Trial reportBMC pregnancy and childbirth2023
Establishment of a predictive model for postpartum hemorrhage in twins: a retrospective study.
Trial report in BMC pregnancy and childbirth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Accuracy of machine learning and traditional statistical models in the prediction of postpartum haemorrhage: a systematic review.BMJ open · 2025Pooled it
- The Impact of Labor-Delivery-Recovery-Postpartum (LDRP) Care Model on Delivery Outcomes: A Single-Center Retrospective Cohort Study.International journal of women's health · 2026Article
- Is Feto-Maternal Transfusion after Cesarean Delivery Different in Singleton and Twin Pregnancy?Journal of clinical medicine · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
objectiveTo explore the risk factors and develop a predictive model for postpartum hemorrhage in twin pregnancies.
methodsAll patients who gave birth at Ningbo Women and Children's Hospital from January 2018 to August 2022 were recruited. Patients were randomly allocated to a training cohort (n[Formula: see text]1395) validation cohort (n[Formula: see text]650) at a 7:3 ratio. In the training cohort, LASSO regression for screening variables and multifactorial logistic regression analysis were performed to identify independent risk factors for postpartum hemorrhage in twin pregnancies. A nomogram was established based on the results of multiple logistic regression analysis. Nomogram performance was quantified using the receiver operating characteristic curve, Hosmer- Lemeshow test and decision curve analysis.
resultsA total of 2045 patients were included in this study. Multifactorial Logistic regression analysis showed maternal age, assisted reproduction, platelet count, fibrinogen level, albumin level, hypertensive disorders of pregnancy, placenta praevia, number of previous cesarean deliveries, number of previous intrauterine manipulation, and neonatal weight were independent risk factors for postpartum hemorrhage in twin births. The area under curve (AUC) for the training cohort was 0.810 [95[Formula: see text] CI (0.781, 0.839)], with a sensitivity of 76.5[Formula: see text], specificity of 71.0[Formula: see text], and positive and negative predictive values of 0.358 and 0.935, respectively, while the AUC for the validation cohort was 0.821 [95[Formula: see text] CI (0.781, 0.860)], with a sensitivity of 80.9[Formula: see text], specificity of 69.49[Formula: see text], and positive predictive value and negative predictive value of 0.426 and 0.929, respectively.
conclusionThe predictive model can effectively and quantitatively assess the risk of postpartum hemorrhage in twin pregnancies and help clinicians to take personalized preventive measures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.