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Record W4411112607 · doi:10.1177/03000605251345954

Association of sST2 with cardiovascular disease in maintenance hemodialysis patients: A systematic review and meta-analysis

2025· review· en· W4411112607 on OpenAlexaboutno aff
Ze Zhang, Tao Yang, Mengya Zhao, Huaqian Chen

Bibliographic record

VenueJournal of International Medical Research · 2025
Typereview
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisHemodialysisInternal medicineDiseaseSystematic reviewMEDLINEIntensive care medicine

Abstract

fetched live from OpenAlex

Background Previous studies have shown that soluble growth-stimulated expression gene 2 protein (sST2) plays a significant role in the progression of maintenance hemodialysis. However, the relationship between sST2 and cardiovascular events in maintenance hemodialysis patients remains largely understudied. Method This study systematically searched PubMed, Wanfang, and other Chinese and English databases for all published studies on sST2 in maintenance hemodialysis. Relevant literature meeting the requirements was screened, and relevant data were extracted accordingly. The Newcastle–Ottawa Scale was used to evaluate the quality of the selected studies. Publication bias was assessed via funnel plots and Egger’s test. A meta-analysis was performed using either a random-effects or fixed-effects model, as appropriate. Results A total of 10 high-quality studies were included in this study, with no significant publication bias. The meta-analysis revealed that sST2 level was associated with the incidence of cardiovascular events in maintenance hemodialysis patients (mean difference = 18.89, 95% confidence interval: 13.93–23.84; p < 0.001). Moreover, elevated sST2 levels were correlated with a higher risk of cardiovascular events (odds ratio = 2.89, 95% confidence interval: 1.71–4.89; p < 0.0001). Conclusion sST2 may serve as a predictive biomarker for cardiovascular events in maintenance hemodialysis patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.274
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.374
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

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