MétaCan
Menu
Back to cohort
Record W4411033059 · doi:10.31083/rcm27942

Platelet-To-Lymphocyte Ratio Efficiency in Predicting Major Adverse Cardiovascular Events After Percutaneous Coronary Intervention in Acute Coronary Syndromes: A Meta-Analysis

2025· review· en· W4411033059 on OpenAlex
Tuerxun Zulikaier, Balati Yumaierjiang, Pengyi He

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReviews in Cardiovascular Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePercutaneous coronary interventionInternal medicineConventional PCIAcute coronary syndromeSubgroup analysisMeta-analysisCochrane LibraryReceiver operating characteristicCardiologyPublication biasInclusion and exclusion criteriaMyocardial infarctionPathology

Abstract

fetched live from OpenAlex

Background: The platelet-to-lymphocyte ratio (PLR) is applied as a potential first-line prognostic predictor for many cardiovascular diseases due to its simplicity and accessibility. This meta-analysis aimed to quantify the predictive power of PLR for major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI), explore its predictive efficacy in different populations, and identify other potential influencing factors. Methods: PubMed, Embase, Cochrane Library, and Web of Science databases were comprehensively searched for eligible studies until February 7, 2025, based on the inclusion and exclusion criteria. The Newcastle–Ottawa scale (NOS) was employed for quality assessment. Sensitivity, specificity, summary receiving operating characteristic (SROC) and area under the curve (AUC) were combined using Stata 15.1 and Meta-DiSc software. Meta-regression analyses, subgroup analyses, threshold effect analyses, sensitivity analyses, and publication bias tests were performed. Results: Nine studies (7174 patients) were enrolled. High PLR could predict MACEs in ACS patients undergoing PCI, with 0.68 sensitivity (95% CI, 0.60–0.76), 0.65 specificity (95% CI, 0.57–0.73), and 0.72 AUC (95% CI, 0.68–0.76). Subgroup analyses noted that PLR better predicted MACEs after PCI in ACS patients in the subgroup with a higher proportion of female patients and the subset aged >60 years. Meta-regression analyses unveiled that study type (p < 0.01) and PLR cutoff value (p < 0.01) might be sources of heterogeneity in the sensitivity analyses, while the mean age (p < 0.001) and sex ratio (p = 0.05) might be sources of heterogeneity in the specificity analyses. Conclusions: High PLR levels have favorable values in predicting in-hospital and long-term MACEs after PCI in ACS patients. The PLR had greater sensitivity and an improved ability to identify risk in patients aged >60 years and the subgroup with a higher proportion of women and was also more sensitive to in-hospital MACEs. The PROSPERO Registration: No. CRD42024537586, https://www.crd.york.ac.uk/PROSPERO/view/CRD42024537586.

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.

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)0.014
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.502
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0270.035
Bibliometrics0.0060.008
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.330
Teacher spread0.285 · 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