Should we use diastolic function parameters to determine preload responsiveness in cardiac surgery? A pilot study
Bibliographic record
Abstract
BACKGROUND: Left ventricular (LV) diastolic function (DF) may play an important role in predicting fluid responsiveness. However, few studies assessed the role of diastolic function in predicting fluid responsiveness. The aim of this pilot study was to assess whether parameters of right and left diastolic function assessed with transesophageal echocardiography, including the mitral E/e' ratio, is associated with fluid responsiveness among patients undergoing elective bypass graft surgery. We also sought to compare other methods of fluid responsiveness assessment, including echocardiographic and hemodynamic parameters, pulse pressure variation, and stroke volume variation (SVV) (arterial pulse contour analysis, Flotrac/Vigileo system). RESULTS: We prospectively studied seventy patients undergoing coronary artery bypass grafting (CABG) monitored with a radial arterial catheter, transesophageal echocardiography (TEE), and a pulmonary artery catheter (for cardiac output measurements), before and after the administration of 500 mL of crystalloid over 10 min after the anesthetic induction. Thirteen patients were excluded (total of 57 patients). Fluid responsiveness was defined as an increase in cardiac index of ≥ 15%. There were 21 responders (36.8%) and 36 non-responders (63.2%). No difference in baseline pulsed wave Doppler echocardiographic measurements of any components of the mitral, tricuspid, and pulmonary and hepatic venous flows were found between responders and non-responders. There was no difference in MV tissue Doppler measurements between responders and non-responders, including E/e' ratio (8.7 ± 4.1 vs. 8.5 ± 2.8 in responders vs. non-responders, P = 0.85). SVV was the only independent variable to predict an increase in cardiac index by multivariate analysis (P = 0.0208, OR = 1.196, 95% CI (1.028-1.393)). CONCLUSIONS: In this pilot study, we found that no parameters of right and left ventricular diastolic function were associated with fluid responsiveness in patients undergoing CABG. SVV was the most useful parameter to predict fluid responsiveness. TRIAL REGISTRATION: ClinicalTrials.gov , NCT02714244 . Registered 21 March 2016-retrospectively registered.
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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".