Comparison of Spot Urine Protein to Creatinine Ratio to 24-Hour Proteinuria to Identify Important Change Over Time in Proteinuria in Lupus
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to determine whether spot urine protein-to-creatinine ratio (PCR) accurately measures the change in proteinuria compared with 24-hour proteinuria (24H-P). METHODS: This was a retrospective analysis on patients' paired visits and paired urine samples for PCR and 24H-P. Patients with both abnormal 24H-P (>0.5 g/d) and PCR (>0.05 g/mmol) or both normal 24H-P (≤0.5 g/d) and PCR (≤0.05 g/mmol) at baseline visit were identified.The first follow-up visit with partial recovery (50% decrease in proteinuria) or complete recovery (≤0.5 g/d) was identified for those with abnormal baseline 24H-P, and new proteinuria (>0.5 g/d) was identified for those with normal 24H-P. Twenty-four-hour urine collection and PCR end-point frequencies were compared. Twenty-four-hour urine collection results were converted to 24H-PCR. Twenty-four-hour PCR and PCR were utilized to measure the magnitude of change (by standardized response mean [SRM]) in patients who achieved the end points. RESULTS: Of 230 patients, at baseline, 95 patients had abnormal and 109 had normal 24H-P and PCR. On follow-up, 57 achieved partial recovery, and 53 achieved complete recovery by 24H-P. Standardized response mean was -1.03 and -1.10 for 24H-PCR and PCR, respectively. By PCR, 53 patients had partial recovery, and 27 had complete recovery. Standardized response mean was -1.25 and -0.86 by 24H-PCR and PCR, respectively.For new proteinuria, 28 patients were identified by 24H-P and 21 by PCR. Twenty-four-hour PCR SRM was 0.80, and PCR SRM was 0.68. CONCLUSIONS: Protein-to-creatinine ratio does not have sufficient accuracy compared with 24H-P for improvement and worsening to be used in lieu of 24H-P.
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How this classification was reachedexpand
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".