Neutrophil to lymphocyte ratio and platelet to lymphocyte ratio as prognostic predictors for delirium in critically ill patients: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: In this systematic review and meta-analysis, we aim to analyze the current literature to evaluate neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) values among critically ill patients who develop delirium as compared to those who do not. METHODS: PubMed, Web of Science, and Scopus were used to conduct a systematic search for relevant publications published before June 12, 2022. The Newcastle-Ottawa scale was used for quality assessment. Because a significant level of heterogeneity was found, we used the random-effects model to generate pooled effects. RESULTS: Twenty-four studies including 11,579 critically ill patients, of whom 2439 were diagnosed with delirium, were included in our meta-analysis. Compared with the non-delirious group, the delirious group's NLR levels were significantly higher (WMD = 2.14; CI 95% = 1.48-2.80, p < 0.01). In the subgroup analysis according to the type of critical condition, the NLR levels in patients of delirious group were significantly more than those of non-delirious group in studies on POD, PSD and PCD (WMD = 1.14, CI 95% = 0.38-1.91, p < 0.01, WMD = 1.38, CI 95% = 1.04-1.72, p < 0.001, and WMD = 4.22, CI 95% = 3.47-4.98, p < 0.001, respectively). However, compared with the non-delirious group, the delirious group's PLR levels were not significantly different (WMD = 1.74; CI 95% = -12.39-15.86, p = 0.80). CONCLUSION: Our findings support NLR to be a promising biomarker that can be readily integrated into clinical settings to aid in the prediction and prevention of delirium.
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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 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".