Classification of left ventricular size: diameter or volume with contrast echocardiography?
Bibliographic record
Abstract
BACKGROUND: Left ventricular (LV) size is an important clinical variable, commonly assessed at echocardiography by measurement of the internal diameter in diastole (IDD). However, this has recognised limitations and volumetric measurement from apical views is considered superior, particularly with the use of echocardiographic contrast. We sought to determine the agreement in classification of LV size by different measures in a large population of patients undergoing echocardiography. METHODS AND RESULTS: Data were analysed retrospectively from consecutive patients (n=2008, 61% male, median 62 years) who received echocardiographic contrast for LV opacification over 3 years in a single institution. Repeat studies were not included. LVIDD was measured, and LV end-diastolic volume (LVEDV) calculated using Simpson's biplane method. Both measures were indexed (i) to body surface area and categorised according to the American Society of Echocardiography (ASE) guidelines as normal, mild, moderate or severely dilated. Of 320 patients with a severely dilated LVEDVi, only 95 (30%) were similarly classified by LVIDD, with 86 patients (27%) measuring in the normal range. LVIDDi agreement was poorer, with only 43 patients (13%) classified as being severely dilated, and 173 (54%) measuring in the normal range. CONCLUSIONS: Currently recommended echocardiographic measures of LV size show limited agreement when classified according to currently recommended cut-offs. LV diameter should have a limited role in the assessment of LV size, particularly where a finding of LV dilation has important diagnostic or therapeutic implications.
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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".