P1786Red cell distribution width and mortality in patients with acute coronary syndrome: a meta-analysis on prognosis
Bibliographic record
Abstract
Background: Red cell distribution width (RDW), a routine component of the 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. Purpose: We aimed to determine the association of RDW with mortality and major cardiovascular events (MACE) in patients with ACS. Methods: 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. Studies that fulfilled the following inclusion criteria 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. The quality of each study was evaluated using the Newcastle-Ottawa Quality Assessment Scale. Our primary outcome of interest was all-cause or cardiovascular (CV) mortality. We also investigated the impact of RDW on major adverse cardiovascular events (MACE) 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.039 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".