<scp>N95</scp> masks increase brain blood velocity and parasympathetic outflow, yet worsen orthostatic symptoms in a healthy cohort
Bibliographic record
Abstract
Abstract Mask wearing became commonplace in everyday life during the COVID‐19 pandemic and masks are frequently used in certain professions. Masks can increase end‐tidal CO2 and the cerebrovasculature is known to vasodilate in response to hypercapnia. Orthostatic intolerance (OI) is the inability to tolerate postural transitions due to the displacement of blood volume away from the cerebral circulation, and we hypothesized that wearing a mask would improve OI symptoms by increasing brain blood flow. Young, healthy participants (n = 27) completed 10 min of 70° head‐up tilt while wearing/not wearing an N95 mask (randomized), while hemodynamics and blood velocity within the middle cerebral artery (MCAv) were measured. Systolic, diastolic, and mean blood pressure and mean and diastolic MCAv decreased during tilt in both conditions (all p < 0.05; Table 1). Systolic MCAV was elevated while wearing a mask (p < 0.05). Some OI symptoms were exacerbated during the mask trial (all p < 0.05) including the overall OI score (p = 0.002; Table 2). There appears to be a disconnect between the physiological response to mask wearing and OI symptoms, potentially indicating that there is a psychological component to mask wearing. While we have provided evidence that masking increases brain blood flow, the psychological effects may outweigh potential benefits to the cerebral circulation.
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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 | 0.000 |
| 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) | 0.004 | 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".