Impaired cerebral autoregulation is associated with poststroke cognitive impairment
Bibliographic record
Abstract
OBJECTIVE: To investigate whether dynamic cerebral autoregulation (CA) and neuroimaging characteristics are determinants of poststroke cognitive impairment (PSCI). METHODS: Eighty patients within 7 days of acute ischemic stroke and 35 age- and sex-matched controls were enrolled. In the patients with stroke, brain magnetic resonance imaging and dynamic CA were obtained at baseline, and dynamic CA was followed up at 3 months and 1 year. Montreal Cognitive Assessment (MoCA) was performed at 3 months and 1 year. Patients with a MoCA score <23 at 1 year were defined as having PSCI, and those with a MoCA score that decreased by 2 points or more between the 3-month and 1-year assessments were defined as having progressive cognitive decline. RESULTS: In total, 65 patients completed the study and 16 developed PSCI. The patients with PSCI exhibited poorer results for all cognitive domains than did those without PSCI. The patients with PSCI also had poorer CA (lower phase shift between cerebral blood flow and blood pressure waveforms in the very low frequency band) compared with that of the patients without PSCI and controls at baseline and 1 year. CA was not different between the patients without PSCI and controls. In the multivariate analysis, low education level, lobar microbleeds, and impaired CA (very low frequency phase shift [≤46°] within 7 days of stroke), were independently associated with PSCI. In addition, impaired CA was associated with progressive cognitive decline. INTERPRETATION: Low education level, lobar microbleeds, and impaired CA are involved in the pathogenesis of PSCI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".