Assessing cerebrovascular reactivity by the pattern of response to progressive hypercapnia
Bibliographic record
Abstract
Cerebral blood flow responds to a carbon dioxide challenge, and is often assessed as cerebrovascular reactivity, assuming a linear response over a limited stimulus range or a sigmoidal response over a wider range. However, these assumed response patterns may not necessarily apply to regions with pathophysiology. Deviations from sigmoidal responses are hypothesised to result from upstream flow limitations causing competition for blood flow between downstream regions, particularly with vasodilatory stimulation; flow is preferentially distributed to regions with more reactive vessels. Under these conditions, linear or sigmoidal fitting may not fairly describe the relationship between stimulus and flow. To assess the range of response patterns and their prevalence a survey of healthy control subjects and patients with cerebrovascular disease was conducted. We used a ramp carbon dioxide challenge from hypo- to hypercapnia as the stimulus, and magnetic resonance imaging to measure the flow responses. We categorized BOLD response patterns into four types based on the signs of their linear slopes in the hypo- and hypercapnic ranges, color coded and mapped them onto their respective anatomical scans. We suggest that these type maps complement maps of linear cerebrovascular reactivity by providing a better indication of the actual response patterns. Hum Brain Mapp 38:3415-3427, 2017. © 2017 Wiley Periodicals, Inc.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".