Evidence map›Paper›PMID 38711993›Full record

ArticleFrontiers in pharmacology2024

Risk prediction model based on machine learning for predicting miscarriage among pregnant patients with immune abnormalities.

Yue Wu, Xixuan Yu, Mengting Li, Jing Zhu, Jun Yue, Yan Wang, Yicun Man, Chao Zhou, Rongsheng Tong, Xingwei Wu

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
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  8. 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

10 authors.

Yue Wu *Department of Pharmacy, Personalised Drug Therapy Key Laboratory of Sichuan Province, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Xixuan Yu *School of Pharmacy, Chengdu Medical College, Chengdu, China.
Mengting LiDepartment of Pharmacy, Personalised Drug Therapy Key Laboratory of Sichuan Province, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Jing ZhuDepartment of Rheumatology and Immunology, Sichuan Provincial People's Hospital, Chengdu, China.
Jun YueDepartment of Gynaecology and Obstetrics, Sichuan Provincial People's Hospital, Chengdu, China.
Yan WangDepartment of Gynaecology and Obstetrics, Sichuan Provincial People's Hospital, Chengdu, China.
Yicun ManDepartment of Gynaecology and Obstetrics, Sichuan Provincial People's Hospital, Chengdu, China.
Chao ZhouDepartment of Gastroenterology, Sichuan Provincial People's Hospital, Chengdu, China.
Rongsheng Tong *Department of Pharmacy, Personalised Drug Therapy Key Laboratory of Sichuan Province, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Xingwei Wu *Department of Pharmacy, Personalised Drug Therapy Key Laboratory of Sichuan Province, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

clinical applicationimmunological abnormalitymachine learningpredictive modelspregnancy outcomes

Identifiers

PMID38711993
PMCPMC11070771

What OpenQuestion holds

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LicenceCC BY
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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.