Scaling Submaximal Exercise Cardiac Output and Stroke Volume: The HERITAGE Family Study
Bibliographic record
Abstract
This study investigated different methods of scaling submaximal cardiac output (Q) and stroke volume (SV) to best normalize for body size (body surface area [BSA], height [Ht], weight [Wt], and fat-free mass [FFM]). Q and SV were measured at both an absolute (50 W) and a relative power output (60 % of VO2max) in 337 men and 422 women, 17 to 65 years of age. Traditional ratio scaling was examined in addition to allometric scaling, where scaling exponents ( B) were determined for each body size variable (x) that best normalized the physiological outcome variables (y) for body size (y = ax(b)). With ratio scaling, regardless of the body size variable (x = BSA, Ht, Wt, FFM), there was no evidence of a linear relationship between x and y (y = Q or SV). A linear relationship is a necessary condition for appropriate normalization. Further, when ratio-scaled variables (e.g., Q/BSA) were correlated to the body size variable (e.g., BSA) by which they were scaled, significant (p <or= 0.05) relationships still existed for BSA, Ht, Wt, and FFM. Thus, ratio scaling did not meet either criteria for normalizing Q and SV for body size. In contrast, when allometrically-derived scaling exponents were used to normalize Q and SV (e.g., Q/BSA(b)), the resulting scaled values were uncorrelated (i.e., size-independent) with BSA, Ht, Wt, or FFM. These results were independent of age, sex or race. In summary, ratio scaling did not appropriately normalize Q and SV for differences in body size, while allometric scaling did result in size-independent values. Thus, individually-derived allometric exponents should be applied to body size variables to most appropriately adjust Q and SV for body size.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".