Altered Cerebral Vasoregulation Predicts the Outcome of Patients with Partial Anterior Circulation Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The aim of this study was to investigate the correlation between cerebral hemodynamic changes and the evolution of neurological deficit after stroke. METHODS: We included 65 patients with non-lacunar stroke admitted to a rehabilitation hospital within 4 weeks from the event. An evaluation of cerebrovascular reactivity to hypercapnia was performed with transcranial Doppler ultrasonography using the breath-holding index (BHI). Activities of daily living status was measured by the Barthel Index (BI) and impairment of mobility was assessed by means of the Rivermead Mobility Index (RMI). Multivariate analyses were performed using effectiveness of treatment, evaluated on BI and RMI as dependent variables. Independent variables were BHI values, age, sex, length of stay, hypertension, smoking habit, presence of aphasia and neglect, poststroke depression, and the degree of severity of stroke. RESULTS: The effectiveness on BI was associated positively with normal BHI values and with neurological severity at admission, measured by the Canadian Neurological Scale. The regression coefficients for effectiveness on RMI showed that the most relevant predictor was ipsilateral BHI (the slope resulted equal to 5.8), followed by age (a 10-year age difference is expected to diminish the effectiveness by about 4.3%) and by depression (depressed patients have almost 11% less effectiveness than non-depressed patients). CONCLUSION: These findings suggest that a satisfactory recovery from neurologic deficits requires a preserved cerebrovascular reactivity in the lesioned hemisphere despite the presence of an anatomic lesion.
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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 | 0.001 |
| 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) | 0.002 | 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".