Neutrophil-to-lymphocyte Ratio and Red Cell Distribution Width as Potential Biomarkers of Frailty: a Scoping Review
Bibliographic record
Abstract
Background Frailty is associated with aging, which has recently become a health issue needs to be addressed urgently in the aging population. Neutrophil-to-lymphocyte ratio (NLR) and red cell distribution width (RDW) are novel inflammatory markers that are readily available clinically. Understanding the association of them with frailty is helpful to identify and monitor the development of frailty. There are few studies on the association of NLR and RDW with frailty, and they are not appropriate for traditional meta-analysis due to great heterogeneity between the study results. Objective To perform a scoping review of studies on NLR and RDW as potential biomarkers of frailty, so as to provide a reference for clarifying the pathogenesis of frailty and developing or improving frailty-related assessment tools. Methods Studies on the association of NLR and RDW with frailty were searched in eight databases (PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang Data, VIP and SinoMed) from inception to March 1, 2022. The studies on NLR and RDW as potential biomarkers of frailty was independently screened by two investigators, and the first author, publication time, country or region of publication, sample information, study methods, assessment tools, and assessment results were extracted. The quality of the literature was assessed using the Newcastle-Ottawa Scale and the AHRQ checklist for cross-sectional studies. Results A total of fourteen studies were enrolled, including five cross-sectional studies, four longitudinal studies, one cohort study and four case-control studies, which were all rated≥4 points in terms of methodological quality, indicating that they were high quality. Nine studies examined the association between NLR and frailty, and seven of them showed that elevated NLR was independently associated with increased risk of frailty, and could predict its progression. Seven studies analyzed the association between RDW and frailty, and five of them showed that elevated RDW was independently associated with increased risk of frailty, and could predict its progression. Conclusion Some studies have shown that the risk of frailty increased with the elevation of NLR or RDW in different populations, and its progression could be predicted by NLR or RDW. As potential biomarkers of frailty, NLR and RDW could provide evidence for the pathogenesis of frailty, and a new theoretical basis for the development or improvement of frailty assessment tools. However, the optimal cut-off value of both for predicting frailty in different age groups and sex groups needs to be studied further.
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 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 | 0.016 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".