Correlation between urine ACR and 24-h proteinuria in a real-world cohort of systemic AL amyloidosis patients
Bibliographic record
Abstract
A 24-h urine protein collection (24hUP), the gold standard for measuring albuminuria in systemic AL amyloidosis, is cumbersome and inaccurate. We retrospectively reviewed 575 patients with systemic AL amyloidosis to assess the correlation between a urine albumin to creatinine ratio (uACR) and the 24hUP. The uACR correlated strongly with 24hUP at diagnosis (Pearson's r = 0.87, 95% CI 0.83-0.90) and during the disease course (Pearson's r = 0.88, 95% CI 0.86-0.90). A uACR ≥300 mg/g estimated a 24hUP ≥ 500 mg with a sensitivity of 92% and specificity of 97% (area under the receiver operating curve = 0.938, 95% CI 0.919-0.957). A uACR cutoff of 3600 mg/g best predicted a 24hUP > 5000 g (sensitivity 93%, specificity 94%), and renal stage at diagnosis was strongly concordant using either 24hUP or uACR as the proteinuria measure (k = 0.823, 95% CI 0.728-0.919). In patients with serial urine collections, a > 30% decrease in uACR predicted a > 30% decrease in 24hUP with a sensitivity of 94%. In conclusion, the uACR is a reliable and convenient method for ruling out proteinuria >500 mg per day, prognosticating renal outcomes, and assessing renal response to therapy. Further studies are needed to validate the uACR cutoffs proposed in this study.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".