Utility of Urine Myoglobin for the Prediction of Acute Renal Failure in Patients with Suspected Rhabdomyolysis: A Systematic Review
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Bibliographic record
Abstract
BACKGROUND: Urine myoglobin continues to be used as a marker of rhabdomyolysis, particularly to assess risk of developing acute renal failure and evaluate treatment success. We sought to determine the predictive validity of urine myoglobin (uMb) for acute renal failure (ARF) in patients with suspected rhabdomyolysis. METHODS: We performed a broad systemic review of the literature from January 1980 to December 2006 using the search terms myoglobin$ AND (renal OR ARF OR kidney). Only primary studies published in English where uMb measurement was related to ARF were included. RESULTS: Of 1602 studies screened, 52 met all selection criteria. The studies covered a wide spectrum of etiologies for rhabdomyolysis, dissimilar diagnostic criteria for ARF and rhabdomyolysis, and various methods of uMb measurement and were mostly case series (n = 32). There was poor reporting on the uMb method, and 17 studies failed to provide any information about the method. The reporting of clinical criteria for ARF with respect to timing, description, performance, and interpretation also lacked adequate detail for replication. Eight studies (total 295 patients) had data for 2-by-2 tables. Sensitivity of the uMb test was 100% in 5 of the 8 studies, specificity varied widely (15% to 88%), and CIs around these measures were high. Pooling of data was not possible because of study heterogeneity. CONCLUSIONS: There is inadequate evidence evaluating the use of uMb as a predictor of ARF in patients with suspected rhabdomyolysis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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