Evidence mapPaperPMID 39705275Full record

SynthesisPloS one2024

Development and validation of a risk assessment model for predicting the failure of early medical abortions: A clinical prediction model study based on a systematic review and meta-analysis.

An-Hao Liu, Bin Xu, Xiu-Wen Li, Yue-Wen Yu, Hui-Xin Guan, Xiao-Lu Sun, Yan-Zhen Lin, Li-Li Zhang, Xian-Di Zhuo, Jia Li and 5 more

Abstract readSystematic ReviewMeta-AnalysisValidation Study
In one paragraph

Synthesis in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
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

2 citing papers in PubMed.

  1. Abortion-A brief description of the evolution of methods.Acta obstetricia et gynecologica Scandinavica · 2026
    Article
  2. Article
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

15 authors.

An-Hao LiuDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Bin XuDepartment of Basic Medicine, School of Medicine, Xiamen University, Xiamen, China.
Xiu-Wen LiDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Yue-Wen YuDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Hui-Xin GuanDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Xiao-Lu SunDepartment of Ultrasound, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Yan-Zhen LinDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Li-Li ZhangDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Xian-Di ZhuoDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Jia LiDepartment of Obstetrics and Gynecology, Jianning General Hospital, Sanming, China.
Wen-Qun ChenDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Wen-Feng HuDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Ming-Zhu YeDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Xiu-Min HuangDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Xun ChenDepartment of Obstetrics and Gynecology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.ORCID 0009-0004-1465-3333

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAs the first model in predicting the failure of early medical abortion (EMA) was inefficient, this study aims to develop and validate a risk assessment model for predicting the failure of EMAs more accurately in a clinical setting.

methodsThe derivation cohort was obtained from a comprehensive systematic review and meta-analysis. The clinically significant risk factors were identified and combined with their corresponding odds ratios to establish a risk assessment model. The risk factors were assigned scores based on their respective weightings. The model's performance was evaluated by an external validation cohort obtained from a tertiary hospital. The outcome was defined as the incidence of EMA failure.

resultsA total of 126,420 patients who had undergone medical abortions were included in the systematic review and meta-analysis, and the pooled failure rate was 6.7%. The final risk factors consisted of gestational age, maternal age, parity, previous termination of pregnancy, marital status, type of residence, and differences between gestational age calculated using the last menstrual period and that measured via ultrasound. The risk factors were assigned scores based on their respective weightings, with a maximum score of 19. The clinical prediction model exhibited a good discrimination, as validated by external verification (402 patients) with an area under the curve of 0.857 (95% confidence interval 0.804-0.910). The optimal cutoff value was determined to be 13.5 points, yielding a sensitivity of 83.3% and specificity of 75.4%.

conclusionThis study effectively establishes a simple risk assessment model including seven routinely available clinical parameters for predicting EMA failure. In preliminary validation, this model demonstrates good performance in terms of predictive efficiency, accuracy, calibration, and clinical benefit. However, more research and validation are warranted for future application. TRIAL REGISTRATION NUMBER: CRD42023485388.

Indexed as

Abortion, InducedAdultFemaleGestational AgeHumansMaternal AgePregnancyRisk AssessmentRisk FactorsTreatment Failure

Identifiers

PMID39705275
PMCPMC11661585

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.