Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as predictors of mortality in acute pulmonary embolism: A systematic review and meta-analysis
Bibliographic record
Abstract
Objective: The purpose of this review was to examine the association between neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) and mortality rates in patients with acute pulmonary embolism (PE). Methods: PubMed Central, Scopus, Web of Science, and Embase were searched for studies reporting the association between NLR and PLR with mortality up to March 17th 2023. Adjusted ratios were sourced from studies and combined to generate pooled outcomes as odds ratio (OR) in a random-effects model. Risk of bias was assessed using the Newcastle Ottawa Scale. Results: Fifteen studies were included. Meta-analysis showed that NLR was a significant predictor of mortality in patients with PE (OR: 1.42 95% CI: 1.26, 1.61 I2=92%). Results were unchanged on sensitivity analysis and subgroup analysis based on study location, method of diagnosis, sample size, overall mortality rates, cut-offs, and follow-up. Pooled analysis failed to demonstrate PLR as a predictor of mortality in patients with PE (OR: 1.00 95% CI: 1.00, 1.01 I2=57%). Results were unchanged on sensitivity analysis and subgroup analysis based on study location, diagnosis of PE, overall mortality rates, and cut-off. Conclusion: Current evidence from retrospective studies shows that NLR can independently predict mortality in acute PE. Data on PLR was limited and failed to indicate an independent role in the prognosis of PE patients. Registration No. PROSPERO (CRD42023407573). doi: https://doi.org/10.12669/pjms.40.6.8802 How to cite this: Tang S, Hu Y. Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as predictors of mortality in acute pulmonary embolism: A systematic review and meta-analysis. Pak J Med Sci. 2024;40(6):1274-1279. doi: https://doi.org/10.12669/pjms.40.6.8802 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".