Comparison of Cardiac Output Using Two Different Methods during Semi-Supine Exercise Echocardiography
Bibliographic record
Abstract
PURPOSE: Accurate measurement of cardiac output (CO) is important in the assessment of children with congenital and acquired heart disease. Using echocardiography CO can be determined by the product of heart rate (HR), the pulsed Doppler velocity time integral (VTI) and aortic cross-sectional area (AoCSA) or m-mode left ventricular dimensions during systole and diastole (LVED and LVES, respectively) and HR. Our aim was to compare these two methods of calculating CO at rest, during, and immediately post- exercise. METHODS: We retrospectively reviewed our stress echocardiography database from 1997-2010. Our protocol includes M-mode and 2-D imaging and pulsed Doppler. CO was calculated as: (1) VTI Method: CO=VTI × AoCSA × HR or (2) Cubed (D3) Method: CO= (LVED)3-(LVES)3 × HR. Cardiac index (CI) was derived by indexing CO to body surface area. CI was compared at rest, peak, and immediately post exercise between healthy controls (CON) and several patient groups including: repaired congenital heart disease (CHD), oncology (ONC), eating disorders (ED), and transplant (TX) patients. A repeated measures ANOVA was performed. P<0.05 was considered statistically significant. RESULTS: Calculation of CI using the VTI method yielded significantly lower values compared to the D3 method at both rest and peak exercise (p<0.001).TableCONCLUSION: We have shown that the CI calculated using the VTI method yields a lower value than the D3 Method.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".