Cardiac output by pulse contour analysis does not match the increase measured by rebreathing during human spaceflight
Bibliographic record
Abstract
Pulse contour analysis of the noninvasive finger arterial pressure waveform provides a convenient means to estimate cardiac output (Q̇). The method has been compared with standard methods under a range of conditions but never before during spaceflight. We compared pulse contour analysis with the Modelflow algorithm to estimates of Q̇ obtained by rebreathing during preflight baseline testing and during the final month of long-duration spaceflight in nine healthy male astronauts. By Modelflow analysis, stroke volume was greater in supine baseline than seated baseline or inflight. Heart rate was reduced in supine baseline so that there were no differences in Q̇ by Modelflow estimate between the supine (7.02 ± 1.31 l/min, means ± SD), seated (6.60 ± 1.95 l/min), or inflight (5.91 ± 1.15 l/min) conditions. In contrast, rebreathing estimates of Q̇ increased from seated baseline (4.76 ± 0.67 l/min) to inflight (7.00 ± 1.39 l/min, significant interaction effect of method and spaceflight, P < 0.001). Pulse contour analysis utilizes a three-element Windkessel model that incorporates parameters dependent on aortic pressure-area relationships that are assumed to represent the entire circulation. We propose that a large increase in vascular compliance in the splanchnic circulation invalidates the model under conditions of spaceflight. Future spaceflight research measuring cardiac function needs to consider this important limitation for assessing absolute values of Q̇ and stroke volume. NEW & NOTEWORTHY Noninvasive assessment of cardiac function during human spaceflight is an important tool to monitor astronaut health. This study demonstrated that pulse contour analysis of finger arterial blood pressure to estimate cardiac output failed to track the 46% increase measured by a rebreathing method. These results strongly suggest that alternative methods not dependent on pulse contour analysis are required to track cardiac function in spaceflight.
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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 | 0.004 |
| 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".