What is the minimum change in left ventricular ejection fraction, which can be measured with contrast echocardiography?
Bibliographic record
Abstract
BACKGROUND: There are limited data on what is the minimum change that can be detected in cancer patients undergoing treatment with cardiotoxic drugs and are referred for monitoring left ventricular (LV) function. OBJECTIVE: To assess the variability in the measurement of LV volumes and ejection fraction (EF) in contrast echocardiography and to determine the minimum detectable difference (MDD) between two EF measurements that can be deemed significant. METHODS: A total of 150 patients were divided into three groups according to EF (EF <53, 53-60, and >60%). Each group consisted of 50 randomly selected cancer patients who underwent contrast echocardiography between July 2010 and May 2014. Repeated measurements of LV volumes and EF were performed offline by a sonographer and a cardiologist. Inter-observer variability was assessed by analysis of variance. Measurement error was estimated by standard error of measurement and MDD. RESULTS: The 95% confidence interval with a single measurement of EF was 2 percentage points in the groups of patients with EF <53% and EF >60%, and 2.5 percentage points for patients with EF 53-60%. The MDD for EF, end-diastolic volume and end-systolic volume that could be recognized with 95% confidence interval were 4 percentage points, 7 mL and 4 mL, respectively. CONCLUSION: Contrast echocardiography is a reliable tool for serial measurements of EF to monitor cardiotoxicity due to chemotherapy. In a high-volume echocardiography laboratory with experienced staff, the MDD for EF of 4 percentage points on a good-quality recording demonstrates the high reproducibility of the Simpson's method using contrast echocardiography.
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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 | 0.013 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".