Reference Values for Indexed Echocardiographic Chamber Sizes in Older Adults: The Multi‐Ethnic Study of Atherosclerosis
Bibliographic record
Abstract
Background Normalization of echocardiographic chamber measurements for body surface area may result in misclassification of individuals with obesity or sarcopenia. Normalization for alternative measures of body size may be preferable, but there remains a dearth of information on their normative values and association with cardiovascular function metrics. Methods and Results A total of 3032 individuals underwent comprehensive 2‐dimensional echocardiography at Exam 6 in MESA (Multi‐Ethnic Study of Atherosclerosis). In the subgroup of 608 individuals free of cardiopulmonary disease (69.5±7.0 years, 46% male, 48% White, 17% Chinese, 15% Black, 21% Hispanic), normative values were derived for left and right cardiac chamber measurements across a variety of ratiometric (body surface area, body mass index, height) and allometric (height 1.6 , height 2.7 ) scaling parameters. Normative upper and lower reference values were provided for each scaling parameter stratified across age groups, sex, and race or ethnicity. Among scaling parameters, body surface area and height were associated with the least variability across race and ethnicity categories and height 2.7 was associated with the least variability across sex categories. Conclusions In this diverse cohort of community‐dwelling older adults, we provide normative values for common echocardiographic parameters across a variety of indexation methods.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".