1. Early warning systems for identifying severe maternal outcomes: findings from the WHO global maternal sepsis studyResearch in context
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Yamikani Chimwaza, Alexandra Hunt, Livia Oliveira-Ciabati, Laura Bonnett, Edgardo Abalos, Cristina Cuesta, João Paulo Souza, Mercedes Bonet, Vanessa Brizuela, David Lissauer, Mohammad Iqbal Aman, Bashir Noormal, Marisa Espinoza, Julia Pasquale, Charlotte Leroy, Kristien Roelens, Griet Vandenberghe, M. Christian Urlyss Agossou, Sourou Goufodji Keke, Christiane Tshabu Aguemon, Patricia Soledad Apaza Peralta, Víctor Conde Altamirano, Rosalinda Hernández Muñoz, José Guilherme Cecatti, Carolina Ribeiro do Valle, Vincent Batiene, Kadari Cisse, Henri Gautier Ouedraogo, Kannitha Cheang, Phirun Lam, Tung Rathavy, Elie Simo, Pierre-Marie Tebeu, Emah Irene Yakana, Javier Carvajal, María Fernanda Escobar, Paula Fernández, Lotte Berdiin Colmorn, Jens Langhoff-Roos, Wilson Mereci, Paola Vélez, Yasser Salah Eldin, Alaa Sultan, Alula M. Teklu, Dawit Worku, Richard Adanu, Philip Govule, Charles Noora Lwanga, William Enrique Arriaga Romero, María Guadalupe Flores Aceituno, Carolina Bustillo, Bredy Lara, Vijay Kumar, Vanita Suri, Sonia Trikha, Irene Cetin, Serena Donati, Carlo Personeni, Guldana Baimussanova, Saule Kabylova, Balgyn Sagyndykova, George Gwako, Alfred Osoti, Zahida Qureshi, Raisa Asylbasheva, Aigul Boobekova, Damira Seksenbaeva, Saad Eddine Itani, Meilė Minkauskienė, Diana Ramašauskaitė, Owen Chikhwaza, Luis Gadama, Eddie Malunga, Haoua Dembele, Hamadoun Sangho, Fanta Eliane Zerbo, Filiberto Dávila Serapio, Nazarea Herrera Maldonado, Juan I. Islas Castañeda, Tatiana Cauaus, Ala Curteanu, Victor Petrov, Yadamsuren Buyanjargal, Seded Khishgee, Bat-Erdene Lkhagvasuren, Amina Essolbi, Rachid Moulki, Zara Jaze, Arlete Mariano, Nafissa Bique Osman, Hla Mya Thway Einda, Thae Maung Maung, Khaing Nwe Tin, Tara Gurung, Amir Babu Shrestha, Sangeeta Shrestha, Kitty Bloemenkamp, Marcus J. Rijken, Thomas Van Den Akker, María Esther Estrada, Néstor J. Pavón Gómez, Olubukola Adesina, Chris Aimakhu, Bukola Fawole, Rizwana Chaudhri, Saima Hamid, M. Adnan Khan, María del Pilar Huatuco Hernández, Nelly M. Zavaleta Pimentel, Maria Lu Andal, Zenaida Dy Recidoro, Carolina Paula Martin, Mihaela Budianu, Lucian Pușcașiu, Léopold Diouf, Dembo Guirassy, Philippe Marc Moreira, Miroslav Borovsky, Ladislav Kovac, Alexandra Kristufkova, Sylvia Cebekhulu, Laura Cornelissen, Priya Soma-Pillay, Vicenç Cararach, Marta López, María José Vidal Benedé, Hemali Jayakody, Kapila Jayaratne, Dhammica Rowel, Wisal Nabag, Sara Omer, Victoria Tsoy, Urunbish Uzakova, Dilrabo Yunusova, Thitiporn Siriwachirachai, Thumwadee Tangsiriwatthana, Catherine Dunlop, Marian Knight, Jhon Roman, Gerardo Vitureira, Dinh Anh Tuan, Luong Ngoc Truong, Nghiem Thi Xuan Hanh, Mugove Madziyire, Thulani Magwali, Stephen Munjanja, Adama Baguiya, Mónica Chamillard, Seni Kouanda, Pisake Lumbiganon, Ashraf Nabhan, Ruta Nadisauskiene, Linda Bartlett, Fernando Bellissimo-Rodrigues, Shevin T. Jacob, Sadia Shakoor, Khalid Yunis, Liana Campodónico, Hugo Gamerro, Daniel Giordano, Fernando Althabe, and A. Metin Gülmezoglu
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Early warning systems ,Sepsis ,Maternal sepsis ,Early identification ,Severe maternal outcome ,Medicine (General) ,R5-920 - Abstract
Summary: Background: Infections and sepsis are leading causes of morbidity and mortality in women during pregnancy and the post-pregnancy period. Using data from the 2017 WHO Global Maternal Sepsis Study, we explored the use of early warning systems (EWS) in women at risk of sepsis-related severe maternal outcomes. Methods: On April 27, 2023, we searched the literature for EWS in clinical use or research in obstetric populations. We calculated the proportion of women for whom each existing EWS identified them as at risk for developing severe maternal outcomes by infection severity (complications and severe maternal outcomes). Sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratios, and J statistics were calculated to assess EWS performance. Machine learning was used to test the diagnostic potential of routine maternal sepsis markers. Findings: 21 EWS were assessed in 2560 women from 46 countries with suspected or confirmed infections. The NICE Risk Stratification tool, Modified Shock Index, maternity Systemic Inflammatory Response Syndrome, and Early Maternal Infection Prompts scores had high sensitivity (88.1–97.5%) for identifying sepsis-related severe maternal outcomes. The quick Sequential Organ Failure Assessment (SOFA) in Pregnancy score and Obstetrically modified SOFA had high specificity (90.4–100%) for identifying women with sepsis-related severe maternal outcomes. Furthermore, combinations of sepsis markers had very low sensitivity and high specificity using machine learning. Interpretation: No score demonstrated enough diagnostic accuracy to be used alone to identify sepsis. However, obstetric—and sepsis-specific EWS performed better for early identification of maternal sepsis than non-obstetric and non-sepsis-specific scoring systems. There are limitations to applying EWS to real-world data, mainly due to the incompleteness of medical data that hinders EWS effectiveness. There is a need to continue developing and testing criteria for early identification of maternal sepsis. Funding: UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), WHO, Merck for Mothers, U.S. Agency for International Development, Wellcome Trust, and National Institute for Health and Care Research.
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- 2025
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