Strategies to improve respiratory chemoreflex characterization by Duffin's rebreathing
Bibliographic record
Abstract
New Findings What is the central question of this study? We assessed the test–retest variability of respiratory chemoreflex characterization by Duffin's modified rebreathing method and explored whether signal averaging of repeated trials improves confidence in parameter estimation. What is the main finding and its importance? Modified rebreathing is a reproducible method to characterize responses of central and peripheral respiratory chemoreflexes. Signal averaging of multiple repeated tests minimizes within‐ and between‐test variability, improves the confidence of chemoreflex characterization and reduces the minimal change in parameters required to establish an effect. Future experiments that apply this method might benefit from signal averaging to improve its discriminatory effect. Abstract We assessed the test–retest variability of central and peripheral respiratory chemoreflex characterization by Duffin's modified rebreathing method and explored whether signal averaging of repeated trials improves confidence in parameter estimation. Over four laboratory visits, 13 participants (mean ± SD age, 25 ± 5 years) performed six repetitions of modified rebreathing in isoxic–hypoxic conditions [end‐tidal () = 50 mmHg] and isoxic–hyperoxic conditions ( = 150 mmHg). End‐tidal (), and minute ventilation ( E ) were measured breath‐by‐breath, by gas analyser and pneumotachograph. The E versus relationships were fitted with a piecewise model to estimate the ventilatory recruitment threshold (VRT) and the slope above the VRT ( E S). Breath‐by‐breath data from the three within‐ and between‐day trials were averaged using two approaches [simple average (fit then average) and ensemble average (average then fit)] and compared with a single‐trial fit. Variability was assessed by intraclass correlation (ICC) and coefficient of variance (CV), and the minimal detectable change was computed for each approach using two independent sets of three trials. Within days, the VRT and E S exhibited excellent test–retest variability in both hyperoxic conditions (VRT: ICC = 0.965, CV = 2.3%; E S: ICC = 0.932, CV = 15.5%) and hypoxic conditions (VRT: ICC = 0.970, CV = 2.9%; E S: ICC = 0.891, CV = 17.2%). Between‐day reproducibility was also excellent (hyperoxia, VRT: ICC = 0.930, CV = 2.2%; E S: ICC = 0.918, CV = 14.2%; and hypoxia, VRT: ICC = 0.940, CV = 3.0%; E S: ICC = 0.880, CV = 18.1%). Compared with a single‐trial fit, there were no differences in VRT or E S using the simple average or ensemble average approaches; however, ensemble averaging reduced the minimal detectable change for E S from 2.95 to 1.39 L min −1 mmHg −1 (hyperoxia) and from 3.64 to 1.82 L min −1 mmHg −1 (hypoxia). Single trials of modified rebreathing are reproducible; however, signal averaging of repeated trials improves confidence in parameter estimation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".