MétaCan
Menu
← Back to cohort

Abstract 13433: Predictors of Contrast Induced Nephropathy in Patients With Acute Coronary Syndromes and Normal Baseline Glomerular Filtration Rate

2020· article· en· W3163337494 on OpenAlexaffabout
Daniel Negreanu, Michaël Gagnon, Anh Thi Nguyen, Samer Mansour, Michel Nguyen, Martine Montigny, Claude Lauzon, Mark J. Eisenberg, Stéphane Rinfret, Simon Kouz, Marc Afilalo, Philippe L. L’Allier, Bernard De la Rocheliere, Bernard Cantin, Jean‐Claude Tardif, Thao Huynh

Bibliographic record

VenueCirculation · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecMontreal Heart InstituteCentre Intégré de Santé et de Services Sociaux des LaurentidesMcGill University Health CentreMcGill UniversityCentre intégré de santé et de services sociaux de Chaudière-AppalachesCegep de ThetfordCentre Hospitalier de l’Université de MontréalUniversity of TorontoUniversité de SherbrookeCegep regional de LanaudiereJewish General Hospital
Fundersnot available
KeywordsMedicineRenal functionCreatinineInternal medicineContrast-induced nephropathyDiabetes mellitusNephropathyCohortAcute coronary syndromeIncidence (geometry)CardiologyUrologyMyocardial infarctionGastroenterologyEndocrinology

Abstract

fetched live from OpenAlex

Background: The incidence and predictors of contrast-induced nephropathy (CIN) in patients with normal glomerular filtration rate (GFR) are not well ascertained. We aim to determine the incidence and predictors for CIN after coronary catheterization (CATH) for acute coronary syndromes (ACS). Methods: We combined the datasets of two studies. The AMI-QUEBEC was an observational cohort of patients with ST-segment elevation myocardial infarctions in 2003. The AMI-OPTIMA was a study of patients hospitalized with ACS in 2009 and 2012. For this analysis, we retained only patients with GFR > 60 ml/min who underwent CATH. We defined “hyperfiltrators” as patients with GFR above the 95th percentile age and sex-adjusted value. CIN was defined as an increase in serum creatinine >0.5 mg/dL (44.2 μmols/L) or > 50% from baseline serum creatinine. Results: There were 3,188 patients with GFR > 60 ml/min : 39 hyperfiltrators and 3,149 without hyperfiltration. The mean age was similar between the two groups of patients (62 years); 21% and 27% females in hyperfiltrators and non-hyperfiltrators (p<0.0001). The prevalences of diabetes mellitus and hypertension were 36% and 64%, respectively in hyperfiltrators compared to 20% and 46%, respectively in non-hyperfiltrators. The mean baseline GFR and creatinine were 112 ml/min and 50 μmols/L, respectively in hyperfiltrators; 84.2 ml/min and 80 μmols/L in non-hyperfiltrators. There were 225 CIN following CATH; 7.1% of the whole cohort with 35.9% in the hyperfiltrators and 6.7% in non-hyperfiltrators. Hyperfiltration was independently associated with a 13-fold increase in the risk of CIN (Table 1). Each year of increase in age was associated with a 5% increase in the risk of CIN. Shock was also associated with an 11-fold increase in the risk of CIN. Conclusion: Hyperfiltrators may be at high risk of CIN following CATH in ACS. The risk of CIN associated with hyperfiltration should be evaluated in other populations.

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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.217
Teacher spread0.206 · 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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCirculation→Same topicChronic Kidney Disease and Diabetes→French-language works237,207→