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Objective: To estimate the prevalence of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) after infection with SARS-CoV-2 during pregnancy and to characterize associated risk factors., Methods: In a multicenter cohort study (NIH RECOVER [Researching COVID to Enhance Recovery]-Pregnancy Cohort), individuals who were pregnant during their first SARS-CoV-2 infection were enrolled across the United States from December 2021 to September 2023, either within 30 days of their infection or at differential time points thereafter. The primary outcome was PASC , defined as score of 12 or higher based on symptoms and severity as previously published by the NIH RECOVER-Adult Cohort, at the first study visit at least 6 months after the participant's first SARS-CoV-2 infection. Risk factors for PASC were evaluated, including sociodemographic characteristics, clinical characteristics before SARS-CoV-2 infection (baseline comorbidities, trimester of infection, vaccination status), and acute infection severity (classified by need for oxygen therapy). Multivariable logistic regression models were fitted to estimate associations between these characteristics and presence of PASC., Results: Of the 1,502 participants, 61.1% had their first SARS-CoV-2 infection on or after December 1, 2021 (ie, during Omicron variant dominance); 51.4% were fully vaccinated before infection; and 182 (12.1%) were enrolled within 30 days of their acute infection. The prevalence of PASC was 9.3% (95% CI, 7.9-10.9%) measured at a median of 10.3 months (interquartile range 6.1-21.5) after first infection. The most common symptoms among individuals with PASC were postexertional malaise (77.7%), fatigue (76.3%), and gastrointestinal symptoms (61.2%). In a multivariable model, the proportion PASC positive with vs without history of obesity (14.9% vs 7.5%, adjusted odds ratio [aOR] 1.65, 95% CI, 1.12-2.43), depression or anxiety disorder (14.4% vs 6.1%, aOR 2.64, 95% CI, 1.79-3.88) before first infection, economic hardship (self-reported difficulty covering expenses) (12.5% vs 6.9%, aOR 1.57, 95% CI, 1.05-2.34), and treatment with oxygen during acute SARS-CoV-2 infection (18.1% vs 8.7%, aOR 1.86, 95% CI, 1.00-3.44) were associated with increased prevalence of PASC., Conclusion: The prevalence of PASC at a median time of 10.3 months after SARS-CoV-2 infection during pregnancy was 9.3% in the NIH RECOVER-Pregnancy Cohort. The predominant symptoms were postexertional malaise, fatigue, and gastrointestinal symptoms. Several socioeconomic and clinical characteristics were associated with PASC after infection during pregnancy., Clinical Trial Registration: ClinicalTrials.gov , NCT05172024., Competing Interests: Financial Disclosure Torri D. Metz is the site PI for a Pfizer study of Paxlovid in pregnancy and was the site PI for a Pfizer study of COVID-19 vaccination in pregnancy. She has received UpToDate royalties for two topics on trial of labor after cesarean. Carmen J. Beamon disclosed receiving payments from Wellcare of North Carolina. Ann Chang's institution received payment from New York University for her efforts on this study. Kelly S. Gibson disclosed that her institution received funding from the NICHD, NHLBI, and Materna. Rachel Hess received payment from Astellas Pharmaceuticals. M. Camile Hoffman disclosed her institution received payment for her expert testimony for one medicolegal trial from Wheeler, Trigg, and Associates (a defense attorneys firm). Her institution also received payment for a disease state presentation on postpartum depression and zuranolone from SAGE/Biogen. Brenna L. Hughes disclosed receiving payments from UpToDate and Moderna. Stuart Katz disclosed payments for providing expert testimony for Venable LLP. Jennifer Hadlock has received funding (paid to institution) for retrospective studies of COVID-19 from Pfizer, Novartis, Janssen, and Gilead. Grace A. McComsey served as an advisor for Gilead and ViiVGlaxoSmithKline. Patrick Ramsey disclosed receiving royalties from UpToDate. His institution was paid by the Texas Collaborative for Healthy Mothers and Babies (TCHMB)—Texas PQC for part of his efforts. Daniel W. Skupski reports receiving payments from Organon, Inc and Cooper Surgical. Alan T.N. Tita disclosed money paid to his institution from Pfizer for his efforts in this study. Andrea Foulkes disclosed receiving past payments from Round Table, Inc. The other authors did not report any potential conflicts of interest., (Copyright © 2024 by the American College of Obstetricians and Gynecologists. Published by Wolters Kluwer Health, Inc. All rights reserved.)

Objective: Prediction of blood transfusion during delivery admission allows for clinical preparedness and risk mitigation. Although prediction models have been developed and adopted into practice, their external validation is limited. We aimed to evaluate the performance of three blood transfusion prediction models in a U.S. cohort of individuals undergoing cesarean delivery., Study Design: This was a secondary analysis of a multicenter randomized trial of tranexamic acid for prevention of hemorrhage at time of cesarean delivery. Three models were considered: a categorical risk tool (California Maternal Quality Care Collaborative [CMQCC]) and two regression models (Ahmadzia et al and Albright et al). The primary outcome was intrapartum or postpartum red blood cell transfusion. The CMQCC algorithm was applied to the cohort with frequency of risk category (low, medium, high) and associated transfusion rates reported. For the regression models, the area under the receiver-operating curve (AUC) was calculated and a calibration curve plotted to evaluate each model's capacity to predict receipt of transfusion. The regression model outputs were statistically compared., Results: Of 10,785 analyzed individuals, 3.9% received a red blood cell transfusion during delivery admission. The CMQCC risk tool categorized 1,970 (18.3%) individuals as low risk, 5,259 (48.8%) as medium risk, and 3,556 (33.0%) as high risk with corresponding transfusion rates of 2.1% (95% confidence interval [CI]: 1.5-2.9%), 2.2% (95% CI: 1.8-2.6%), and 7.5% (95% CI: 6.6-8.4%), respectively. The AUC for prediction of blood transfusion using the Ahmadzia and Albright models was 0.78 (95% CI: 0.76-0.81) and 0.79 (95% CI: 0.77-0.82), respectively ( p  = 0.38 for difference). Calibration curves demonstrated overall agreement between the predicted probability and observed likelihood of blood transfusion., Conclusion: Three models were externally validated for prediction of blood transfusion during cesarean delivery admission in this U.S., Cohort: Overall, performance was moderate; model selection should be based on ease of application until a specific model with superior predictive ability is developed., Key Points: · A total of 3.9% of individuals received a blood transfusion during cesarean delivery admission.. · Three models used in clinical practice are externally valid for blood transfusion prediction.. · Institutional model selection should be based on ease of application until further research identifies the optimal approach.., Competing Interests: None declared., (Thieme. All rights reserved.)

Despite advances in hemorrhage detection and management, postpartum hemorrhage remains the single leading cause of maternal death worldwide. Within the United States, hemorrhage is the leading cause of maternal death on the day of delivery and within the first week after delivery. Blood transfusion after hemorrhage represents a large proportion of severe maternal morbidity during and after delivery. Blood loss during delivery has historically been assessed visually by inspecting soiled pads, linens, and laparotomy sponges. These methods underestimate the volume of blood loss by as much as 40%, becoming increasingly inaccurate as blood loss increases. Young, healthy obstetrical patients compensate for blood loss via peripheral vasoconstriction, maintaining heart rate and blood pressure in a normal range until over 1 L of blood has been lost. A significant decrease in blood pressure along with marked tachycardia (>120 bpm) may not be seen until 30% to 40% of blood volume has been lost, or 2.0 to 2.6 L in a healthy term pregnant patient, after which the patient may rapidly decompensate. In resource-poor settings especially, the narrow window between the emergence of significant vital sign abnormalities and clinical decompensation may prove catastrophic. Once hemorrhage is detected, decisions regarding blood product transfusion are routinely made on the basis of inaccurate estimates of blood loss, placing patients at risk of underresuscitation (increasing the risk of hemorrhagic shock and end-organ damage) or overresuscitation (increasing the risk of transfusion reaction, fluid overload, and alloimmunization). We will review novel technologies that have emerged to assist both in the early and accurate detection of postpartum hemorrhage and in decisions regarding blood product transfusion., (Published by Elsevier Inc.)

Maternal mortality has increased in the last decades in the United States as a result of increased prevalence of coexisting medical diseases such as hypertension, diabetes, and both acquired and congenital heart diseases. Obstetricians and maternal-fetal medicine physicians should have the basic medical knowledge to initiate appropriate diagnostic and early therapeutic interventions since they may be the only provider available at the time of presentation. The goal of this article is not to extensively discuss the management of complex medical diseases during pregnancy, rather we provide a concise review of key early medical interventions that will likely result in improved clinical outcomes. KEY POINTS: · Obstetricians and maternal-fetal medicine physicians must be familiar with initial basic management of common medical emergencies.. · Management of these complex cases is ideally multidisciplinary.. · Residency/fellowship programs should include common disease management to improve maternal outcomes.., Competing Interests: None declared., (Thieme. All rights reserved.)

An increase in the prevalence of obesity, hypertension, diabetes, and abnormal placentation, among others, has fueled the recent rise in maternal mortality, "near misses" and severe morbidity. In 1976, the March of Dimes published a report, "Toward Improving the Outcome of Pregnancy," which included recommendations for levels of perinatal care. Although the original intent was to address the needs of both mother and neonate, implementation in the ensuing years focused mostly on the latter. Currently, there are no well-defined nationally accepted levels of maternal care similar to those adopted by the American Academy of Pediatrics for neonatal intensive care units. When discussing regionalization of perinatal care, the needs of the mother are frequently overlooked. We propose that it is time to address this deficiency and develop levels of care that are specific to the mother. We expect that improving maternal care will also improve neonatal outcome. We call on various organizations and agencies to establish national standards and levels of maternity care much as our colleagues in neonatology have already successfully done. We canvassed the available publications by states and other countries and found a number of noteworthy examples. We propose that the goal would be an integrated maternal-fetal-neonatal care network, a model similar to what is done in stroke or emergency care. In addition to accepting transfers, the central facility functioning at the highest level would also be responsible for education, evidence-based best practices, policy development, and quality review and improvement within the network.