4.6 Article

Prognostic Value of an Estimate-of-Risk Model in Critically Ill Obstetric Patients in Brazil

Journal

OBSTETRICS AND GYNECOLOGY
Volume 139, Issue 1, Pages 83-90

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/AOG.0000000000004619

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The study externally validated the CIPHER model for predicting mortality and interventions in critically ill obstetric patients, finding poor performance in the Brazilian population and suggesting the need for different predictors for patients in low- and middle-income countries receiving care in public hospitals.
OBJECTIVE: To externally validate the CIPHER (Collaborative Integrated Pregnancy High-Dependency Estimate of Risk) prognostic model for pregnant and postpartum women admitted to the intensive care unit. METHODS: A retrospective and a prospective validation study were conducted at two reference centers in Brazil. A composite outcome was defined as maternal death or need for prolonged organ support (more than 7 days) or acute lifesaving intervention. To evaluate the performance of the CIPHER model, a receiver operating characteristic curve was used and score calibration was assessed by the Hosmer-Lemeshow test. We conducted a descriptive analysis comparing the results of the current study with the results of the model development study. RESULTS: A total of 590 women were included. The composite outcome was observed in 90 (15.2%) women. Of these, 13 (2.2%) were maternal deaths and 77 (13%) required one or more component of organ support or lifesaving intervention. The CIPHER model's area under the curve (AOC) did not show significant predictive ability (AOC 0.53, 95% CI 0.46-0.60), and consequently its calibration was poor (Hosmer-Lemeshow test P<.05). CONCLUSION: The CIPHER model for prediction of mortality and need for interventions in critically ill obstetric patients did not perform well in our Brazilian population. Different predictors of morbidity and mortality may need to be used for patients receiving care in public hospitals in low- and middle-income countries.

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