Urinary soluble CD163 and monocyte chemoattractant protein-1 in the identification of subtle renal flare in anti-neutrophil cytoplasmic antibody-associated vasculitis
Bibliographic record
Abstract
BACKGROUND: Prior work has shown that urinary soluble CD163 (usCD163) displays excellent biomarker characteristics for detection of active renal vasculitis using samples that included new diagnoses with highly active renal disease. This study focused on the use of usCD163 in the detection of the more clinically relevant state of mild renal flare and compared results of usCD163 testing directly to testing of urinary monocyte chemoattractant protein-1 (uMCP-1). METHODS: Patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV, n = 88) were identified within a serially sampled, longitudinal and multicentre cohort. Creatinine-normalized usCD163 and uMCP-1 levels were measured by enzyme-linked immunosorbent assay and, both alone and in combination, were compared between times of active renal AAV and during remission and/or active non-renal AAV. RESULTS: Samples from 320 study visits included times of active renal vasculitis (n = 39), remission (n = 233) and active extrarenal vasculitis (n = 48). Median creatinine levels were 0.9 mg/dL [interquartile range (IQR) 0.8-1.2] in remission and 1.4 mg/dL (IQR 1.0-1.8) during renal flare. usCD163 levels were higher in patients with active renal vasculitis compared with patients in remission and those with active extrarenal vasculitis, with median values of 162 ng/mmol (IQR 79-337), 44 (17-104) and 38 (7-76), respectively (P < 0.001). uMCP-1 levels were also higher in patients with active renal vasculitis compared with patients in remission and those with active extrarenal vasculitis, with median values of 10.6 pg/mmol (IQR 4.6-23.5), 4.1 (2.5-8.4) and 4.1 (1.9-6.8), respectively (P < 0.001). The proposed diagnostic cut-points for usCD163 and uMCP-1 were 72.9 ng/mmol and 10.0 pg/mmol, respectively. usCD163 and uMCP-1 levels were marginally correlated (r2 = 0.11, P < 0.001). Combining novel and existing biomarkers using recursive tree partitioning indicated that elevated usCD163 plus either elevated uMCP-1 or new/worse proteinuria improved the positive likelihood ratio (PLR) of active renal vasculitis to 19.2. CONCLUSION: A combination of usCD163 and uMCP-1 measurements appears to be useful in identifying the diagnosis of subtle renal vasculitis flare.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".