Agreement of concomitant cardiac output measurement by thoracic bio‐impedance and inert gas rebreathing in healthy subjects
Bibliographic record
Abstract
PURPOSE: Inasmuch as they are deemed valid, noninvasive measurement of cardiac output techniques present advantages of ease and safety for use in humans. Few studies have compared the use of thoracic bioimpedance and inert gas rebreathing techniques for cardiac output (CO) assessment at rest and exercise. This manuscript reports on differences between Physioflow® and Innocor® CO measurements at rest and during cycling in a population of healthy subjects. METHODS: Fifty healthy subjects (52 ± 16 years) underwent an incremental cycle exercise testing (IET) during which standardized Physioflow® and Innocor® CO assessments were achieved. Measurements were completed in a subgroup of twelve subjects during two constant-load 10-min cycling bouts at moderate and high intensities. RESULTS: Mean difference between Physioflow® and Innocor® was of 0.002 ± 0.98 l/min at rest and 0.38 ± 1.31 l/min during IET without statistical difference. Correlation coefficient values were higher for exercise (r = 0.83) than resting (r = 0.40) measurements. Good reproducibility of the two devices was observed on different graded exercises with intraindividual variability lower than 6%, except for rest Innocor® CO measurements (CV = 18%). CONCLUSION: Physioflow® and Innocor® can be easily used concomitantly for noninvasive measurement of CO. Despite finding a strong agreement between techniques for exercise CO, results should not be interpreted as being interchangeable as values are derived from different flow measurements: systemic blood flow for Physioflow® and pulmonary blood flow for Innocor®. However, the concomitant use of both techniques could be of value in clinical setting for noninvasive intrathoracic shunt quantification.
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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".