血清 C 反应蛋白和基底节区脑出血早期神经功能恶化的相关性分析
Bibliographic record
Abstract
Objective Clinical studies show that the level of C-reactive protein ( CRP ) markedly increases in the acute phase of cerebral hemorrhage .However , the correlation of the CRP level with early neurological deterioration ( END) in patients with basal ganglia hemorrhage remains unclear .This study investigated the correlation between CRP and END in basal ganglia hemorrhage . Methods This study included 142 cases of basal ganglia hemorrhage diagnosed by cranial CT between Jan 2010 and Dec 2012 .END was defined as any decrease in Canadian Stroke Scale ( CSS) score≥1 point in the first 48 hours after stroke onset .We compared the baseline data between the END and non-END patients and evaluated the correlation between CRP and END by logistic regression analy -sis. Results END was found in 31 (21.8%) of the 142 patients.Univariate analysis of the END versus non-END cases showed that hyperglycemia (29.03 vs 11.71%, P=0.018), neutrophil count ([11.8 ±1.2] vs [7.8 ±7.7] ×109/L, P=0.019), CRP (P=0.001), hematoma expansion (54.83 vs 19.81%, P=0.001), hematoma volume ([23.6 ±21.9] vs [14.8 ±12.7] mL, P=0.005), and intraventricular hemorrhage (68.75 vs 28.83%, P<0.001) were significantly associated with END .Logistic regression a-nalysis indicated that the CRP level (OR=1.072, 95%CI:1.034-1.112, P=0.001), intraventricular hemorrhage (OR=4.162, 95%CI: 1.498 -11.564, P =0.006), and hematoma expansion (OR=5.297, 95%CI:1.906-14.723, P=0.001) were correlated with END in the patients during their hospital stay .ROC analysis man-ifested the predictive value of the CRP level for END in basal ganglia hemorrhage (OR=0.812, 95%CI: 0.732 -0.891, P <0.001). Conclusion The elevated level of CRP is significantly correlated with END in patients with basal ganglia hemorrhage and therefore can be re-garded as a predictive factor for this condition .
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".