Evidence map›Paper›PMID 41087817›Full record

ArticleJournal of assisted reproduction and genetics2025

Prediction of the acupuncture effects on pregnancy outcomes with personalized, embryonic, endometrial characteristics in women undergoing frozen-thawed embryo transfer.

Li-Ying Liu, Yuan-Yuan Lai, Yong-Na Wu, Lei Huang, Rui Tian, Di Gan, Wen-Hui Hu, Si-Yi Yu, Jie Yang

Abstract read
In one paragraph

Article in Journal of assisted reproduction and genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Li-Ying LiuAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China.
Yuan-Yuan LaiAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China.
Yong-Na WuAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China.
Lei HuangAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China.
Rui TianAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China.
Di GanAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China.
Wen-Hui HuReproductive Medicine Center, Chengdu Jinjiang Hospital for Women and Children Health, Chengdu, 610000, China.
Si-Yi YuAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China.
Jie YangAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, No.37 Shi'er Qiao Road, Chengdu, 610075, China. jenny_yang_jie@126.com.ORCID http://orcid.org/0000-0002-6787-0938

Funding

National Natural Science Foundation of China 82174517National Natural Science Foundation of China 82505759National Natural Science Foundation of China 82575219Sichuan Province Science and Technology Support Program 2020JDJQ0051
6 · The paper itself

Abstract

objectiveAcupuncture is acknowledged for its safety and effectiveness in the process of frozen embryo transfer (FET) to improve pregnancy outcomes. The study aimed to develop a clinical prediction model to predict the probability of clinical pregnancy after acupuncture treatment during FET and to identify the most predictive characteristics.

methodsTwo clinical trials on acupuncture treatment during FET containing a total of 390 patients (315 in Trial 1 and 75 in Trial 2) were involved for data training. Eighty baseline clinical characteristics were collected from patients in Trial 1, and the support vector classification (SVC) model was created to predict the improvement of FET clinical pregnancy by acupuncture. Trial 1 was utilized as the internal validation set (divided into internal test and validation sets in a 7:3 ratio), whereas Trial 2 was used as the external validation set to assess the external generalizability of this clinical prediction model.

resultsIn Trial 1, the prediction model achieved an accuracy of 0.778, a precision of 0.821, a recall score of 0.807, an f1 score of 0.814, and an AUC of 0.772 in predicting the acupuncture response. The in-hospital cycle, vascularized flow index, and transferred embryo number were the essential predictive features identified by the SVC model. For Trial 2, an accuracy of 0.74, a precision of 0.625, a recall score of 0.625, an f1 score of 0.625, an AUC of 0.713 were shown in the LSVC model.

conclusionThe clinical prediction model constructed through this study may help physicians determine in advance how patients will respond to acupuncture before FET and provide accurate treatment plans for acupuncture.

Indexed as

Acupuncture TherapyEmbryo TransferEndometriumAdultCryopreservationFemaleFertilization in VitroHumansPregnancyPregnancy OutcomePregnancy RateAcupunctureClinical prediction modelFrozen embryo transferMachine learningPregnancy

Identifiers

PMID41087817
PMCPMC12705510

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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 OpenQuestion graph.