Transcranial Doppler ultrasound blood flow velocity and pulsatility index as systemic indicators for Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Multiple lines of evidence suggest that cardiovascular co-morbidities hasten the onset of Alzheimer's disease (AD) or accelerate its course. METHODS: To evaluate the utility of cerebral vascular physical function and/or condition parameters as potential systemic indicators of AD, transcranial Doppler (TCD) ultrasound was used to assess cerebral blood flow and vascular resistance of the 16 arterial segments comprising the circle of Willis and its major tributaries. RESULTS: Our study showed that decreased arterial mean flow velocity and increased pulsatility index are associated with a clinical diagnosis of presumptive AD. Cerebral blood flow impairment shown by these parameters reflects the global hemodynamic and structural consequences of a multifaceted disease process yielding diffuse congestive microvascular pathology, increased arterial rigidity, and decreased arterial compliance, combined with putative age-associated cardiovascular output declines. CONCLUSIONS: TCD evaluation offers direct physical confirmation of brain perfusion impairment and might ultimately provide a convenient and a noninvasive means to assess the efficacy of medical interventions on cerebral blood flow or reveal incipient AD. In the near term, TCD-based direct assessments of brain perfusion might offer the prospect of preventing or mitigating AD simply by revealing patients who would benefit from interventions to improve circulatory system function.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".