Pregnancy-related mortality in the United States, 2003-2016: age, race, and place of death

Health Care Disparities and the Emergency Management of Postpartum Patients with Cardiovascular Complaints

OBJECTIVE

 This study aimed to determine health care disparities in evaluation and admission among underserved racial and ethnic minority groups presenting with cardiovascular complaints during the first postpartum year according to patient and provider demographics.

STUDY DESIGN

 A retrospective cohort study was performed on all postpartum patients who sought emergency care between February 2012 and October 2020 in a large urban care center in Southeastern Texas. Patient information was collected according to International Classification of Diseases 10th Revision codes and individual chart analysis. Race, ethnicity, and gender information were self-reported for both patients on hospital enrollment forms and emergency department (ED) providers on their employment records. Statistical analysis was performed with logistic regression and Pearson's chi-square test.

RESULTS

 Of 47,976 patients who delivered during the study period, 41,237 (85.9%) were black, Hispanic, or Latina and 490 (1.1%) presented to the ED with cardiovascular complaints. Baseline characteristics were similar between groups; however, Hispanic or Latina patients were more likely to have had gestational diabetes mellitus during the index pregnancy (6.2 vs. 18.3%). There was no difference in hospital admission between groups (17.9% black vs. 16.2% Latina or Hispanic patients). There was no difference in the hospital admission rate by provider race or ethnicity overall (p = 0.82). There was no difference in the hospital admission rate when a patient was evaluated by a provider of a different race or ethnicity (relative risk [RR] = 1.08, CI: 0.6-1.97). There was no difference in the rate of admission according to the self-reported gender of the provider (RR = 0.97, CI: 0.66-1.44).

CONCLUSION

 This study illustrates that disparities did not exist in the management of racial and ethnic minority groups who presented to the ED with cardiovascular complaints during the first postpartum year. Patient-provider discordance in race or gender was not a significant source of bias or discrimination during the evaluation and treatment of these patients.

KEY POINTS

· Adverse postpartum outcomes disproportionately affect minorities.. · There was no difference in admissions between minority groups.. · There was no difference in admissions by provider race and ethnicity..

The role of cultural competency training to address health disparities in surgical settings

BACKGROUND

Disparities in health care delivered to marginalized groups are unjust and result in poor health outcomes that increase the cost of care for everyone. These disparities are largely avoidable and health care providers, have been targeted with education and specialised training to address these disparities.

SOURCES OF DATA

In this manuscript we have sought out both peer-reviewed material on Pubmed, as well as policy statements on the potential role of cultural competency training (CCT) for providers in the surgical care setting. The goal of undertaking this work was to determine whether there is evidence that these endeavours are effective at reducing disparities.

AREAS OF AGREEMENT

The unjustness of health care disparities is universally accepted.

AREAS OF CONTROVERSY

Whether the outcome of CCT justifies the cost has not been effectively answered.

GROWING POINTS

These include the structure/content of the CCT and whether the training should be delivered to teams in the surgical setting.

AREAS TIMELY FOR DEVELOPING RESEARCH

Because health outcomes are affected by many different inputs, should the effectiveness of CCT be improvement in health outcomes or should we use a proxy or a surrogate of health outcomes.

Pregnancy and Postpartum Drug Overdose Deaths in the US Before and During the COVID-19 Pandemic

Importance

Knowledge about characteristics of US pregnancy-associated decedents is needed to guide responses.

Objective

To examine individual sociodemographic characteristics and residing county's health care resources and socioeconomic factors among pregnancy-associated overdose decedents in comparison with obstetric decedents and overdose decedents who were not pregnant in the past year.

Design, Setting, and Participants

This cross-sectional, exploratory study included 1457 pregnant and postpartum overdose decedents, 4796 obstetric decedents, and 11 205 nonpregnant overdose decedents aged 10 to 44 years from 2018 to 2021. Data were analyzed August 2023.

Exposures

Decedents from the 2018-2021 Multiple Cause of Death Files linked to the 2021 Area Health Resources Files and the 2018-2021 County Health Rankings data at the county level.

Main Outcomes and Measures

Pregnancy-associated deaths were defined as deaths during pregnancy or within 1 year of pregnancy termination. This study focused on unintentional drug overdoses or drug overdoses with undetermined intent involving the most common psychotropic drugs of misuse.

Results

From 2018 to 2021, across the pregnancy-postpartum continuum, pregnancy-associated overdose mortality ratios consistently increased among women aged 10 to 44 years. Mortality ratio more than tripled among pregnant and postpartum women aged 35 to 44 years from 4.9 (95% CI, 3.0-8.0) per 100 000 mothers aged 35 to 44 years with a live birth in January to June 2018 to 15.8 (95% CI, 12.3-20.4) in July to December 2021 (average semiannual percentage changes, 15.9; 95% CI, 8.7-23.6; P < .001). Compared with pregnant obstetric decedents, pregnant overdose decedents had increased odds of being aged 10 to 34 years (75.4% vs 59.5%; range of odds ratios [ORs], 1.8 [95% CI, 1.3-2.5] for ages 10 to 24 years to 2.2 [95% CI, 1.7-2.8] for ages 25 to 34 years), being non-college graduates (72.1% vs 59.4%; range of ORs, 2.7 [95% CI, 1.7-4.3] for those with some college education to 3.9 [95% CI, 2.4-6.1] for those with less than high school education), being unmarried (88.0% vs 62.1%; OR, 4.5; 95% CI, 3.7-6.0), and dying in nonhome, non-health care settings (25.9% vs 4.5%; OR, 2.5; 95% CI, 1.8-3.6) and were associated with decreased odds of dying in health care settings (34.7% vs 77.6%; range of ORs, 0.1 [95% CI, 0.1-0.1] for those who died in hospital inpatient settings to 0.4 [95% CI, 0.3-0.6] for those who died in hospital outpatient/emergency room settings).

Conclusions and Relevance

From 2018 to 2021, the mortality ratio more than tripled among pregnant and postpartum women aged 35 to 44 years, consistent with increases in overdose mortality across US populations. Most pregnancy-associated overdose deaths occurred outside health care settings, indicating the need for strengthening community outreach and maternal medical support. To reduce pregnancy-associated overdose mortality, evidence-based interventions are urgently needed at individual, health care, local, and national levels, along with nonpunitive approaches incentivizing pregnant and postpartum women to seek substance use disorder treatments.

High maternal mortality rate associated with advanced maternal age in Japan

This study aimed to clarify the relationship between maternal mortality and advanced maternal age in Japan and to provide useful information for future perinatal management. Maternal death rates by age group were investigated for all maternal deaths in Japan for an 11-year period, from 2010 to 2021. Maternal deaths among those aged ≥ 40 years were examined in detail to determine the cause, and the number of deaths by cause was calculated. The causes of onset of the most common causes of death were also investigated. The maternal mortality rates were 0.8 (95% confidence interval [CI] 0.3-4.7) for < 20 years, 2.6 (95% CI 1.7-3.8) for 20-24 years, 2.9 (95% CI 2.3-3.6) for 25-29 years, 3.9 (95% CI 3.3-4.5) for 30-34 years, 6.8 (95% CI 5.9-7.9) for 35-39 years, and 11.2 (95% CI 8.8-14.3) for ≥ 40 years of age. Patients who were ≥ 40 years of age had a significantly higher mortality rate compared to that in other age groups. Hemorrhagic stroke was the most common cause of death in patients aged ≥ 40 years (15/65 [23%]), and preeclampsia (8/15 [54%]) was the most common cause of hemorrhagic stroke. Maternal mortality is significantly higher in older than in younger pregnant women in Japan, with hemorrhagic stroke being the most common cause of maternal death among women > 40 years of age. More than half of hemorrhagic strokes are associated with hypertension disorder of pregnancy. These facts should be considered by women who become pregnant at an advanced age and by healthcare providers involved in their perinatal care.

Trends in Maternal Mortality and Severe Maternal Morbidity During Delivery-Related Hospitalizations in the United States, 2008 to 2021

Importance

Maternal mortality and severe maternal morbidity (SMM) are important focus areas in public health. Further understanding trends, health disparities, and risk factors for these adverse outcomes is vital to public health decision-making.

Objective

To describe trends and risk factors for delivery-related maternal deaths and SMM in the United States.

Design, Setting, and Participants

This is a retrospective cross-sectional study using data from a large, geographically diverse, all-payer hospital administrative database. Hospital discharges from January 2008 to December 2021 with any Medicare Severity Diagnosis Related Group, International Classification of Diseases, Ninth Revision, Clinical Modification, or International Classification of Diseases, Tenth Revision, Clinical Modification delivery diagnosis or procedure code were included. Data analysis took place from February 2021 to March 2023.

Exposures

Year, quarter (Q), age, race and ethnicity, delivery method.

Main Outcomes and Measures

Maternal mortality, SMM during delivery-related hospitalization.

Results

Overall, 11 628 438 unique hospital discharges were analyzed, with a mean (SD) age of 28 (6) years. There were 437 579 (3.8%) Asian, 92 547 (0.8%) American Indian, 1 640 355 (14.1%) Black, 1 762 392 (15.2%) Hispanic, 83 189 (0.7%) Pacific Islander, and 6 194 139 (53.3%) White patients. Regression-adjusted maternal mortality per 100 000 discharges declined from 10.6 deaths in Q1 2008 to 4.6 deaths in Q4 2021. Mortality was significantly higher among patients with advanced maternal age (eg, age 35-44 years vs 25-34 years: adjusted odds ratio [aOR], 1.49; 95% CI, 1.22-1.84). Other significant risk factors for mortality included cesarean delivery, comorbid conditions, complications, and COVID-19 diagnosis (eg, cesarean delivery: aOR, 2.28; 95% CI, 1.87-2.79). The prevalence of any SMM increased from 146.8 per 10 000 discharges in Q1 of 2008 to 179.8 per 10 000 discharges in Q4 of 2021. SMM risk factors included age 24 years or younger or age 35 years or older, belonging to a racial or ethnic minority group, cesarean delivery, Medicaid insurance, and having 1 or more comorbidities (eg, age 10-19 years: aOR, 1.39; 95% CI, 1.36-1.42).

Conclusions and Relevance

This cross-sectional study found that delivery-related mortality in US hospitals decreased for all racial and ethnic groups, age groups, and modes of delivery during 2008 to 2021, likely demonstrating the impact of national strategies focused on improving maternal quality of care provided during delivery-related hospitalizations. SMM prevalence increased for all patients, with higher rates for racial and ethnic minority patients of any age. Advanced maternal age, racial or ethnic minority group status, cesarean delivery, and comorbidities were associated with higher odds of mortality and SMM.

The exciting potential for ChatGPT in obstetrics and gynecology

Natural language processing-the branch of artificial intelligence concerned with the interaction between computers and human language-has advanced markedly in recent years with the introduction of sophisticated deep-learning models. Improved performance in natural language processing tasks, such as text and speech processing, have fueled impressive demonstrations of these models' capabilities. Perhaps no demonstration has been more impactful to date than the introduction of the publicly available online chatbot ChatGPT in November 2022 by OpenAI, which is based on a natural language processing model known as a Generative Pretrained Transformer. Through a series of questions posed by the authors about obstetrics and gynecology to ChatGPT as prompts, we evaluated the model's ability to handle clinical-related queries. Its answers demonstrated that in its current form, ChatGPT can be valuable for users who want preliminary information about virtually any topic in the field. Because its educational role is still being defined, we must recognize its limitations. Although answers were generally eloquent, informed, and lacked a significant degree of mistakes or misinformation, we also observed evidence of its weaknesses. A significant drawback is that the data on which the model has been trained are apparently not readily updated. The specific model that was assessed here, seems to not reliably (if at all) source data from after 2021. Users of ChatGPT who expect data to be more up to date need to be aware of this drawback. An inability to cite sources or to truly understand what the user is asking suggests that it has the capability to mislead. Responsible use of models like ChatGPT will be important for ensuring that they work to help but not harm users seeking information on obstetrics and gynecology.

Hospital characteristics associated with nurse staffing during labor and birth: Inequities for the most vulnerable maternity patients

BACKGROUND

Evidence is limited on nurse staffing in maternity units.

PURPOSE

To estimate the relationship between hospital characteristics and adherence with Association of Women's Health, Obstetric and Neonatal Nurses nurse staffing guidelines.

METHODS

We enrolled 3,471 registered nurses in a cross-sectional survey and obtained hospital characteristics from the 2018 American Hospital Association Annual Survey. We used mixed-effects linear regression models to estimate associations between hospital characteristics and staffing guideline adherence.

FINDINGS

Overall, nurses reported strong adherence to AWHONN staffing guidelines (rated frequently or always met by ≥80% of respondents) in their hospitals. Higher birth volume, having a neonatal intensive care unit, teaching status, and higher percentage of births paid by Medicaid were all associated with lower mean guideline adherence scores.

DISCUSSION AND CONCLUSIONS

Important gaps in staffing were reported more frequently at hospitals serving patients more likely to have medical or obstetric complications, leaving the most vulnerable patients at risk.

Epidemiology and definition of PPH worldwide

Postpartum/peripartum hemorrhage (PPH) is an obstetric emergency complicating 1-10% of all deliveries and is a leading cause of maternal mortality and morbidity worldwide. However, the incidence of PPH differs widely according to the definition and criteria used, the way of measuring postpartum blood loss, and the population being studied with the highest numbers in developing countries. Despite all the significant progress in healthcare, the incidence of PPH is rising due to an incomplete implementation of guidelines, resulting in treatment delays and suboptimal care. A consensus clinical definition of PPH is needed to enable awareness, early recognition, and initiation of appropriate intensive treatment. Unfortunately, the most used definition of PPH based on blood loss ≥500 ml after delivery suffers from inaccuracies in blood loss quantification and is not clinically relevant in most cases, as the amount of blood loss does not fully reflect the severity of bleeding.

Comparison of Natural Language Processing of Clinical Notes With a Validated Risk-Stratification Tool to Predict Severe Maternal Morbidity

IMPORTANCE

Risk-stratification tools are routinely used in obstetrics to assist care teams in assessing and communicating risk associated with delivery. Electronic health record data and machine learning methods may offer a novel opportunity to improve and automate risk assessment.

OBJECTIVE

To compare the predictive performance of natural language processing (NLP) of clinician documentation with that of a previously validated tool to identify individuals at high risk for maternal morbidity.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective diagnostic study was conducted at Brigham and Women's Hospital and Massachusetts General Hospital, Boston, Massachusetts, and included individuals admitted for delivery at the former institution from July 1, 2016, to February 29, 2020. A subset of these encounters (admissions from February to December 2018) was part of a previous prospective validation study of the Obstetric Comorbidity Index (OB-CMI), a comorbidity-weighted score to stratify risk of severe maternal morbidity (SMM).

EXPOSURES

Natural language processing of clinician documentation and OB-CMI scores.

MAIN OUTCOMES AND MEASURES

Natural language processing of clinician-authored admission notes was used to predict SMM in individuals delivering at the same institution but not included in the prospective OB-CMI study. The NLP model was then compared with the OB-CMI in the subset with a known OB-CMI score. Model discrimination between the 2 approaches was compared using the DeLong test. Sensitivity and positive predictive value for the identification of individuals at highest risk were prioritized as the characteristics of interest.

RESULTS

This study included 19 794 individuals; 4034 (20.4%) were included in the original prospective validation study of the OB-CMI (testing set), and the remaining 15 760 (79.6%) composed the training set. Mean (SD) age was 32.3 (5.2) years in the testing cohort and 32.2 (5.2) years in the training cohort. A total of 115 individuals in the testing cohort (2.9%) and 468 in the training cohort (3.0%) experienced SMM. The NLP model was built from a pruned vocabulary of 2783 unique words that occurred within the 15 760 admission notes from individuals in the training set. The area under the receiver operating characteristic curve of the NLP-based model for the prediction of SMM was 0.76 (95% CI, 0.72-0.81) and was comparable with that of the OB-CMI model (0.74; 95% CI, 0.70-0.79) in the testing set (P = .53). Sensitivity (NLP, 28.7%; OB-CMI, 24.4%) and positive predictive value (NLP, 19.4%; OB-CMI, 17.6%) were comparable between the NLP and OB-CMI high-risk designations for the prediction of SMM.

CONCLUSIONS AND RELEVANCE

In this study, the NLP method and a validated risk-stratification tool had a similar ability to identify patients at high risk of SMM. Future prospective research is needed to validate the NLP approach in clinical practice and determine whether it could augment or replace tools requiring manual user input.

Incidence and outcomes of acute high-risk chest pain diseases during pregnancy and puerperium

Aim

To investigate the incidence and outcomes of acute high-risk chest pain diseases, including acute myocardial infarction (AMI), aortic dissection (AD), and pulmonary embolism (PE) during pregnancy and puerperium.

Methods

The National Inpatient Sample was queried to identify pregnancy-related hospitalizations from January 1, 2008 to December 31, 2017. Temporal trends in the incidence and mortality of AMI, AD and PE were extracted.

Results

Among 41,174,101 hospitalizations, acute high-risk chest pain diseases were diagnosed in 40,285 (0.098%). The incidence increased from 79.92/100,000 in 2008 to 114.79/100,000 in 2017 (P_trend < 0.0001). The most frequent was PE (86.5%), followed by AMI (9.6%) and AD (3.3%). The incidence of PE in pregnancy decreased after 2014 and was lower than AMI and AD, while its incidence in puerperium was higher than AMI and AD consistently (P_trend < 0.0001). Subgroup analysis showed the incidence of these diseases was higher in black women, lowest-income households, and elderly parturients (P_trend < 0.0001). The mortality decreased from 2.24% in 2008 to 2.21% in 2017 (P_trend = 0.0240), exhibiting 200-fold higher than patients without these diseases. The following factors were significantly associated with these diseases: aged ≥ 45 years (OR, 4.25; 95%CI, 3.80–4.75), valvular disease (OR, 10.20; 95%CI, 9.73–10.70), and metastatic cancer (OR, 9.75; 95%CI, 7.78–12.22). The trend of elderly parturients increased from 14.94% in 2008 to 17.81% in 2017 (P_trend < 0.0001), while no such up-trend was found in valvular disease and metastatic cancer.

Conclusion

The incidence of acute high-risk chest pain diseases, especially PE in puerperium, increased consistently. Although mortality has shown a downward trend, it is still at a high level. We should strengthen monitoring and management of acute high-risk pain diseases in pregnancy and puerperium, especially for black women, lowest-income households, and elderly parturients in the future.

Trends and Distribution of In-Hospital Mortality Among Pregnant and Postpartum Individuals by Pregnancy Period

This cross-sectional study investigates trends in death rates and proportion of deaths by pregnancy period among pregnant and postpartum individuals from 1994 to 2019.

Natural language processing of admission notes to predict severe maternal morbidity during the delivery encounter

BACKGROUND

Severe maternal morbidity and mortality remain public health priorities in the United States, given their high rates relative to other high-income countries and the notable racial and ethnic disparities that exist. In general, accurate risk stratification methods are needed to help patients, providers, hospitals, and health systems plan for and potentially avert adverse outcomes.

OBJECTIVE

Our objective was to understand if machine learning methods with natural language processing of history and physical notes could identify a group of patients at high risk of maternal morbidity on admission for delivery without relying on any additional patient information (eg, demographics and diagnosis codes).

STUDY DESIGN

This was a retrospective study of people admitted for delivery at 2 hospitals (hospitals A and B) in a single healthcare system between July 1, 2016, and June 30, 2020. The primary outcome was severe maternal morbidity, as defined by the Centers for Disease Control and Prevention; furthermore, we examined nontransfusion severe maternal morbidity. Clinician documents designated as history and physical notes were extracted from the electronic health record for processing and analysis. A bag-of-words approach was used for this natural language processing analysis (ie, each history or physical note was converted into a matrix of counts of individual words (or phrases) that occurred within the document). The least absolute shrinkage and selection operator models were used to generate prediction probabilities for severe maternal morbidity and nontransfusion severe maternal morbidity for each note. Model discrimination was assessed via the area under the receiver operating curve. Discrimination was compared between models using the DeLong test. Calibration plots were generated to assess model calibration. Moreover, the natural language processing models with history and physical note texts were compared with validated obstetrical comorbidity risk scores based on diagnosis codes.

RESULTS

There were 13,572 delivery encounters with history and physical notes from hospital A, split between training (A_train, n=10,250) and testing (A_test, n=3,322) datasets for model derivation and internal validation. There were 23,397 delivery encounters with history and physical notes from hospital B (B_valid) used for external validation. For the outcome of severe maternal morbidity, the natural language processing model had an area under the receiver operating curve of 0.67 (95% confidence interval, 0.63-0.72) and 0.72 (95% confidence interval, 0.70-0.74) in the A_test and B_valid datasets, respectively. For the outcome of nontransfusion severe maternal morbidity, the area under the receiver operating curve was 0.72 (95% confidence interval, 0.65-0.80) and 0.76 (95% confidence interval, 0.73-0.79) in the A_test and B_valid datasets, respectively. The calibration plots demonstrated the bag-of-words model's ability to distinguish a group of individuals at a substantially higher risk of severe maternal morbidity and nontransfusion severe maternal morbidity, notably those in the top deciles of predicted risk. Areas under the receiver operating curve in the natural language processing-based models were similar to those generated using a validated, retrospectively derived, diagnosis code-based comorbidity score.

CONCLUSION

In this practical application of machine learning, we demonstrated the capabilities of natural language processing for the prediction of severe maternal morbidity based on provider documentation inherently generated at the time of admission. This work should serve as a catalyst for providers, hospitals, and electronic health record systems to explore ways that artificial intelligence can be incorporated into clinical practice and evaluated rigorously for their ability to improve health.

Hypertensive Disorders of Pregnancy: Common Clinical Conundrums

Importance

Hypertensive complications of pregnancy comprise 16% of maternal deaths in developed countries and 7.4% of deaths in the United States. Rates of preeclampsia increased 25% from 1987 to 2004, and rates of severe preeclampsia have increased 6.7-fold between 1980 and 2003.

Objective

The aim of this study was to review current and available evidence for common clinical questions regarding the management of hypertensive disorders of pregnancy.

Evidence Acquisition

Original research articles, review articles, and guidelines on hypertension in pregnancy were reviewed.

Results

Severe gestational hypertension should be managed as preeclampsia with severe features. Serum uric acid levels can be useful in predicting development of superimposed preeclampsia for women with chronic hypertension. When presenting with preeclampsia with severe features before 34 weeks, expectant management should be considered only when both maternal and fetal conditions are stable. In the setting of hypertensive disorders of pregnancy, oral antihypertensive medications should be initiated when systolic blood pressure is greater than 160 mm Hg or when diastolic blood pressure is greater than 110 mm Hg, with the most ideal agents being labetalol or nifedipine. Furthermore, although risk of preeclampsia recurrence in future pregnancy is low, women with a history of preeclampsia should be managed with 81 mg aspirin daily for preeclampsia prevention.

Conclusions and Relevance

Despite the frequency with which hypertensive disorders of pregnancy are encountered clinically, situations arise frequently with limited evidence to guide providers in their management. An urgent need exists to better understand this disease to optimize outcomes for impacted patients.

The Index of Concentration at the Extremes (ICE) and Pregnancy-Associated Mortality in Louisiana, 2016-2017

OBJECTIVES

Social and contextual factors underlying the continually disproportionate and burdensome risk of adverse health outcomes experienced by Black women in the US are underexplored in the literature. The aim of this study was to use an index based on area-level population distributions of race and income to predict risk of death during pregnancy and up to 1 year postpartum among women in Louisiana.

METHODS

Using vital records data provided by the Louisiana Department of Health 2016-2017 (n = 125,537), a modified Poisson model was fit with generalized estimating equations to examine the risk of pregnancy-associated death associated with census tract-level values of the Index of Concentration at the Extremes (ICE)-grouped by tertile-while adjusting for both individual and tract-level confounders.

RESULTS

Analyses resulted in an estimated 1.73 (95% CI 1.02-2.93) times increased risk for pregnancy-associated death for those in areas which were characterized by concentrated deprivation (high proportions of Black and low-income residents) relative to those in areas of concentrated privilege (high proportions of white and high-income residents), independent of other factors.

CONCLUSIONS FOR PRACTICE

In addition to continuing to consider the deeply entrenched racism and economic inequality that shape the experience of pregnancy-associated death, we must also consider their synergistic effect on access to resources, maternal population health, and health inequities.

Estimating the Risk of Maternal Death at Admission: A Predictive Model from a 5-Year Case Reference Study in Northern Uganda

Background. Uganda is one of the countries in the Sub-Saharan Africa with a very high maternal mortality ratio estimated at 336 deaths per 100,000 live births. We aimed at exploring the main factors affecting maternal death and designing a predictive model for estimation of the risk of dying at admission at a major referral hospital in northern Uganda. Methods. This was a retrospective matched case-control study, carried out at Lacor Hospital in northern Uganda, including 130 cases and 336 controls, from January 2015 to December 2019. Multivariate logistic regression was used to estimate the net effect of the associated factors. A cumulative risk score for each woman based on the unstandardised canonical coefficients was obtained by the discriminant equation. Results. The average maternal mortality ratio was 328 per 100,000 live births. Direct obstetric causes contributed to 73.8% of maternal deaths; the most common were haemorrhage (42.7%), sepsis (24.0%), hypertensive disorders (18.7%) and complications of abortion (2.1%), whereas malaria (23.5%) and HIV/AIDS (20.6%) were the leading indirect causes. The odds of dying were higher among women who were aged 30 years or more (OR 1.12; 95% CI, 1.04–1.19), did not attend antenatal care (OR 3.11; 95% CI, 1.36–7.09), were HIV positive (OR 3.13; 95% CI, 1.41–6.95), had a caesarean delivery (OR 2.22; 95% CI 1.13–4.37), and were referred from other facilities (OR 5.57; 95% CI 2.83–10.99). Conclusion. Mortality is high among mothers referred late from other facilities who are HIV positive, aged more than 30 years, lack antenatal care attendance, and are delivered by caesarean section. This calls for prompt and better assessment of referred mothers and specific attention to antibiotic therapy before and after caesarean section, especially among HIV-positive women.

Multimodality Multisystem Imaging of Pregnancy-Related Changes: Featuring Neurologic, Cardiothoracic, Breast, Gynecologic, and Musculoskeletal Issues

ABSTRACT

Pregnancy and the puerperium are a time of significant physiologic change, and with an average of 4 million births in the United States yearly, radiologists encounter pregnancy-related imaging findings regularly. While many of these findings represent physiologic changes, a significant number represent pathology, making it paramount for radiologists to distinguish between the two. This case-based article reviews imaging findings within the nervous, cardiovascular, pulmonary, breast, gynecologic, musculoskeletal, digestive, hematologic, and integumentary systems throughout pregnancy and the postpartum period.

Longitudinal blood pressure patterns of women with hypertensive disorders of pregnancy: preconception through postpartum

OBJECTIVE

To investigate the longitudinal blood pressure (BP) pattern of women with hypertensive disorders of pregnancy (HDP) preconception through the postpartum day (PPD) 42.

STUDY DESIGN

A retrospective study of women (≥15 years old) diagnosed with an HDP antenatally or postpartum, who were enrolled prospectively in a postpartum remote BP monitoring program between 3/2017 and 5/2020. BPs were collected from 47-time points: preconception, each trimester, delivery day, and 42 days postpartum. Analysis was conducted utilizing a mixed-effects longitudinal model.

MAIN OUTCOME MEASURES

Primary outcome was the longitudinal BP patterns. Secondary outcomes were the timing of BP stabilization (BPs < 140/90 mmHg for ≥48 h) and resolution (stabilized without antihypertensive medication use).

RESULTS

Our final analysis included 897 of the 964 eligible women. The peak systolic and diastolic BPs were on PPDs 3, 4, 5, and 5, 6, 7, respectively. Systolic BP fell below the preconception level after PPD15; diastolic BP reached its plateau after PPD17 and remained above the preconception level till PPD42 (p < .001). Postpartum BP peaked with the highest percentage of BP spikes on PPDs 4-7. The median survival times to BP stabilization and resolution were PPDs 11 (95% CI: 10-12) and 23 (95% CI: 21-25), respectively. By PPD42, 91.0% and 74.1% of women achieved BP stabilization and resolution, respectively.

CONCLUSION

This study data could be used to develop evidence-based recommendations for women with an HDP. Diastolic BPs remaining significantly higher than the preconception level indicates the long-term risk of cardiovascular disease. In our cohort, 26% of women had unresolved hypertension by PPD42, which reinforces the necessity to ensure long-term follow-up.

Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model

Aims

Cardiovascular disease is a major threat to maternal health, with cardiomyopathy being among the most common acquired cardiovascular diseases during pregnancy and the postpartum period. The aim of our study was to evaluate the effectiveness of an electrocardiogram (ECG)-based deep learning model in identifying cardiomyopathy during pregnancy and the postpartum period.

Methods and results

We used an ECG-based deep learning model to detect cardiomyopathy in a cohort of women who were pregnant or in the postpartum period seen at Mayo Clinic. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. We compared the diagnostic probabilities of the deep learning model with natriuretic peptides and a multivariable model consisting of demographic and clinical parameters. The study cohort included 1807 women; 7%, 10%, and 13% had left ventricular ejection fraction (LVEF) of 35% or less, <45%, and <50%, respectively. The ECG-based deep learning model identified cardiomyopathy with AUCs of 0.92 (LVEF ≤ 35%), 0.89 (LVEF < 45%), and 0.87 (LVEF < 50%). For LVEF of 35% or less, AUC was higher in Black (0.95) and Hispanic (0.98) women compared to White (0.91). Natriuretic peptides and the multivariable model had AUCs of 0.85 to 0.86 and 0.72, respectively.

Conclusions

An ECG-based deep learning model effectively identifies cardiomyopathy during pregnancy and the postpartum period and outperforms natriuretic peptides and traditional clinical parameters with the potential to become a powerful initial screening tool for cardiomyopathy in the obstetric care setting.

Placenta-Derived Exosomes as a Modulator in Maternal Immune Tolerance During Pregnancy

Exosomes are a subset of extracellular vesicles with an average diameter of ~100nm. Exosomes are released by all cells through an endosome-dependent pathway and carry nucleic acids, proteins, lipids, cytokines and metabolites, mirroring the state of the originating cells. The function of exosomes has been implicated in various reproduction processes, such as embryo development, implantation, decidualization and placentation. Placenta-derived exosomes (pEXO) can be detected in the maternal blood as early as 6 weeks after conception and their levels increase with gestational age. Importantly, alternations in the molecular signatures of pEXO are observed in pregnancy-related complications. Thus, these differentially expressed molecules could be the potential biomarkers for diagnosis of the pregnancy-associated diseases. Recent studies have demonstrated that pEXO play a key role in the establishment of maternal immune tolerance, which is critical for a successful pregnancy. To gain a better understanding of the underlying mechanism, we highlighted the advanced studies of pEXO on immune cells in pregnancy.

Patient race and racial composition of delivery unit associated with disparities in severe maternal morbidity: a multistate analysis 2007-2014

BACKGROUND

High Black-serving delivery units and high hospital safety-net burden have been associated with poorer patient outcomes. We examine these hospital-level factors and their association with severe maternal morbidity (SMM), independently and as effect modifiers of patient-level factors.

METHODS

Using the 2007-2014 State Inpatient Databases (Florida, New York, California, Maryland, Kentucky), we analyzed delivery hospitalizations. We constructed generalized linear mixed models with patient- and hospital-level variables (Black-serving delivery units: high: top 5th percentile; medium: 5th-25th percentile; low: bottom 75th percentile; hospital safety-net burden status defined by insurance status) and report adjusted odds ratios (aOR) and 99% confidence intervals (CI). We repeated our mixed models with stratification and interaction analysis.

RESULTS

6 879 332 delivery hospitalizations were included in the analysis. Deliveries at high (aOR 1.83; 99% CI 1.34 to2.50) or medium (aOR 1.27; 99% CI 1.10 to 1.46) Black-serving delivery units were more likely to have SMM than deliveries at low Black-serving delivery units. Hospital safety-net burden was not significantly associated with SMM. In stratified models by hospital category, deliveries of Black women were associated with an increase in SMM compared with deliveries of White women in all hospital categories. In interaction models, Black women giving birth in high Black-serving delivery units had more than twice the odds of White women in low Black-serving delivery units of experiencing SMM (aOR 2.42; 99% CI 1.90 to 3.08).

CONCLUSION

The patient racial/ethnic composition of the delivery unit is associated with adjusted-odds of SMM, both independently and interactively with individual patient race.

Heart disease in women: a narrative review

Cardiovascular disease is the worldwide leading cause of death in women. Biological differences between the sexes, a result of genetic, epigenetic and sex hormone-mediated factors, are complex and incompletely understood. These differences are compounded by socio-cultural factors and together account for the variation in the prevalence, presentation and natural history of cardiovascular disease between men and women. Although there is growing recognition of sex-specific determinants of outcomes, women remain under-represented in clinical trials, and sex-disaggregated diagnostic and management strategies are not currently recommended in clinical guidelines. Women remain more likely to experience delays in diagnosis, to be treated less aggressively and to have worse outcomes. As a consequence, cardiovascular disease in women remains understudied, underdiagnosed and undertreated. This review will focus on female-specific characteristics of cardiovascular disease and how these may impact on anaesthetic and peri-operative risk assessment and care. We highlight significant differences between the sexes in the natural history of cardiovascular disease, including those disease entities that are more common in women, such as sudden coronary artery dissection or microvascular dysfunction. Given the rapidly rising incidence of maternal cardiovascular disease and associated complications, special consideration is given to the risk assessment and management of these conditions during pregnancy. Increased awareness of these issues has the potential to improve the effectiveness of the multidisciplinary heart team and ultimately improve the care provided to women.

Association of Adverse Neighborhood Exposures With HIV Viral Load in Pregnant Women at Delivery

IMPORTANCE

Racial disparities in maternal morbidity and mortality are in large part driven by poor control of chronic diseases. The association between adverse neighborhood exposures and HIV virologic control has not been well described for women with HIV during pregnancy.

OBJECTIVE

To evaluate the association between adverse neighborhood exposures and HIV viral load at delivery.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cohort study assessed HIV surveillance data for pregnant women with HIV who had live deliveries in Philadelphia from January 1, 2005, through December 31, 2015. Data analyses were completed in August 2020.

EXPOSURES

Neighborhood exposures included extreme poverty, educational attainment, crime rates (using separate and composite measures), and social capital categorized above or below the median. Each neighborhood exposure was modeled separately to estimate its association with elevated HIV viral load.

MAIN OUTCOMES AND MEASURES

The main outcome was elevated HIV viral load of ≥200 copies/mL at delivery. We hypothesized that adverse neighborhood exposures would be associated with higher odds of having an elevated viral load at delivery. Confounders included birth year, age, race/ethnicity, previous birth while living with HIV, and prenatal HIV diagnosis. Prenatal care and substance use were considered potential mediators. We used logistic mixed effects models to estimate the association between neighborhood exposures and elevated viral load, adjusting for confounders in Model 1 and confounders and mediators in Model 2.

RESULTS

There were 905 births among 684 women with HIV, most of whom were aged 25 to 34 years (n = 463 [51.2%]) and were Black non-Hispanic (n = 743 [82.1%]). The proportion of women with elevated viral load decreased from 58.2% between 2005 and 2009 to 23.1% between 2010 and 2015. After adjusting for confounders in Model 1, higher neighborhood education was associated with lower odds of having an elevated viral load (adjusted odds ratio [AOR], 0.70; 95% CI, 0.50-0.96). More violent crime (AOR, 1.51; 95% CI, 1.10-2.07), prostitution crime (AOR, 1.46; 95% CI, 1.06-2.00), and a composite measure of crime (AOR, 1.44; 95% CI, 1.05-1.98) were positively associated with having a higher HIV viral load. These associations remained after adjusting for mediators in Model 2. In addition, the AOR for intermediate prenatal care varied between 1.93 (95% CI, 1.28-2.91) and 1.97 (95% CI, 1.31-2.96), whereas the AOR for inadequate prenatal care varied between 3.01 (95% CI, 2.05-4.43) and 3.06 (95% CI, 2.08-4.49) across regression models.

CONCLUSIONS AND RELEVANCE

In this cohort study, adverse neighborhood exposures during pregnancy and poor engagement in prenatal care were associated with poor virologic control at delivery. These findings suggest that interventions targeted at improving maternal health need to take the social environment into consideration.

Pregnancy and Congenital Heart Disease: A Brief Review of Risk Assessment and Management

Cardiac disease is a leading cause of morbidity and mortality in pregnant women. An increased prevalence of the cardiovascular disease has been found in women of childbearing age, in which the responsibility of the treating physician extends to the mother and to the unborn fetus. As a result, care of these high-risk pregnant women with cardiovascular disease including those with congenital heart disease (CHD) require a team approach including specialists in maternal-fetal medicine, adult congenital cardiology, and obstetrical anesthesia. The human body undergoes significant amounts of physiological changes during this period of time and the underlying cardiac disease can affect both the mother and the fetus. Today, most female children born with CHD will reach childbearing age. For many women with complex CHD, carrying a pregnancy has a moderate to high risk for both the mother and her fetus. This chapter will review the epidemiology, risk factors, clinical presentation including common signs and symptoms, physiological changes in pregnancy, and the medical approach including cardiac medications, percutaneous interventions, and surgical procedures for pregnant women with CHD.

Expected Surge in Maternal Mortality and Severe Morbidity among African-Americans in the Era of COVID-19 Pandemic

Prior to the COVID-19 pandemic, African-American mothers were three times as likely to die from pregnancy-related causes compared to white mothers. The impact of the pandemic among African-Americans could further worsen the racial disparities in maternal mortality (MM) and severe maternal morbidity (SMM). This study aimed to create a theoretical framework delineating the contributors to an expected rise in maternal mortality (MM) and severe maternal morbidity (SMM) among African-Americans in the era of the COVID-19 pandemic due to preliminary studies suggesting heightened vulnerability of African-Americans to the virus as well as its adverse health effects. Rapid searches were conducted in PubMed and Google to identify published articles on the health determinants of MM and SMM that have been or likely to be disproportionately affected by the pandemic in African-Americans. We identified socioeconomic and health trends determinants that may contribute to future adverse maternal health outcomes. There is a need to intensify advocacy, implement culturally acceptable programs, and formulate policies to address social determinants of health.