Low HALP (Hemoglobin, Albumin, Lymphocyte, and Platelet) Score Increases the Risk of Post-Stroke Cognitive Impairment: A Multicenter Cohort Study
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Bibliographic record
Abstract
Objective: The HALP (hemoglobin, albumin, lymphocyte, and platelet) score is a novel indicator that measures systemic inflammation and nutritional status that has not been correlated with the risk of post-stroke cognitive impairment in patients with acute ischemic stroke or transient ischemic attack (TIA). Methods: Study participants were recruited from 40 stroke centers in China. The HALP score was derived using a weighted sum of hemoglobin, albumin, lymphocytes and platelets, and study participants were categorized into 4 groups of equal sizes based on quartiles cutoffs of the HALP score. The Montreal Cognitive Assessment (MoCA)-Beijing Cognitive Assessment Scale (MoCA-Beijing) was performed at 2 weeks and 12 months following stroke onset. Post-stroke cognitive impairment was considered in patients with MoCA-Beijing≤22. Multiple logistic regression methods were employed to evaluate the relationship between the HALP score and the subsequent risk of developing post-stroke cognitive impairment. Results: The study population comprised 1022 patients (mean age 61.6±11.0 years, 73% men). The proportion of individuals with MoCA-Beijing≤22 at 2 weeks was 49.2% and 32.4% at one year. Patients in the lowest quartile of HALP score (<36.56) were observed to harbor the highest risk of post-stroke cognitive impairment at 12 months post-stroke/TIA compared to those in the highest quartile (odds ratio=1.59, 95% CI=1.07-2.37, p=0.022), and lower domain scores for executive function, naming, and attention. There were no statistically significant differences between patients in the different quartiles of HALP score and HALP score at 2 weeks post-stroke/TIA. Conclusion: The HALP score is a simple score that could stratify the risk of post-stroke cognitive impairment in stroke/TIA patients to facilitate early diagnosis and interventions.
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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 | 0.003 |
| 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 it