A prediction model for hemolysis, elevated liver enzymes and low platelets syndrome in pre-eclampsia with severe features.

HELLP syndrome prediction model pre‐eclampsia with severe features risk factors

Journal

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
ISSN: 1879-3479
Titre abrégé: Int J Gynaecol Obstet
Pays: United States
ID NLM: 0210174

Informations de publication

Date de publication:
09 Aug 2024
Historique:
revised: 28 07 2024
received: 03 06 2024
accepted: 30 07 2024
medline: 9 8 2024
pubmed: 9 8 2024
entrez: 9 8 2024
Statut: aheadofprint

Résumé

The aim of the present study was to determine the risk factors for patients with pre-eclampsia (PE) with severe features to develop hemolysis, elevated liver enzymes and low platelets (HELLP) syndrome and to design a prediction score model that incorporates these risk factors. A retrospective cohort study was conducted at a tertiary university-affiliated medical center between 2011 and 2019. The study population comprised patients diagnosed with PE with severe features, divided into two groups: those with HELLP syndrome (study group) and those without (control group). A logistic regression was employed to identify independent predictors of HELLP syndrome. A predictive model for the occurrence of HELLP syndrome in the context of PE with severe features was developed using a receiver operating characteristic curve analysis. Overall, 445 patients were included, of whom 69 patients were in the study group and 376 in the control group. A multivariate logistic analysis regression showed that maternal age <40 (OR = 2.28, 95% CI: 1.13-5.33, P = 0.045), nulliparity (OR = 2.22, 95% CI: 1.14-4.88, P = 0.042), mild hypertension (OR = 2.31, 95% CI: 1.54-4.82, P = 0.019), epigastric pain (OR = 3.41, 95% CI: 1.92-7.23, P < 0.001) and placental abruption (OR = 6.38, 95% CI: 1.29-35.61, P < 0.001) were independent risk factors for HELLP syndrome. A prediction score model reached a predictive performance with an area under the curve of 0.765 (95% CI: 0.709-0.821). This study identified several key risk factors for developing HELLP syndrome among patients with PE with severe features and determined that a prediction score model has the potential to aid clinicians in identifying high risk patients.

Identifiants

pubmed: 39118476
doi: 10.1002/ijgo.15848
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 The Author(s). International Journal of Gynecology & Obstetrics published by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics.

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Auteurs

Itamar Gilboa (I)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Daniel Gabbai (D)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Yariv Yogev (Y)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Omri Dominsky (O)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Yuval Berger (Y)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Michael Kupferminc (M)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Liran Hiersch (L)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Eli Rimon (E)

Lis Hospital for Women's Health, Tel Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Classifications MeSH