The role of red blood cell distribution width to platelet ratio in predicting hemorrhagic transformation after mechanical thrombectomy therapy in acute ischemic stroke patients
Bibliographic record
Abstract
Objective: Hemorrhagic transformation (HT) is common complication after mechanical thrombectory (MT) for acute ischemic stroke (AIS). To our knowledge, there has been no study on the correlation between baseline red blood cell distribution width (RDW) to platelet ratio (RPR) and HT after MT. Methods: This study recruited 126 AIS patients with anterior or posterior circulation large-vessel occlusion who underwent MT therapy at the Department of Neurology, Taizhou Hospital, Zhejiang province between September 2019 and April 2021. Patients were divided into two groups: patients with HT and those without HT (wHT), and their laboratory and clinical data were compared. Results: We found no significant differences in sex, age, alcohol consumption, diabetes mellitus, atrial fibrillation, systolic blood pressure, diastolic blood pressure, triglycerides, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, serum creatinine, blood urea nitrogen, fibrinogen, neutrophil count, lymphocyte count, neutrophil-to-lymphocyte ratio (NLR), National Institutes of Health Stroke Scale (NIHSS) score, Alberta Stroke Program Early Computed Tomography Score (ASPECTS), whether intravenous thrombolysis was accepted, and TOAST classification between the two groups. Compared with patients without HT, we found that the admission blood glucose, RDW and RPR levels were higher in patients with HT after MT in AIS patients, multivariate logistic regression analysis revealed that baseline RPR (odds ratio (OR), 1.290; 95% CI, 1.062–1.567; P=0.010) and glucose level (OR, 1.177; 95% CI, 1.013–1.369; P=0.034) are independent predictors for HT after MT. Conclusion: Higher baseline RPR and higher admission blood glucose levels might be related to HT in AIS patients who received MT therapy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".