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Prognostic Value of an Estimate-of-Risk Model in Critically Ill Obstetric Patients in Brazil
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 Brazi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8667803/ https://www.ncbi.nlm.nih.gov/pubmed/34915534 http://dx.doi.org/10.1097/AOG.0000000000004619 |
Sumario: | 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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