using clinical data before discharge, the AUROCs were similar to those in the conventional logistic regression models (AUROC, 0.569-0.630 vs. 0.626). The incorporation of additional 2-week postpartum checkup data into the model significantly improved the predictive performance for PPD compared to that without in the Ridge regression and Elastic net (AUROC, 0.702 vs. 0.630 [p < 0.01] and 0.701 vs. 0.628 [p < 0.01], respectively).

CONCLUSIONS

Our machine learning models did not achieve better predictive performance for PPD than conventional logistic regression models. However, we demonstrated the usefulness of the 2-week postpartum checkup for the identification of women at high risk of PPD.