Evidence map›Paper›PMID 36164531›Full record

ArticleHeliyon2022

Prediction and verification of the effect of psoriasis on coronary heart disease based on artificial neural network.

An-Hai Li, Meng-Meng Qi, Wen-Wen Li, Xiao-Qian Yu, Li-Li Yang, Jun Wang, Ding Li

Abstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Metabolites and coronary heart disease: A two sample Mendelian randomization.International journal of cardiology. Cardiovascular risk and prevention · 2025
    Article
  2. Review
  3. 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

7 authors.

An-Hai LiDepartment of Dermatology, Qingdao Huangdao District Central Hospital, Qingdao, Shandong, China.
Meng-Meng QiDepartment of Endocrinology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Wen-Wen LiDepartment of Hematology, Qingdao Women and Children's Hospital, Qingdao, Shandong, China.
Xiao-Qian YuDepartment of Dermatology, Qingdao Haici Hospital (Qingdao Traditional Chinese Medicine Hospital), Qingdao, Shandong, China.
Li-Li YangDepartment of Traditional Chinese Medicine, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Jun WangDepartment of Clinical Laboratory, Weifang Maternal and Child Health Hospital Affiliated to Weifang Medical University, Weifang, Shandong, China.
Ding LiDepartment of Dermatology, Qingdao Huangdao District Central Hospital, Qingdao, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: Psoriasis is an independent risk factor for coronary heart disease. It is important for predicting the complications of coronary heart disease in patients with psoriasis. Methods: In this study, related cases were collected from the case system of Qingdao University, and commonly used laboratory indicators were extracted. Artificial neural network (ANN) and logistics regression analysis were used to learn to distinguish psoriasis patients, coronary heart disease patients, and psoriasis patients with coronary heart disease. We identified independent risk factors for coronary heart disease in psoriasis patients that exacerbate coronary heart disease symptoms in patients with psoriasis. Findings: Analysis shows that the accuracy of the ANN model was higher than 79%. It was determined that age, chlorinated, phosphorus, magnesium, low-density lipoprotein, triglycerides, high density lipoprotein and total cholesterol are independent risk factors for coronary heart disease in patients with psoriasis. Similarly, gender, age, chlorinated, magnesium, triglycerides, and high density lipoprotein are risk factors that exacerbate coronary heart disease symptoms in patients with psoriasis. Interpretation: The presented approach is a valuable tool for identifying psoriasis patients, coronary heart disease patients, and psoriasis patients with coronary heart disease. It can also serve as a support tool clinicians in the diagnostic process, by providing an outstanding support in the diagnostics prevention of coronary heart disease in psoriasis.

Indexed as

Artificial neural networksCoronary heart diseaseDeep learningMultilayer perceptronPsoriasisRegression

Identifiers

PMID36164531
PMCPMC9508559

What OpenQuestion holds

Textmetadata
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.