Abstract P-539: ALBUMIN VS CRYSTALLOIDS FOR FLUID RESUSCITATION IN CHILDREN AFTER CARDIAC SURGERY
Bibliographic record
Abstract
Aims & Objectives: To determine the benefit of using colloids vs. crystalloids for volume resuscitation in children after cardiac surgery. Methods Design: Retrospective cohort study. Patients: Children admitted to the Stollery Children’s Hospital pediatric cardiac intensive care unit (PCICU) after cardiac surgery. Intervention: Fluid resuscitation policy change in which crystalloids replaced albumin 5% as the main fluid used for resuscitation after cardiac surgery. Results We compared children having surgery 6 months prior to the policy change (5% albumin group, AG) vs children admitted 6 months after (crystalloid group, CG).Demographic,peri-operative and the following outcome variables (fluid intake day 1 to 4 post-operative,vasoactive therapy,blood products,time to negative fluid balance,dialysis, mechanical ventilation,PCICU and hospital stay) were collected.Data was analysed using multivariate analysis.366 children were included in the study.There was no association between fluid group and fluid intake (ml/kg) on day 1 post-operative (Coef. 2.84; 95%CI -5.37, 11.05; p-value=0.497).However,CG was associated with significantly less fluid intake on day 2 (Coef. -14.9; 95%CI -24.3, -5.57; p-value=0.002) and on the first 48 hours post-operative (Coef. 3.99; 95%CI -27.6, -1.29; p-value=0.032).Mechanical ventilation days (Coef. -1.21; 95%CI -2.19, -0.05; p-value=0.040) and PCICU stay (Coef. -1.29; 95%CI -2.50, -0.08; p-value=0.036) were shorter for the CG,with no significant differences in other outcomes. Conclusions The use of colloids for resuscitation after cardiac surgery was not associated with less fluid intake but rather the opposite. Colloid administration may not provide any clinical benefit after cardiac surgery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".