Assessment of fluid responsiveness in children using respiratory variations in descending aortic flow
Bibliographic record
Abstract
BACKGROUND: The primary aim of the current study was to investigate the ability of respiratory variations in descending aortic flow, measured with two-dimensional echo at the suprasternal notch (ΔVpeak dAo), to predict fluid responsiveness in anesthetized mechanically ventilated children. In addition, variations in peak descending aortic flow measured with apical transthoracic echo (ΔVpeak LVOT) were examined for the same properties. METHODS: fluid bolus. Patients were classified as responders if stroke volume index increased by >15% after fluid bolus. The ability of each parameter to predict fluid responsiveness was assessed using receiver operating characteristic curves. RESULTS: Twenty-seven patients were analyzed, mean age and weight 43 months and 16 kg, respectively. Twelve responders and 15 non-responders were identified. ΔVpeak dAo was significantly higher in the responder group (14%, 95% confidence interval [CI]: 12%-17%) compared to the non-responder group (11%, 95% CI: 9%-13%) (p = .04) at baseline. Area under the ROC curve for ΔVpeak dAo and ΔVpeak LVOT was 0.73 (95% CI: 0.52-0.89, p = .02) and 0.56 (0.34-0.78, p = .3), respectively. A baseline level of ΔVpeak dAo of >14% predicted fluid responsiveness with a sensitivity of 58% (95% CI: 28%-85%) and specificity of 73% (95% CI: 45%-92%). CONCLUSION: In mechanically ventilated children, ΔVpeak dAo identified fluid responders with moderate diagnostic power in the current study. ΔVpeak LVOT failed to predict fluid responders in the current study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".