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Record W4401185418 · doi:10.69944/pjc.b163abe16b

The Neutrophil-Lymphocyte Ratio Predicts Mortality in Acute Coronary Syndrome (NLR-ACS): A Meta-analysis

2015· article· en· W4401185418 on OpenAlexaboutno aff
Edgar Wilson G Timbol, John Daniel A Ramos, Jaime Alfonso M. Aherrera, Lowe Chiong, Felix Eduardo R. Punzalan

Bibliographic record

VenuePhilippine journal of cardiology. · 2015
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsAcute coronary syndromeNeutrophil to lymphocyte ratioMedicineMeta-analysisInternal medicineCardiologyLymphocyteMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: The neutrophil to lymphocyte ratio (NLR) is a recently described biomarker of inflammation that is an independent predictor of death and myocardial infarction. It integrates two leukocyte subtype counts with opposing actions in terms of vascular inflammation. This can be readily derived from a simple routine complete blood count taken during admission. We conducted a meta-analysis on the usefulness of a high NLR value in predicting mortality among patients with acute coronary syndrome (ACS). OBJECTIVE: To determine the association of neutrophil to lymphocyte ratio and mortality among patients with acute coronary syndrome. METHODS: We conducted a systematic search of studies using MEDLINE, EMBASE, ScienceDirect, and Cochrane Central Register of Controlled Trials databases and examined reference lists of studies that used the NLR in ACS patients in reporting mortality. We identified 12 studies that met inclusion criteria including 2 local studies. The study title, follow-up period, neutrophil-lymphocyte ratio, and mortality outcomes were extracted from these studies. Each study was assessed using the Newcastle-Ottawa Quality Assessment Scale. These were done independently by the authors resolving disagreements, if any, by discussion. The outcome of interest was assessed using Mantel Haenzel analysis to compute for odds ratio, and evaluation of heterogeneity were carried out using Review Manager (RevMan) 5.0.18 (The Nordic Cochrane Centre, The Cochrane Collaboration). RESULTS: Data were combined from 12 studies enrolling 9,835 patients. Pooled analysis showed that a high NLR was predictive of increased total mortality among patients presenting with ACS compared to those patients whose NLR were not high (8.65% vs 2.26%, OR 4.10, 95% CI 3.36, 5.00; p<0.00001). Data were homogenous (I2=0%) and there was no evidence of publication bias by funnel-plot method. Thirty-day mortality, including in-hospital death, was likewise increased among those with high NLR (7.78% vs 2.22%, OR 3.67, 95% CI 2.93, 4.58; p<0.00001; I2=0%). CONCLUSION: A high NLR value is associated with high mortality among patients with ACS. This parameter can be easily derived from a routine complete blood count taken during hospital admission and is a useful parameter to determine prognosis and may indicate a more intensive approach to therapy. Keywords: neutrophil-lymphocyte ratio, NLR, acute coronary syndrome, mortality, ACS, NSTEMI, STEMI, unstable angina, ST-segment myocardial infarction, non-ST-segment myocardial infarction

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.032
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0220.060
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.074
GPT teacher head0.320
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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