Acute Kidney Injury, Fluid Overload, and Outcomes in Children Supported With Extracorporeal Membrane Oxygenation for a Respiratory Indication
Bibliographic record
Abstract
This study seeks to evaluate the association between acute kidney injury (AKI), fluid overload (FO), and mortality in children supported with extracorporeal membrane oxygenation (ECMO) for refractory respiratory failure. This retrospective observational cohort study was performed at six tertiary care children's hospital intensive care units, studying 424 patients < 18 years of age supported with ECMO for ≥ 24 hours for a respiratory indication from January 1, 2007, to December 31, 2011. In a multivariate analysis, FO level at ECMO initiation was not associated with hospital mortality, whereas peak FO level during ECMO was associated with hospital mortality. For every 10% increase in peak FO during ECMO, the odds of hospital mortality were approximately 1.2 times higher. Every 10% increase in peak FO during ECMO resulted in a significant relative change in the duration of ECMO hours by a factor of 1.08. For hospital survivors, every 10% increase in peak FO level during ECMO resulted in a significant relative change in the duration of mechanical ventilation hours by a factor of 1.13. In this patient population, AKI and FO are associated with increased mortality and should be considered targets for medical interventions including judicious fluid management, diuretic use, and renal replacement therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".