MétaCan
Menu
Back to cohort
Record W2807404468 · doi:10.14740/cr732w

Red Cell Distribution Width and Mortality in Patients With Acute Coronary Syndrome: A Meta-Analysis on Prognosis

2018· article· en· W2807404468 on OpenAlexvenueaboutno aff
Lauro L. Abrahan, John Daniel Ramos, Elleen L. Cunanan, Marc Denver A. Tiongson, Felix Eduardo R. Punzalan

Bibliographic record

VenueCardiology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRed blood cell distribution widthCardiologyInternal medicineAcute coronary syndromeDistribution (mathematics)Meta-analysisMyocardial infarctionMathematics

Abstract

fetched live from OpenAlex

Background: Red cell distribution width (RDW), a routine component of the complete blood count (CBC), measures variation in the size of circulating erythrocytes. It has been associated with several clinical outcomes in cardiovascular disease. We sought to strengthen the association between RDW and mortality in patients admitted for acute coronary syndrome (ACS) by pooling together data from available studies. Methods: Studies that fulfilled the following were identified for analysis: 1) observational; 2) included patients admitted for ACS; 3) reported data on all-cause or cardiovascular (CV) mortality in association with a low or high RDW; and 4) used logistic regression analysis to control for confounders. Using MEDLINE, Clinical Key, ScienceDirect, Scopus, and Cochrane Central Register of Controlled Trials databases, a search for eligible studies was conducted until January 9, 2017. The quality of each study was evaluated using the Newcastle-Ottawa Quality Assessment Scale. Our primary outcome of interest was all-cause or CV mortality. We also investigated the impact of RDW on major adverse cardiovascular events (MACEs) for the studies that reported these outcomes. Review Manager (RevMan) 5.3 was utilized to perform Mantel-Haenzel analysis of random effects and compute for relative risk. Results: We identified 13 trials involving 10,410 patients, showing that in ACS, a low RDW is associated with a statistically significant lower all-cause or CV mortality (RR 0.35, (95% CI 0.30 to 0.40), P < 0.00001, I 2 = 53%), a finding that was consistent both in the short- and long-term. Conclusions: A low RDW is also associated with lower risk for MACEs after an ACS (RR 0.56, (95% CI 0.51 to 0.61), P < 0.00001, I 2 = 91%). A low RDW during an ACS is associated with lower all-cause or CV mortality and lower risk of subsequent MACEs, providing us with a convenient and inexpensive risk stratification tool in ACS patients. Cardiol Res. 2018;9(3):144-152 doi: https://doi.org/10.14740/cr732w

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)0.012
metaresearch head score (Gemma)0.023
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 score0.013
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.043
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.071
GPT teacher head0.361
Teacher spread0.290 · 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".

Quick stats

Citations72
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueCardiology ResearchSame topicInflammatory Biomarkers in Disease PrognosisFrench-language works237,207