Differences in classification of left ventricular size measured by diameter and volume with contrast echocardiography
Bibliographic record
Abstract
Background: Left Ventricular (LV) size is commonly assessed at echocardiography by measurement of the End-Diastolic Diameter (EDD) in the parasternal long axis view. However, this has recognized limitations, and volumetric measurement from apical views is considered superior, particularly with the use of echocardiographic contrast to improve endocardial border definition. We sought to determine the agreement in classification of LV size by these different measures in a large population of patients undergoing clinically indicated echocardiography. Methods: Data were analyzed retrospectively from consecutive patients (n=2008, 61% male, age 62±13 years) who received echocardiographic contrast for LV opacification over 3 years in a single institution. Repeat studies were not included. LVEDD was measured, and LV End-Diastolic Volume (LVEDV) calculated using Simpson's biplane method. Both measures were indexed to body surface area (BSA) and categorized according to ASE guidelines as normal, mild, moderate or severely dilated. Results: There was a good overall correlation between LVEDD and LVEDV (Spearman's rho 0.74, p<0.001). However, when patients were categorized by indexed (i) LV diameter and volume there was poor agreement in classification (kappa = 0.200). Of 320 patients with severely dilated LVEDVi, only 43 were similarly classified by LVEDDi. Furthermore, 173 patients (54%) with a severely dilated LVEDVi had an LVEDDi in the normal range. Classification of LV size Conclusion: Agreement between different recommended measures of LV size is limited, even with significant LV dilation. The use of LVEDDi as the sole measure of ventricular size risks under-diagnosing or underestimating the degree of LV dilation. This has implications for reporting in circumstances where accurate assessment of LV size is important, such as timing of surgery in asymptomatic valve disease or classification of cardiomyopathy.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".