Evidence map›Paper›PMID 35559036›Full record

ArticleFrontiers in genetics2022

Clinical Prediction of Heart Failure in Hemodialysis Patients: Based on the Extreme Gradient Boosting Method.

Yanfeng Wang, Xisha Miao, Gang Xiao, Chun Huang, Junwei Sun, Ying Wang, Panlong Li, Xu You

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Predicting stroke and mortality in mitral stenosis with atrial flutter: A machine learning approach.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2023
    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

8 authors at 3 institutions in 1 country.

Yanfeng WangThe School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Xisha MiaoThe School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Gang XiaoDepartment of Clinical Laboratory, The Third Affiliated Hospital, Southern Medical University, Guangzhou, China.
Chun HuangThe School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Junwei SunThe School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Ying WangDepartment of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Panlong LiThe School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Xu YouDepartment of Clinical Laboratory, The Third Affiliated Hospital, Southern Medical University, Guangzhou, China.
Zhengzhou University of Light Industry · CNThird Affiliated Hospital of Southern Medical University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

extreme gradient boostingheart failure predictionhemodialysismachine learningrisk factors

Identifiers

PMID35559036
PMCPMC9086166
OpenAlexW4224436648

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.