Development of an integrated predictive model for the risks of obstetric hemorrhage in multiple pregnancies

DOI

https://dx.doi.org/10.18565/aig.2026.154

Gladkova K.A., Sakalo V.A., Kiryanova A.O.
1) Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of the Russian Federation, Moscow, Russia; 2) N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation (Sechenov University), Moscow, Russia

Background. Obstetric hemorrhage remains one of the leading causes of maternal mortality and accounts for approximately 28% of deliveries. In multiple pregnancies, the risk of hemorrhagic complications is significantly increased, highlighting the need for tools that enable early risk prediction.
Objective. To develop an integrated prognostic model for predicting the risk of obstetric hemorrhage in women with twin pregnancies.
Materials and methods. This retrospective single-center cohort observational study included 590 pregnant women with twin pregnancies. Patients were divided into two groups: those who developed intrapartum or postpartum hemorrhage (≥1000 mL) (n=38) and those without hemorrhage (n=552). The selection of variables for statistical analysis was based on the published literature and the availability of retrospective clinical data. Clinical, anamnestic, ultrasonographic, and laboratory parameters were analyzed. Continuous variables were compared using the Mann–Whitney U test, and categorical variables were analyzed using the chi-square test or Fisher’s exact test, as appropriate. To identify risk factors, univariate and multivariate binary logistic regression analyses were performed, with the calculation of odds ratios (OR) and 95% confidence intervals (CI). The predictive performance of the model was assessed using receiver operating characteristic (ROC) curve analysis, including the determination of an optimal cutoff value, followed by the construction of a nomogram.
Results. In the hemorrhage group, hemoglobin and platelet levels were significantly lower than those in the non-hemorrhage group (115.0 vs. 118.0 g/L, p=0.016; 179×10⁹/L vs. 212.5×10⁹/L, p=0.001, respectively). In multivariate analysis, an independent predictor of bleeding was previous anemia (OR 3.12; 95% CI 1.39–6.99; p=0.006), while an increase in hemoglobin levels above 115 g/l (OR 0.957; 95% CI 0.931–0.985; p=0.002) and platelets above 179.0×109/L (OR 0.987; 95% CI 0.981–0.993; p<0.0001) was associated with a reduced risk. ROC curve analysis demonstrated good predictive performance of the model (AUC=0.779; 95% CI 0.696–0.862; p<0.0001), with an optimal cutoff value of 0.06587 (sensitivity, 75.7%; specificity, 72.8%). Based on the multifactor model, a nomogram was constructed using the RMS Packet Edition 7.1.7.0 32 software.
Conclusion. The developed prognostic model demonstrated satisfactory predictive performance; however, it requires further external validation in independent cohorts and prospective studies.

Authors' contributions. Gladkova K.A. – conception and design of the study, statistical analysis, drafting, structuring, and finalizing the manuscript; Gladkova K.A., Sakalo V. A., Kiryanova A.O. – data collection, statistical analysis, drafting and editing of the manuscript.
Conflicts of interest. The authors have no conflicts of interest to declare.
Funding. There was no funding for this study.
Ethical Approval. The study was reviewed and approved by the Research Ethics Committee of the V.I. Kulakov NMRC for OG&P.
Generative Artificial Intelligence. In preparing this article, ChatGPT (OpenAI GPT-5.3-mini) artificial intelligence tools were used to improve the structure and style of the article. The content generated by the AI was reviewed, edited, and approved by the authors. The authors bear full responsibility for the accuracy of the content of this publication.
Patient Consent for Publication. All patients provided informed consent for the publication of their data.
Authors' Data Sharing Statement. The data supporting the findings of this study are available upon request from the corresponding author after approval from the principal investigator.
For citation: Gladkova K.A., Sakalo V.A., Kiryanova A.O. Development of an integrated
predictive model for the risks of obstetric hemorrhage in multiple pregnancies.
Akusherstvo i Ginekologiya/Obstetrics and Gynecology. 2026; (8): 74-82 (in Russian)
https://dx.doi.org/10.18565/aig.2026.154

postpartum hemorrhage

multiple pregnancies

risk factors

nomogram

Full text (in Russian)

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Received 05.05.2026

Accepted 30.06.2026

Kristina A. Gladkova, PhD, Head of the 1st Obstetric Department of Pregnancy Pathology, V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia, 4 Ac. Oparina str., Moscow, 117997, Russia, +7(916)321-10-07, k_gladkova@oparina4.ru, https://orcid.org/0000-0001-8131-4682
Victoria A. Sakalo, PhD, Obstetrician-Gynecologist at the 1st Obstetric Department of Pregnancy Pathology, V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia, 4 Ac. Oparina str., Moscow, 117997, Russia, +7(929)588-72-08, v_sakalo@oparina4.ru,
https://orcid.org/0000-0002-5870-4655
Anastasia O. Kiryanova, 6th year student at the N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia (Sechenov University), 8-2 Trubetskaya str., Moscow, 119048, Russia, +7(963)380-89-16, anastasia.kiryanova2002@gmail.com
Corresponding author: Kristina A. Gladkova, k_gladkova@oparina4.ru

Development of an integrated predictive model for the risks of obstetric hemorrhage in multiple pregnancies

Gladkova K.A., Sakalo V.A., Kiryanova A.O.

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