Reproducibility of near-infrared spectroscopy parameters measured during brachial artery occlusion and reactive hyperemia in healthy men
Bibliographic record
Abstract
Near-infrared spectroscopy (NIRS) is a noninvasive technique evaluating microvascular function. The aim of this study was to assess the reproducibility of NIRS parameters during reactive hyperemia induced by a 5 min brachial artery occlusion. Twenty-four healthy young males (mean 34 ± 8 years old) had two microvascular function evaluations by NIRS over a 7 to 30-day period (mean 16 ± 10 days). Intra-subject and inter-observer reproducibility were evaluated with intraclass correlation coefficient (ICC), coefficient of variation (CV), and standard error of measurement (SEM%) for every parameter. Mean NIRS parameters did not differ between both evaluations. Reproducibility was greatest for muscle oxygen consumption (ICC: 0.84; CV: 6.51%; SEM: 7.11%), time to basal O(2)Hb (ICC: 0.63, CV: 20.04%, SEM 27.22%), time to maximal O(2)Hb (ICC: 0.71; CV: 15.61%; SEM: 19.27%), peak of O(2)Hb (ICC: 0.63, CV: 6.68%, SEM 8.53%), time to maximal tHb (ICC: 0.73, CV: 19,61%, SEM 24.56%) and area under the O(2)Hb and tHb curves (ICC: 0.68, CV: 16.15%, SEM 22.93% and ICC: 0.62, CV: 18.59%, SEM 26.64%, respectively). Moreover, inter-observer reproducibility ranged from excellent to perfect (ICC from 0.85 to 1.00) for every parameter. NIRS parameters during reactive hyperemia are highly reproducible which enables their repeated measurement to study microvascular function in healthy subjects.
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 | 0.003 | 0.007 |
| 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 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".