Cardiovascular severe maternal morbidity in pregnant and postpartum women: development and internal validation of risk prediction models.


Journal

BJOG : an international journal of obstetrics and gynaecology
ISSN: 1471-0528
Titre abrégé: BJOG
Pays: England
ID NLM: 100935741

Informations de publication

Date de publication:
04 2021
Historique:
accepted: 09 09 2020
pubmed: 19 9 2020
medline: 18 3 2021
entrez: 18 9 2020
Statut: ppublish

Résumé

To develop and internally validate risk prediction models identifying women at risk for cardiovascular severe maternal morbidity (CSMM). A retrospective cohort study. An obstetric teaching hospital between 2007 and 2017. A total of 89 681 delivery hospitalisations. We created and evaluated two models, one predicting CSMM at delivery (delivery model) and the other predicting CSMM postpartum following discharge from delivery hospitalisation (postpartum CSMM). We assessed model discrimination and calibration and used bootstrapping for internal validation. Cardiovascular severe maternal morbidity comprised the following confirmed conditions: pulmonary oedema/acute heart failure, myocardial infarction, aneurysm, cardiac arrest/ventricular fibrillation, heart failure/arrest during surgery or procedure, cerebrovascular disorders, cardiogenic shock, conversion of cardiac rhythm and difficult-to-control severe hypertension. The delivery model contained 11 variables and 3 interaction terms. The strongest predictors were gestational hypertension, chronic hypertension, multiple gestation, cardiac lesions or valvular heart disease, maternal age ≥40 years and history of poor pregnancy outcome. The postpartum model comprised eight variables. The strongest predictors were severe pre-eclampsia, non-Hispanic Black race/ethnicity, chronic hypertension, gestational hypertension, non-severe pre-eclampsia and maternal age ≥40 years at delivery. The delivery and postpartum models had an area under the receiver operating characteristic curve of 0.87 (95% CI 0.85-0.89) and 0.85 (95% CI 0.80-0.90), respectively. Both models were adequately calibrated and performed well on internal validation. These tools may help providers to identify women at highest risk of CSMM and enable future prevention measures. Risk assessment tools for cardiovascular severe maternal morbidity were developed and internally validated.

Identifiants

pubmed: 32946639
doi: 10.1111/1471-0528.16512
doi:

Types de publication

Journal Article Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

922-932

Subventions

Organisme : Women & Infants Hospital of Rhode Island Constance A. Howes Innovation Research Fund Award

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2020 John Wiley & Sons Ltd.

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Auteurs

I Malhamé (I)

Department of Medicine, McGill University Health Centre, McGill University, Montreal, Quebec, Canada.
Department of Medicine, Women and Infants Hospital, Warren Alpert School of Brown University, Providence, RI, USA.

V A Danilack (VA)

Department of Obstetrics and Gynecology, Women & Infants Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA.

C A Raker (CA)

Department of Obstetrics and Gynecology, Women & Infants Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA.

E J Hardy (EJ)

Department of Medicine, Women and Infants Hospital, Warren Alpert School of Brown University, Providence, RI, USA.
Department of Obstetrics and Gynecology, Women & Infants Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA.

H Spalding (H)

Department of Medicine, Women and Infants Hospital, Warren Alpert School of Brown University, Providence, RI, USA.

B A Bouvier (BA)

Department of Medicine, Women and Infants Hospital, Warren Alpert School of Brown University, Providence, RI, USA.

H Hurlburt (H)

Department of Medicine, Brigham and Women's Cardiovascular Associates of Care New England, Harvard Medical School, Boston, MA, USA.

R Vrees (R)

Department of Obstetrics and Gynecology, Women & Infants Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA.

D A Savitz (DA)

Department of Obstetrics and Gynecology, Women & Infants Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA.

N Mehta (N)

Department of Medicine, Women and Infants Hospital, Warren Alpert School of Brown University, Providence, RI, USA.
Department of Medicine, Rhode Island Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA.

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