Assessment of Left Ventricular Dimensions by Transoesophageal Echocardiography in Patients During Coronary Artery Bypass Surgery
Bibliographic record
Abstract
OBJECTIVE: Normative values of left ventricular (LV) end-diastolic area and diameter (EDA and EDD) for intraoperative transoesophageal echocardiography (TEE) have not been established. We aimed to define the ranges of LV EDA and EDD for intraoperative TEE examinations in patients undergoing coronary artery bypass graft (CABG) surgery. METHODS: A MEDLINE search for studies reporting LV EDA and EDD in CABG patients was performed. Individual-level dataset from 333 anaesthetised and mechanically ventilated patients with preserved LV function (study population) were received from 8 studies. EDA and calculated EDD values in the study population were compared with summary mean EDD values obtained by transthoracic echocardiography (TTE) in 2 studies of 500 awake patients with coronary artery disease (CAD). Further, the influence of prespecified factors on EDD was evaluated through a multivariate regression model. RESULTS: and 4.6±0.6 cm, respectively. EDD values measured by TEE in anaesthetised patients were 10% to 13% less those measured by TTE in 2 studies of awake patients (p<0.001). Body surface area, age and fractional area change but not sex were factors that affected LV EDD. CONCLUSION: LV EDD values measured by intraoperative TEE in anaesthetised and mechanically ventilated CABG patients were 10% to 13% less than those measured by TTE in awake CAD patients. This finding indicates that independent normative values specific for intraoperative TEE should be established for guiding intraoperative clinical decisions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".