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Record W2925126723 · doi:10.1016/j.ekir.2019.03.004

Clinical Value of Complement Activation Biomarkers in Overt Diabetic Nephropathy

2019· article· en· W2925126723 on OpenAlexafffund
Karyne Pelletier, Arnaud Bonnefoy, Hugo Chapdelaine, Vincent Pichette, Matthieu Lejars, François Madore, Soumeya Brachemi, Stéphan Troyanov

Bibliographic record

VenueKidney International Reports · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsCentre Hospitalier de l’Université de MontréalCentre Hospitalier Universitaire Sainte-JustineHôpital Maisonneuve-RosemontMontreal Clinical Research InstituteHôpital du Sacré-Cœur de Montréal
FundersFonds de Recherche du Québec - Santé
KeywordsMedicineProteinuriaRenal functionInternal medicineDiabetic nephropathyComplement systemGlomerulonephritisFactor HEndocrinologyUrinary systemLupus nephritisMembranous nephropathyImmunologyKidneyDiseaseImmune system

Abstract

fetched live from OpenAlex

BACKGROUND: Experimental studies support a role of complement activation in diabetic nephropathy (DN), yet few clinical correlates exist. We evaluated urinary levels of sC5b-9 membrane attack complex (MAC) in patients with overt DN, and examined its association with the glomerular filtration rate (GFR) decline, proteinuria, and inflammatory biomarkers. We explored different complement pathways and compared our findings to autoimmune glomerulonephritis. METHODS: = 63). RESULTS: = 0.03) between the level of proteinuria and urinary sC5b-9: in individuals with higher levels of urinary MAC, the relationship between proteinuria and the rate of renal function decline was more pronounced than in those with low urinary MAC. Finally, patients with DN had levels of urinary sC5b-9 comparable to autoimmune glomerulonephritis, when stratified by the level of proteinuria. CONCLUSION: Urinary MAC is present in patients with overt DN at levels comparable to autoimmune glomerulonephritis and correlates with the GFR decline, supporting that complement activation and its measurement are clinically relevant in DN.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.017
GPT teacher head0.312
Teacher spread0.296 · 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 teacher head, not a consensus.

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".

Quick stats

Citations31
Published2019
Admission routes2
Has abstractyes

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