Helen M Ryan1, Meghan A Jones2, Beth A Payne2, Sumedha Sharma2, Anna M Hutfield2, Tang Lee2, U Vivian Ukah2, Keith R Walley3, Laura A Magee4, Peter von Dadelszen5. 1. Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC; Department of Family Practice, University of British Columbia, Vancouver, BC; Child and Family Research Institute, University of British Columbia, Vancouver, BC. 2. Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC; Child and Family Research Institute, University of British Columbia, Vancouver, BC. 3. Department of Medicine, University of British Columbia, Vancouver, BC; Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, BC. 4. Institute of Cardiovascular and Cell Sciences, St. George's, University of London, London, UK; Department of Obstetrics and Gynaecology, St. George's University Hospitals NHS Foundation Trust, London, UK. 5. Institute of Cardiovascular and Cell Sciences, St. George's, University of London, London, UK; Department of Obstetrics and Gynaecology, St. George's University Hospitals NHS Foundation Trust, London, UK. Electronic address: pvd@sgul.ac.uk.
Abstract
OBJECTIVES: To evaluate the performance of the Modified Early Obstetric Warning System (MEOWS) to predict maternal ICU admission in an obstetric population. DESIGN: Case-control study. SETTING: Two maternity units in Vancouver, Canada, one with ICU facilities, between January 1, 2000, and December 31, 2011. PATIENTS: Pregnant or recently delivered (≤6 weeks) women admitted to the hospital for >24 hours. Three control patients were randomly selected per case and matched for year of admission. MEASUREMENTS AND MAIN RESULTS: Retrospective, observational, case-control validation study investigating the physiologic predictors of admission in the 24-hour period preceding either ICU admission >24 hours (cases) or following admission (control patients). Model performance was assessed based on sensitivity, specificity, and predictive values. Forty-six women were admitted to the ICU for >24 hours (0.51/1000 deliveries); the study included 138 randomly selected control patients. There were no maternal deaths in the cohort. MEOWS had high sensitivity (0.96) but low specificity (0.54) for ICU admission >24 hours, whereas ≥1 one red trigger maintained sensitivity (0.96) and improved specificity (0.73). CONCLUSION: Altering MEOWS trigger parameters may improve the accuracy of MEOWS in predicting ICU admission. Formal modelling of a MEOWS scoring system is required to support evidence-based care.
OBJECTIVES: To evaluate the performance of the Modified Early Obstetric Warning System (MEOWS) to predict maternal ICU admission in an obstetric population. DESIGN: Case-control study. SETTING: Two maternity units in Vancouver, Canada, one with ICU facilities, between January 1, 2000, and December 31, 2011. PATIENTS: Pregnant or recently delivered (≤6 weeks) women admitted to the hospital for >24 hours. Three control patients were randomly selected per case and matched for year of admission. MEASUREMENTS AND MAIN RESULTS: Retrospective, observational, case-control validation study investigating the physiologic predictors of admission in the 24-hour period preceding either ICU admission >24 hours (cases) or following admission (control patients). Model performance was assessed based on sensitivity, specificity, and predictive values. Forty-six women were admitted to the ICU for >24 hours (0.51/1000 deliveries); the study included 138 randomly selected control patients. There were no maternal deaths in the cohort. MEOWS had high sensitivity (0.96) but low specificity (0.54) for ICU admission >24 hours, whereas ≥1 one red trigger maintained sensitivity (0.96) and improved specificity (0.73). CONCLUSION: Altering MEOWS trigger parameters may improve the accuracy of MEOWS in predicting ICU admission. Formal modelling of a MEOWS scoring system is required to support evidence-based care.
Authors: Nicola Vousden; Elodie Lawley; Hannah L Nathan; Paul T Seed; Muchabayiwa Francis Gidiri; Shivaprasad Goudar; Jane Sandall; Lucy C Chappell; Andrew H Shennan Journal: Lancet Glob Health Date: 2019-03 Impact factor: 26.763
Authors: Amam C Mbakwem; Johann Bauersachs; Charle Viljoen; Julian Hoevelmann; Peter van der Meer; Mark C Petrie; Alexandre Mebazaa; Sorel Goland; Kamilu Karaye; Cécile Laroche; Karen Sliwa Journal: ESC Heart Fail Date: 2021-01-16
Authors: Beth A Payne; Helen Ryan; Jeffrey Bone; Laura A Magee; Alice B Aarvold; J Mark Ansermino; Zulfiqar A Bhutta; Mary Bowen; J Guilherme Cecatti; Cynthia Chazotte; Tim Crozier; Anne-Cornélie J M de Pont; Oktay Demirkiran; Tao Duan; Marlot Kallen; Wessel Ganzevoort; Michael Geary; Dena Goffman; Jennifer A Hutcheon; K S Joseph; Stephen E Lapinsky; Isam Lataifeh; Jing Li; Sarka Liskonova; Emily M Hamel; Fionnuala M McAuliffe; Colm O'Herlihy; Ben W J Mol; P Gareth R Seaward; Ramzy Tadros; Turkan Togal; Rahat Qureshi; U Vivian Ukah; Daniela Vasquez; Euan Wallace; Paul Yong; Vivian Zhou; Keith R Walley; Peter von Dadelszen Journal: Crit Care Date: 2018-10-30 Impact factor: 9.097