The Association Of Neutrophil Lymphocyte Ratio And In-Hospital Mortality In Acute Coronary Syndrome Patients: Meta Analysis
Bibliographic record
Abstract
Coronary artery disease, including acute coronary syndrome (ACS), is a major cause of mortality and morbidity worldwide. The neutrophil lymphocyte ratio (NLR) is a nonspecific marker of inflammation and previous studies have shown that increased NLR is associated with mortality in acute coronary syndrome patients and may act as a prognostic marker. The aim of this study was to assess the association of NLR and in-hospital mortality in ACS patients. The method used in this study was, Literature search was carried out using the Ebsco, Embasse, Nature, Proquest, PubMed, Science Direct and Scopus databases until March 2022 to find an observational cohort study that assessed the association of NLR and in-hospital mortality in ACS patients. A systematic review of published studies following the preferred reporting items for systematic review and guideline meta-analysis (PRISMA) was conducted. Study quality was assessed with the Newcastle Ottawa Scale (NOS) and only high quality studies were included in this meta-analysis. The primary outcome was in-hospital mortality and the effect was measured in Risk Ratio (RR) and 95% CI. Conclusion: A high NLR increases the risk of in-hospital death in acute coronary syndrome patients. Further studies in large settings are needed to assess the NLR threshold values that can predict in-hospital mortality in acute coronary syndrome 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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".