Evidence map›Paper›PMID 40046046›Full record

ArticleFrontiers in immunology2025

Aberrant lipid profiles and lymphocyte counts in systemic sclerosis population, reassessing predictive value for concurrent cardiovascular diseases.

Ronghong Guo, Jinfang Gao, Yanli Yang, Ke Xu

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  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

4 authors.

Ronghong GuoThird Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Jinfang GaoThird Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Yanli YangThird Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Ke XuThird Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate alterations in blood lipid profiles and T cell subsets among systemic sclerosis (SSc) patients, and to assess their potential utility in predicting cardiovascular disease (CVD) risk. Methods: 105 SSc patients and 80 age- and sex-matched healthy controls (HCs) were enrolled. Flow cytometry was employed to quantify T cell subsets. Multivariate logistic regression analysis investigated the association between blood lipid profile, T cell subsets, SSc occurrence, and CVD risk. Additionally, a prediction model was developed to assess the potential predictive value of CVD risk. Results: In the SSc patients, low-density lipoprotein cholesterol (LDL-C) (OR = 3.212, 95%CI = 1.132-9.113, Conclusion: Altered lipid profiles and dysregulated Th cell expression in SSc patients, with a significant elevation of Th cells specifically noted in SSc-CVD patients, suggesting that Th cells may serve as a potential predictive biomarker for CVD in SSc patients, thereby aiding in early diagnosis. The underlying mechanism of this association requires further investigation.

Indexed as

Cardiovascular DiseasesLipidsScleroderma, SystemicAdultAgedBiomarkersCase-Control StudiesFemaleHumansLymphocyte CountMaleMiddle AgedPredictive Value of TestsRisk FactorsT-Lymphocyte SubsetsBiomarkersLipidscardiovascular diseaselow-density lipoprotein cholesterolrisk factorsystemic sclerosisT helper cells

Identifiers

PMID40046046
PMCPMC11880226

What OpenQuestion holds

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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.