Early Prediction and Outcome of Septic Encephalopathy in Acute Stroke Patients With Nosocomial Coma
Bibliographic record
Abstract
BACKGROUND: Septic encephalopathy (SE) is the most common acute encephalopathy in ICU; however, little attention has been focused on risk of SE in the course of acute stroke. Our aim is to investigate the early prediction and outcome of SE in stroke patients with nosocomial coma (NC). METHODS: A retrospective cohort study was conducted in an ICU of the tertiary teaching hospital in China from January 2006 to December 2009. Ninety-four acute stroke patients with NC were grouped according to with or without SE. Risk factors for patients with SE were compared with those without SE by univariate and multivariate analysis. RESULTS: Of 94 stroke patients with NC, 46 (49%) had NC with SE and 48 (51%) had NC without SE. The onset-to-NC time was significant later in stroke patients with SE than those without SE (P < 0.01). There was a significant difference in body temperature, heart rate, respiratory rate, white blood cell (WBC), systolic blood pressure (SBP), diastolic blood pressure (DBP), systemic inflammatory response syndrome (SIRS), acute respiratory failure, septic shock, hypernatremia, and sequential organ failure assessment (SOFA) score between the SE and non-SE group (P < 0.05). On a repeat head imaging, vasogenic edema (P = 0.023) and subcortical white matter lesions (P = 0.011) were significantly higher in patients with SE than those without SE, while hematoma growth (P = 0.000), infarction progress (P = 0.003), and recurrent subarachnoid hemorrhage (SAH) (P = 0.011) were significantly lower in patients with SE than those without SE. Patients with SE had higher adjusted rates of fever ≥ 39 °C (odds ratio (OR): 2.753; 95% confidence interval (CI): 1.116 - 6.794; P = 0.028) and SIRS ≥ 3 items (OR: 6.459; 95% CI: 2.050 - 20.351; P = 0.001). The 30-day mortality in stroke patients with SE was higher than those without SE (76.1% vs. 45.8%, P = 0.003). CONCLUSION: High fever and severe SIRS are two early predictors of stroke patients with SE, and survival rates were worse in stroke patients with SE than those without SE.
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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 | 0.001 |
| 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".