Premium
Comparison of the CIPHER prognostic model with the existing scores in predicting severe maternal outcomes during intensive care unit admission
Author(s) -
Silva Flávio X.,
Parpinelli Mary A.,
OliveiraNeto Antonio F.,
Ribeiro do Valle Carolina C.,
Souza Renato T.,
Costa Maria L.,
Correia Mario D. T.,
Katz Leila,
Cecatti José G.
Publication year - 2022
Publication title -
international journal of gynecology and obstetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.895
H-Index - 97
eISSN - 1879-3479
pISSN - 0020-7292
DOI - 10.1002/ijgo.14127
Subject(s) - medicine , cipher , intensive care unit , standardized mortality ratio , saps ii , receiver operating characteristic , cohort , pediatrics , emergency medicine , apache ii , computer science , encryption , operating system
Objective To compare the performance of the Collaborative Integrated Pregnancy High‐Dependency Estimate of Risk (CIPHER) model in predicting maternal death and near‐miss morbidity (Severe Maternal Outcome [SMO]) with the Sequential Organ Failure Assessment (SOFA), the Acute Physiology and Chronic Health Evaluation (APACHE) II, and the Simplified Acute Physiology Score (SAPS) III scores. Methods A retrospective and a prospective study was conducted at two centers in Brazil. For each score, area under curve (AUC) was used and score calibration was assessed using the Hosmer‐Lemeshow statistic (H‐L) test and the standardized mortality ratio (SMR). Results A cohort of 590 women was analyzed. A SMO was observed in 216 (36.6%) women. Of these, 13 (2.2%) were maternal deaths and 203 (34.4%) met one or more maternal near‐miss criteria. The CIPHER model did not show significant diagnostic ability (AUC 0.52) and consequently its calibration was poor (H‐L P < 0.05). The SAPS III had the best performance (AUC 0.77, H‐L P > 0.05 and SMR 0.85). Conclusion The performance of the CIPHER model was lower compared to the other scores. Since the CIPHER model is not ready for clinical use, the SAPS III score should be considered for the prediction of SMO.