What recording duration is required to provide physiologically valid and reliable dynamic cerebral autoregulation transfer functional analysis estimates?
Bibliographic record
Abstract
Abstract Objective. Currently, a recording of 300 s is recommended to obtain accurate dynamic cerebral autoregulation estimates using transfer function analysis (TFA). Therefore, this investigation sought to explore the concurrent validity and the within- and between-day reliability of TFA estimates derived from shorter recording durations from squat-stand maneuvers.Approach. Retrospective analyses were performed on 70 young, recreationally active or endurance-trained participants (17 females; age: 26 ± 5 years, [range: 20–39 years]; body mass index: 24 ± 3 kg m−2). Participants performed 300 s of squat-stands at frequencies of 0.05 and 0.10 Hz, where shorter recordings of 60, 120, 180, and 240 s were extracted. Continuous transcranial Doppler ultrasound recordings were taken within the middle and posterior cerebral arteries. Coherence, phase, gain, and normalized gain metrics were derived. Bland–Altman plots with 95% limits of agreement (LOA), repeated measures ANOVA’s, two-tailed paired t-tests, coefficient of variation, Cronbach’s alpha, intraclass correlation coefficients, and linear regressions were conducted.Main results. When examining the concurrent validity across different recording durations, group differences were noted within coherence (F(4155) > 11.6,p < 0.001) but not phase (F(4155) < 0.27,p > 0.611), gain (F(4155) < 0.61,p > 0.440), or normalized gain (F(4155) < 0.85,p > 0.359) parameters. The Bland–Altman 95% LOA measuring the concurrent validity, trended to narrow as recording duration increased (60 s: < ±0.4, 120 s: < ±0.3, 180 s < ±0.3, 240 s: < ±0.1). The validity of the 180 and 240 s recordings further increased when physiological covariates were included within regression models.Significance. Future studies examining autoregulation should seek to have participants perform 300 s of squat-stand maneuvers. However, valid and reliable TFA estimates can be drawn from 240 s or 180 s recordings if physiological covariates are controlled.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".