Faculty Opinions recommendation of A systematic review of RIFLE criteria in children, and its application and association with measures of mortality and morbidity.
Bibliographic record
Abstract
The RIFLE criteria were developed to improve consistency in the assessment of acute kidney injury. The high face validity, collaborative development method, and validation against mortality have supported the widespread adoption of the RIFLE to evaluate adult patients; however, its inconsistent application in adult studies is associated with significant effects on the estimated incidence of acute kidney injury. As the RIFLE criteria are now being used to determine acute kidney injury in children, we conducted a systematic review to describe its application and assess associations between the RIFLE and measures of mortality and morbidity in pediatric patients. In 12 studies we found wide variation in the application of the RIFLE, including the range of assessed RIFLE categories, omission of urine output criteria, varying definitions of baseline renal function, and methods for handling missing baseline measurements. Limited and conflicting associations between the RIFLE and mortality, length of stay, illness severity, and measures of kidney function were found. Thus, although the RIFLE was developed to improve the consistency of defining acute kidney injury, there are still major discrepancies in its use in pediatric patients that may undermine its potential utility as a standardized measure of acute kidney injury in children. PMID: 22258324 Funding information This work was supported by: Canadian Institutes of Health Research, Canada
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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 | 0.053 | 0.232 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.009 | 0.004 |
| Insufficient payload (model declined to judge) | 0.057 | 0.009 |
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".