Influence of Stroke Localization on Autonomic Activation, Immunodepression, and Post-Stroke Infection
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Experimental and clinical data suggest that overactivation of the sympathetic nerve system (SNS) is an essential mediator of stroke-induced immunodepression, which in turn increases susceptibility to post-stroke infections. In a post hoc analysis of the PANTHERIS (Preventive Antibacterial Treatment in Acute Stroke) trial, we investigated the impact of distinct lesion patterns on SNS activation, immunodepression, and frequency of post-stroke infections. METHODS: Stroke volume, stress hormone levels, and immune function were determined on day 1 after stroke onset. Stroke localization was graded using the Alberta Stroke Programme Early CT score (ASPECTS). In univariate analysis, we investigated the impact of clinical (National Institutes of Health Stroke Scale, NIHSS) and imaging stroke characteristics (lesion volume, lateralization, localization grading) on autonomous nervous system activity (norepinephrine, cortisol), immune competence (monocytic HLA-DR expression), and the frequency of post-stroke infections. In a logistic regression model, we tested for independent factors that might increase susceptibility to post-stroke infections. RESULTS: In a single-factor analysis, large stroke volume, lesions affecting distinct regions of the MCA cortex, and SNS activation (elevated norepinephrine levels) were associated with an impaired immune function (reduced mHLA-DR expression) and a higher susceptibility to post-stroke infections. Multivariate analysis identified increased levels of norepinephrine and infarction of the anterior MCA cortex as independent risk factors of post-stroke infections. Neither stroke severity nor stroke volume was independently associated with post-stroke infections. CONCLUSIONS: Apart from sympathetic activation, our data suggest that ischemic lesion in the anterior MCA cortex may be a major determinant of stroke-associated infection. This finding has to be confirmed in larger prospective studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".