Evidence map›Paper›PMID 35685210›Full record

Trial reportFrontiers in endocrinology2022

A Validated Model for Individualized Prediction of Live Birth in Patients With Adenomyosis Undergoing Frozen-Thawed Embryo Transfer.

Yaoqiu Wu, Rong Yang, Haiyan Lin, Chunwei Cao, Xuedan Jiao, Qingxue Zhang

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Yaoqiu WuGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Rong YangReproductive Medicine Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Haiyan LinReproductive Medicine Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Chunwei CaoGuangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Xuedan JiaoReproductive Medicine Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Qingxue ZhangReproductive Medicine Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Sun Yat-sen Memorial Hospital · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to develop a predictive tool for live birth in women with adenomyosis undergoing Methods: A total of 424 patients with adenomyosis who underwent frozen-thawed embryo transfer (FET) from January 2013 to December 2019 at a public university hospital were included. The patients were randomly divided into training ( Results: In total, 183 (43.16%) patients became pregnant, and 114 (26.88%) had a live birth. The MLR showed that the probability of live birth was significantly correlated with age [odds ratio (OR), 3.465; 95% confidence interval (CI), 1.215-9.885, Conclusions: This visual and easily applied nomogram built on the risk factors of live birth in patients with adenomyosis provides useful and precise information for physicians on individualized decision-making during the IVF/ICSI procedure.

Indexed as

AdenomyosisLive BirthEmbryo TransferFemaleHumansPregnancyPregnancy RateSperm Injections, IntracytoplasmicadenomyosisGnRH-alive birthprediction modeluterine size

Identifiers

PMID35685210
PMCPMC9171040
OpenAlexW4281381826

What OpenQuestion 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 OpenQuestion graph.