Human respiratory muscle blood flow measured by near-infrared spectroscopy and indocyanine green
Bibliographic record
Abstract
Measurement of respiratory muscle blood flow (RMBF) in humans has important implications for understanding patterns of blood flow distribution during exercise in healthy individuals and those with chronic disease. Previous studies examining RMBF in humans have required invasive methods on anesthetized subjects. To assess RMBF in awake subjects, we applied an indicator-dilution method using near-infrared spectroscopy (NIRS) and the light-absorbing tracer indocyanine green dye (ICG). NIRS optodes were placed on the left seventh intercostal space at the apposition of the costal diaphragm and on an inactive control muscle (vastus lateralis). The primary respiratory muscles within view of the NIRS optodes include the internal and external intercostals. Intravenous bolus injection of ICG allowed for cardiac output (by the conventional dye-dilution method with arterial sampling), RMBF, and vastus lateralis blood flow to be quantified simultaneously. Esophageal and gastric pressures were also measured to calculate the work of breathing and transdiaphragmatic pressure. Measurements were obtained in five conscious humans during both resting breathing and three separate 5-min bouts of constant isocapnic hyperpnea at 27.1 +/- 3.2, 56.0 +/- 6.1, and 75.9 +/- 5.7% of maximum minute ventilation as determined on a previous maximal exercise test. RMBF progressively increased (9.9 +/- 0.6, 14.8 +/- 2.7, 29.9 +/- 5.8, and 50.1 +/- 12.5 ml 100 ml(-1) min(-1), respectively) with increasing levels of ventilation while blood flow to the inactive control muscle remained constant (10.4 +/- 1.4, 8.7 +/- 0.7, 12.9 +/- 1.7, and 12.2 +/- 1.8 ml 100 ml(-1) min(-1), respectively). As ventilation rose, RMBF was closely and significantly correlated with 1) cardiac output (r = 0.994, P = 0.006), 2) the work of breathing (r = 0.995, P = 0.005), and 3) transdiaphragmatic pressure (r = 0.998, P = 0.002). These data suggest that the NIRS-ICG technique provides a feasible and sensitive index of RMBF at different levels of ventilation in humans.
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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) | 0.001 | 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".