A multi-centre evaluation of the RIFLE criteria for early acute kidney injury in critically ill patients
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Bibliographic record
Abstract
BACKGROUND: The Acute Dialysis Quality Initiative Working Group recently developed the RIFLE criteria, a consensus definition for acute kidney injury (AKI). We sought to evaluate the RIFLE criteria on the day of ICU admission in a large heterogenous population of critically ill patients. METHODS: Retrospective interrogation of prospectively collected data from the Australian New Zealand Intensive Care Society Adult Patient Database. We evaluated 120 123 patients admitted for >/=24 h from 1 January 2000 to 31 December 2005 from 57 ICUs across Australia. RESULTS: The median (IQR) age was 64.3 (50.8-75.4) years, 59.5% were male, 28.6% had co-morbid disease, 50.3% were medical admissions and the initial mean (+/-SD) APACHEII score was 16.9 (+/-7.7). According to the RIFLE criteria, on the day of admission, AKI occurred in 36.1%, with a maximum RIFLE category of Risk in 16.3%, Injury in 13.6%, and Failure 6.3%. AKI, defined by any RIFLE category, was associated with an increase in hospital mortality (OR 3.29, 95% CI 3.19-3.41, P < 0.0001). The crude hospital mortality stratified by RIFLE category was 17.9% for Risk, 27.7% for Injury and 33.2% for Failure. By multivariable analysis, each RIFLE category was independently associated with hospital mortality (OR: Risk 1.58, Injury 2.54 and Failure 3.22). CONCLUSION: In a large heterogenous cohort of critically ill patients, the RIFLE criteria classified >36% with AKI on the day of admission. For successive increases in severity of RIFLE category, there were increases in hospital mortality. The RIFLE criteria represent a simple tool for the detection and classification of AKI and for correlation with clinical outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it