Annals of palliative medicine · 2021
Prediction of adverse maternal and perinatal outcomes in preeclampsia based on B-type natriuretic peptide: a retrospective study.
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Hong Haijie, Zhang Lei, Hong Fanzhen, Xiao Juan, Sun Wenjuan, Dong Lihua, Li Mingjiang
Аннотация
BACKGROUND: Elevated B-type natriuretic peptide (BNP) is closely related to preeclampsia. Whether it is a predictor of adverse outcomes in preeclampsia is unclear. This study aimed to investigate the relationship between BNP and adverse outcomes of preeclampsia, and to establish the prediction models and nomograms based on BNP.
METHODS: A retrospective analysis was conducted involving 284 women with preeclampsia admitted to a tertiary hospital from January 2017 to July 2019. Logistic regression and receiver operating characteristic (ROC) curve were used to analyze the relationship between BNP and adverse outcomes. Multivariate logistic regression was used to establish the models for predicting adverse outcomes. Then the nomogram and ROC curve of the models were generated.
RESULTS: In preeclampsia, BNP is a risk factor for adverse outcomes, and as the level of BNP increases, the incidence of adverse outcomes increases. Preeclampsia with BNP >118 pg/mL was associated with a significantly increased risk of adverse outcomes. The results showed that BNP has a predictive value for adverse maternal outcomes, and the area under the ROC curve (AUC) was 0.739 [P<0.001, 95% confidence interval (CI): 0.684-0.789]. Then, the prediction models for adverse maternal and perinatal outcomes based on BNP combined with other multi-factors were established. The discriminative ability of the 2 models was found to be good, the AUC was 0.844 (95% CI: 0.796-0.884) and 0.792 (95% CI: 0.740-0.838), respectively. Therefore, BNP was shown to significantly improve the discriminative ability of the prediction models.
CONCLUSIONS: The BNP is an important risk factor for evaluating the adverse outcomes of preeclampsia. Combined with multi-factors, BNP can be used to predict the adverse outcomes.
METHODS: A retrospective analysis was conducted involving 284 women with preeclampsia admitted to a tertiary hospital from January 2017 to July 2019. Logistic regression and receiver operating characteristic (ROC) curve were used to analyze the relationship between BNP and adverse outcomes. Multivariate logistic regression was used to establish the models for predicting adverse outcomes. Then the nomogram and ROC curve of the models were generated.
RESULTS: In preeclampsia, BNP is a risk factor for adverse outcomes, and as the level of BNP increases, the incidence of adverse outcomes increases. Preeclampsia with BNP >118 pg/mL was associated with a significantly increased risk of adverse outcomes. The results showed that BNP has a predictive value for adverse maternal outcomes, and the area under the ROC curve (AUC) was 0.739 [P<0.001, 95% confidence interval (CI): 0.684-0.789]. Then, the prediction models for adverse maternal and perinatal outcomes based on BNP combined with other multi-factors were established. The discriminative ability of the 2 models was found to be good, the AUC was 0.844 (95% CI: 0.796-0.884) and 0.792 (95% CI: 0.740-0.838), respectively. Therefore, BNP was shown to significantly improve the discriminative ability of the prediction models.
CONCLUSIONS: The BNP is an important risk factor for evaluating the adverse outcomes of preeclampsia. Combined with multi-factors, BNP can be used to predict the adverse outcomes.