{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T17:04:44Z","timestamp":1781715884677,"version":"3.54.5"},"reference-count":23,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T00:00:00Z","timestamp":1723161600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Intl J Gynecology &amp; Obste"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>The aim of the present study was to determine the risk factors for patients with pre\u2010eclampsia (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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A retrospective cohort study was conducted at a tertiary university\u2010affiliated 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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 &lt;40 (OR\u2009=\u20092.28, 95% CI: 1.13\u20135.33, <jats:italic>P<\/jats:italic>\u2009=\u20090.045), nulliparity (OR\u2009=\u20092.22, 95% CI: 1.14\u20134.88, <jats:italic>P<\/jats:italic>\u2009=\u20090.042), mild hypertension (OR\u2009=\u20092.31, 95% CI: 1.54\u20134.82, <jats:italic>P<\/jats:italic>\u2009=\u20090.019), epigastric pain (OR\u2009=\u20093.41, 95% CI: 1.92\u20137.23, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001) and placental abruption (OR\u2009=\u20096.38, 95% CI: 1.29\u201335.61, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001) 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\u20130.821).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1002\/ijgo.15848","type":"journal-article","created":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T07:15:49Z","timestamp":1723187749000},"page":"230-236","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A prediction model for hemolysis, elevated liver enzymes and low platelets syndrome in pre\u2010eclampsia with severe features"],"prefix":"10.1002","volume":"168","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0941-2074","authenticated-orcid":false,"given":"Itamar","family":"Gilboa","sequence":"first","affiliation":[{"name":"Lis Hospital for Women\u2019s Health Tel Aviv Sourasky Medical Center Faculty of Medicine Tel Aviv University  Tel Aviv Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Gabbai","sequence":"additional","affiliation":[{"name":"Lis Hospital for Women\u2019s Health Tel Aviv Sourasky Medical Center Faculty of Medicine Tel Aviv University  Tel Aviv Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yariv","family":"Yogev","sequence":"additional","affiliation":[{"name":"Lis Hospital for Women\u2019s Health Tel Aviv Sourasky Medical Center Faculty of Medicine Tel Aviv University  Tel Aviv 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