Cohort profile: Canadian study of prediction of death, dialysis and interim cardiovascular events (CanPREDDICT)
Notice bibliographique
Résumé
BACKGROUND: The Canadian Study of Prediction of Death, Dialysis and Interim Cardiovascular Events (CanPREDDICT) is a large, prospective, pan-Canadian, cohort study designed to improve our understanding of determinants of renal and cardiovascular (CV) disease progression in patients with chronic kidney disease (CKD). The primary objective is to clarify the associations between traditional and newer biomarkers in the prediction of specific renal and CV events, and of death in patients with CKD managed by nephrologists. This information could then be used to better understand biological variation in outcomes, to develop clinical prediction models and to inform enrolment into interventional studies which may lead to novel treatments. METHODS/DESIGNS: Commenced in 2008, 2546 patients have been enrolled with eGFR between 15 and 45 ml/min 1.73m2 from a representative sample in 25 rural, urban, academic and non academic centres across Canada. Patients are to be followed for an initial 3 years at 6 monthly intervals, and subsequently annually. Traditional biomarkers include eGFR, urine albumin creatinine ratio (uACR), hemoglobin (Hgb), phosphate and albumin. Newer biomarkers of interest were selected on the basis of biological relevance to important processes, commercial availability and assay reproducibility. They include asymmetric dimethylarginine (ADMA), N-terminal pro-brain natriuretic peptide (NT-pro-BNP), troponin I, cystatin C, high sensitivity C-reactive protein (hsCRP), interleukin-6 (IL6) and transforming growth factor beta 1 (TGFβ1). Blood and urine samples are collected at baseline, and every 6 monthly, and stored at -80°C. Outcomes of interest include renal replacement therapy, CV events and death, the latter two of which are adjudicated by an independent panel. DISCUSSION: The baseline distribution of newer biomarkers does not appear to track to markers of kidney function and therefore may offer some discriminatory value in predicting future outcomes. The granularity of the data presented at baseline may foster additional questions.The value of the cohort as a unique resource to understand outcomes of patients under the care of nephrologists in a single payer healthcare system cannot be overstated. Systematic collection of demographic, laboratory and event data should lead to new insights. The mean age of the cohort was 68 years, 90% were Caucasian, 62% were male, and 48% had diabetes. Forty percent of the cohort had eGFR between 30-45 mL/min/1.73m², 22% had eGFR values below 20 mL/min/1.73m²; 61% had uACR < 30. Serum albumin, hemoglobin, calcium and 25-hydroxyvitamin D (25(OH)D) levels were progressively lower in the lower eGFR strata, while parathyroid hormone (PTH) levels increased. Cystatin C, ADMA, NT-proBNP, hsCRP, troponin I and IL-6 were significantly higher in the lower GFR strata, whereas 25(OH)D and TGFβ1 values were lower at lower GFR. These distributions of each of the newer biomarkers by eGFR and uACR categories were variable.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».