Evidence map›Paper›PMID 37358602›Full record

Trial reportAbdominal radiology (New York)2023

MRI-based scoring model to predict massive hemorrhage during dilatation and curettage in patients with cesarean scar pregnancy.

Fengleng Yang, Xilin Yang, Huaibo Jing, Xiaodan Wang, Zhaolin Gong, Chen Deng, Fang Wang, Yongzhong Shuai, Zhigang Wang, Hua Lai

Abstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in Abdominal radiology (New York), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.6field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Fengleng Yang *Department of Radiology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Xilin Yang *Department of Radiation Oncology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Huaibo JingDepartment of Gynecology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Xiaodan WangDepartment of Gynecology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Zhaolin GongDepartment of Gynecology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Chen DengDepartment of Radiology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Fang WangDepartment of Radiology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Yongzhong ShuaiDepartment of Radiology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Zhigang WangDepartment of Radiology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China. docwzg@yeah.net.ORCID http://orcid.org/0000-0002-4589-0946
Hua LaiDepartment of Radiology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China. 383616361@qq.com.
University of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo construct a scoring model based on MRI signs to predict massive hemorrhage during dilatation and curettage in cesarean scar pregnancy (CSP) patients. MATERIALS AND

methodsThe MRIs of CSP patients admitted to a tertiary referral hospital between February 2020 and July 2022 were retrospectively reviewed. The included patients were randomly assigned to the training and validation cohorts. The univariate and multivariate logistic regression analyses were adopted to identify the independent risk factors for massive hemorrhage (the amount of bleeding ≥ 200 ml) during the dilatation and curettage. A scoring model predicting intraoperative massive hemorrhage was established where each positive independent risk factor was assigned 1 point, and the predictive power of this model was evaluated both in the training and validation cohorts via the receiver operating characteristic curve.

resultsA total of 187 CSP patients were enrolled, who were divided into the training cohort (31 in 131 patients had massive hemorrhage) and validation cohort (10 in 56 patients had massive hemorrhage). The independent risk factors for intraoperative massive hemorrhage included cesarean section diverticulum area (OR = 6.957, 95% CI 1.993-21.887; P = 0.001), uterine scar thickness (OR = 5.113, 95% CI 2.086-23.829; P = 0.025) and gestational sac diameter (OR = 3.853, 95% CI 1.103-13.530; P = 0.025). A scoring model with a total point of 3 was developed and the CSP patients were divided into low-risk (Total points < 2) and high-risk groups (Total points ≥ 2) for intraoperative massive hemorrhage accordingly. This model possessed high prediction performance both in the training cohort (area under the curve [AUC] = 0.896, 95% CI 0.830-0.942) and validation cohort (AUC = 0.915, 95% CI 0.785-1.000).

conclusionWe first constructed a MRI-based scoring model for predicting intraoperative massive hemorrhage in CSP patients, which could help the decision-making of the patients' therapy strategies. Low-risk patients can be cured by D&C alone to reduce the financial burden, while high-risk patients require more adequate preoperative preparation or consideration of changing surgical approaches to reduce bleeding risk.

Indexed as

Cesarean SectionPregnancy, EctopicBlood Loss, SurgicalCicatrixDilatation and CurettageFemaleHumansPregnancyRetrospective StudiesTreatment OutcomeCesarean scar pregnancyCurettageMagnetic resonance imaging (MRI)Massive hemorrhageRisk factors

Identifiers

PMID37358602
OpenAlexW4382011217

What OpenQuestion holds

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Registered trials

None linked

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.