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036. USCD163 IS AN EARLY PREDICTOR OF TREATMENT RESPONSE IN CRESCENTIC GLOMERULONEPHRITIS

2019· article· en· W2928768835 on OpenAlexaff
Sarah Moran, Tze Liang Goh, Niall Conlon, Jean Dunne, Elizabeth Groarke, John Holian, Kirsty McLoughlin, Eamonn Molloy, Susan Murray, Jason Wyse, Mark A. Little

Bibliographic record

VenueLara D. Veeken · 2019
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersI.M. Sechenov First Moscow State Medical University
KeywordsMedicineGlomerulonephritisInternal medicineKidney

Abstract

fetched live from OpenAlex

Background: An unmet need exists in the personalized guidance of immunosuppressive therapy intensity. Urine sCD163 is a marker of glomerular crescent macrophage activation with prior work demonstrating increased usCD163 levels in renal ANCA-associated vasculitis (AAV) at diagnosis and flare. Methods: We prospectively enrolled patients with crescentic glomerulonephritis (CGN) undergoing cytotoxic induction therapy and obtained serial detailed clinical phenotypic information and urine samples. Those who did not undergo renal biopsy had met ACR or Chapel Hill Consensus Conference definition of AAV with clinical evidence of renal activity (increase in serum creatinine >30%, new/worse hematuria or proteinuria). usCD163 was measured by ELISA and results normalized to urine creatinine. Refractory disease was defined as per EULAR guidelines with lack of treatment response despite adequate immunosuppression and persistent positive BVAS score. Results: Urine samples and clinical data were obtained at 181 clinical encounters from 33 patients, of whom 25 (76%) had AAV, 6 (18%) had anti-glomerular basement membrane disease and 2 (6%) had other CGN. Mean eGFR at enrollment was 26.5mls/min (SD 18.2). Induction therapy comprised corticosteroids plus cyclophosphamide in 45%, rituximab in 27% and both cyclophosphamide and rituximab in 27%. Median usCD163 level was 1115ng/mmol (IQR 426.7-1804ng/mmol), 634.2ng/mmol (IQR 355.2-1365), 267.9ng/mmol (IQR 140.8-412.5) and 242ng/mmol (IQR 115.2-994.2) at diagnosis, one, three and six months respectively. In those subsequently diagnosed as having refractory disease the usCD163 value at one month was predictive of refractory disease with median usCD163 of 463.7ng/mmol (IQR 182.7- 592.4ng/mmol) and 2021ng/mmol (IQR 1499-2943ng/mmol) in treatment responsive and refractory patients respectively (p < 0.001). We derived an optimal cut off based on month one usCD163 values of greater than 1115ng/mmol, with sensitivity and specificity of 100%. usCD163 level was higher at the time of switch to maintenance therapy in those receiving rituximab induction compared to cyclophosphamide induction with median usCD163 values at time of switch of 382.7ng/mmol (IQR 168.2-889.7ng/mmol) and 142.2ng/mmol (IQR 77.6-243.9ng/mmol), respectively (p = 0.02). Conclusion: usCD163 may aid in the early identification of refractory disease. Disclosures: This work was supported by the Meath Foundation (grant 203170), Irish Health Research Board (grant HRA-POR-2015-1205 and NSAFP-2013-02), and Science Foundation Ireland (11/Y/B2093).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.012
GPT teacher head0.256
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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