Quantitative analysis of tissue oxygenation variability across anatomical landmarks in healthy individuals via near-infrared spectroscopy
Bibliographic record
Abstract
Near-infrared spectroscopy (NIRS) enables noninvasive assessment of tissue oxygenation, but its broader clinical application is hindered by the absence of standardized reference values across anatomical regions. This study aimed to characterize baseline regional tissue oxygen saturation (rSO2) across 17 anatomical landmarks in healthy adults and to identify the most consistent and reproducible measurement sites. Seventy-eight healthy participants (mean age 31 ± 13.4 years) underwent rSO2 assessments using a continuous-wave NIRS system. Demographic and physiological data, including age, sex, skin pigmentation, tissue thickness, and mean arterial pressure, were collected. rSO2 values ranged from 50.5 to 86.0%, with most values between 65 and 76%. The temporomandibular joint and mandibular ramus had the highest mean rSO2 (~ 75.8%), while the thenar eminence and forehead showed the lowest. The quadriceps exhibited the lowest inter-individual variability (2.72 SD), making it the most reliable site for baseline measurements. The sternum also showed low variability (2.96 SD), suggesting its usefulness in dynamic monitoring. Age and sex significantly influenced rSO2 (p < .001), while other variables had limited impact. These findings establish normative rSO2 values and identify optimal NIRS placement sites, supporting device-specific measurement in clinical and research applications to improve detection of tissue hypoxia and perfusion abnormalities.
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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 | 0.001 |
| 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) | 0.001 | 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".