Diagnostic performance of serum blood urea nitrogen to creatinine ratio for distinguishing prerenal from intrinsic acute kidney injury in the emergency department
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The blood urea nitrogen to creatinine ratio (BCR) has been used since the early 1940s to help clinicians differentiate between prerenal acute kidney injury (PR AKI) and intrinsic AKI (I AKI). This ratio is simple to use and often put forward as a reliable diagnostic tool even though little scientific evidence supports this. The aim of this study was to determine whether BCR is a reliable tool for distinguishing PR AKI from I AKI. METHODS: We conducted a retrospective observational study over a 13 months period, in the Emergency Department (ED) of Nantes University Hospital. Eligible for inclusion were all adult patients consecutively admitted to the ED with a creatinine >133 μmol/L (1.5 mg/dL). RESULTS: Sixty thousand one hundred sixty patients were consecutively admitted to the ED. 2756 patients had plasma creatinine levels in excess of 133 μmol/L, 1653 were excluded, leaving 1103 patients for definitive inclusion. Mean age was 75.7 ± 14.8 years old, 498 (45%) patients had PR AKI and 605 (55%) I AKI. BCR was 90.55 ± 39.32 and 91.29 ± 39.79 in PR AKI and I AKI groups respectively. There was no statistical difference between mean BCR of the PR AKI and I AKI groups, p = 0.758. The area under the ROC curve was 0.5 indicating that BCR had no capacity to discriminate between PR AKI and I AKI. CONCLUSIONS: Our study is the largest to investigate the diagnostic performance of BCR. BCR is not a reliable parameter for distinguishing prerenal AKI from intrinsic AKI.
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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 | 0.001 | 0.008 |
| 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 | 0.001 | 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