Evidence map›Paper›PMID 35813439›Full record

ArticleComputational and mathematical methods in medicine2022

Subretinal Drusenoid Deposits and Lower Serum High-Density Lipoprotein Cholesterol Levels Possess Latent Relation to Cardiovascular Disease and Can Be a Feasible Predictor.

Changsen Liang, Ning Wang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Changsen LiangDepartment of Ophthalmology, Jinan Seventh People's Hospital, Jinan 250132, China.
Ning WangDepartment of Cardiovascularology, Jinan Seventh People's Hospital, Jinan 250132, China.ORCID https://orcid.org/0000-0002-5204-7914

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To ascertain whether lipid-related subretinal drusenoid deposits (SDD) are correlated with coexisting cardiovascular disease (CVD), as well as to reveal latent serum markers of CVD. Methods: Patients older than 50 years and plagued by age-related macular degeneration (AMD) were included. Subjects with other retinal degenerations and vascular diseases, any recent treatment at other medical care institutions, and any previous oculopathy or ophthalmic surgery were excluded. All subjects were examined to ascertain whether they possess SDD, to analyze serum cholesterols, including low-density lipoprotein cholesterol (LDL), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and total cholesterol (TC). Subjects were divided into SDD and non-SDD groups and further divided into subgroups by assessment of pump defect, valve defect, and carotid defect. Finally, logistic model trees and random forest algorithm analysis were performed. Results: A total of 85 AMD patients including 43 with and 42 without SDD were involved. The 42 AMD (97.67%, 42/43) patients with SDD showed CVD, including 3 subjects presenting valve defect, 3 subjects presenting carotid defect, 8 subjects presenting pump defect, 14 subjects presenting both pump and valve defects, and 14 subjects presenting pump, valve, and carotid defects. By contrast, 5 AMD (11.90%, 5/42) patients without SDD showed CVD. Cholesterol level of SDD subjects presented significant higher TC (5.66 ± 1.01 vs. 5.58 ± 0.72, Conclusions: The presence of SDD of AMD and lower serum HDL cholesterol level can predict certain CVD for AMD patients. The machine learning based on the SDD image and serum HDL cholesterol may open new avenue for the detection of CVD as a noninvasive approach.

Indexed as

Cardiovascular DiseasesMacular DegenerationRetinal DrusenCholesterol, HDLHumansRisk FactorsTomography, Optical CoherenceCholesterol, HDL

Identifiers

PMID35813439
PMCPMC9270125
OpenAlexW4283776933

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.