Role of the platelet-lymphocyte ratio as a prognostic indicator in patients with intracranial hemorrhage: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The prognostic value of platelet-lymphocyte ratio (PLR) in ischemic stroke had been investigated in previous studies. However, the results of studies on PLR in patients with intracranial hemorrhage (ICH) are inconsistent. We aimed to conduct a meta-analysis to determine the prognostic value of PLR in predicting functional outcome and mortality in patients with ICH. METHODS: We searched the databases of PubMed, Embase, the Cochrane Library, and CNKI for relevant studies up to 10th June 2024. The Newcastle Ottawa Quality Assessment Scale (NOS) was applied to evaluate the quality of the included studies. We calculated the pooled odds ratios (OR) with 95% confidence intervals (CI) between PLR and both functional outcome (as measured by the modified Rankin Scale, mRS) as well as mortality. Poor functional outcomes were defined as mRS > 2. RESULTS: A total of 6 studies with 2992 patients were included. The random effects meta-analysis demonstrated that elevated PLR exhibited an association with poor functional outcome in patients with ICH (OR = 1.69; 95% CI [1.39-2.07]; P<0.0001; I2 = 24%). Similarly, elevated PLR was associated with mortality in patients with ICH (OR = 1.65; 95% CI [1.12-2.43]; P = 0.01; I2 = 31%). CONCLUSION: This study suggested that elevated PLR was significantly associated with poor functional outcome (mRS>2) and increased mortality, indicating that elevated PLR could serve as a reliable a prognostic factor for unfavorable clinical outcomes in patients with ICH. It is advisable to conduct extensive prospective investigations across diverse ethnic backgrounds to verify the accuracy of this correlation prior to its utilization in clinical settings.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".