Association of Serum Bilirubin with Stroke Severity and Clinical Outcomes
Bibliographic record
Abstract
OBJECTIVE: The aim of the study is to explore the association of serum bilirubin levels with admission severity and short term clinical outcomes among acute ischemic stroke patients. METHODS: Data were collected from 2361 acute ischemic stroke patients in four hospitals of Shangdong Province during January 2006 and December 2008. National Institutes of Health Stroke Scale (NIHSS) was used to assess admission and discharge severity. NIHSS≥10 at discharge or in-hospital death was defined as short-term clinical outcomes. Logistic regression and trend test were used to examine the association of serum bilirubin levels with admission severity and short term clinical outcomes. RESULTS: Serum bilirubin levels were significantly and positively associated with admission severity (P for trend <0.05). The age-sex adjusted odds ratios (95% confidential intervals) of NIHSS≥10 associated with the second, third and fourth quartile of total bilirubin/direct bilirubin were 1.245 (0.873, 1.777)/1.276 (0.895, 1.818), 1.484 (1.048, 2.102)/1.628 (1.158, 2.289) and 2.869 (2.076, 3.966)/2.765 (1.996, 3.828), respectively, compared with the lowest quartile; the multivariate adjusted odds ratios of NIHSS≥10 associated with the second, third and fourth quartile of total bilirubin/direct bilirubin were 1.088(0.711, 1.665)/1.436(0.94, 2.193), 1.328(0.877, 2.011)/1.647(1.092, 2.485) and 2.336(1.579, 3.458)/3.079 (2.049, 4.623), respectively, compared with the lowest quartile. However, no association between serum bilirubin levels and short-term clinical outcomes was observed in our study. CONCLUSION: Serum bilirubin levels were associated with initial stroke severity closely. Nevertheless, there is no significant relationship between serum bilirubin levels and short-term clinical outcomes among acute ischemic stroke patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".