SaO029THE BURDEN OF FRACTURES IN EARLY CHRONIC KIDNEY DISEASE: ANALYSIS OF CARTAGENE
Notice bibliographique
Résumé
INTRODUCTION: The association between ESRD and increased fracture risk is well known. Nevertheless, whether early CKD increases fracture risk is controversial, as most studies have focused on older adults and evaluated hip fracture only. Therefore, we aimed to evaluate the association between fracture incidence at any anatomical site and early CKD in middle-aged individuals. We also aimed to assess the effect of age and gender on this association and the role of CKD in fracture prediction. METHODS: Prospective analysis of CARTaGENE, a cohort of individuals from Quebec (Canada) aged 40 to 69 years recruited between 2009 and 2010. Individuals with eGFR above 30 ml/min/1,73m2are included. Early CKD is expressed continuously (eGFR levels using restricted cubic splines) or categorically (KDIGO Stages). Fracture incidence from recruitment to 2016 is identified using health administrative databases with validated algorithms. Associations between early CKD and fracture are assessed using Cox regression models adjusted for demographics, comorbidities, medication, bone mineral density, physical activity, and grip strength. The effect of age and sex on these associations is assessed using interaction terms. Predicted probabilities of fracture associated with early CKD and other traditional risk factors are computed for each gender at 45 and 65 years using previously built models. RESULTS: We included 19,391 individuals (51% women, mean age 54, mean eGFR 88 ml/min/1,73m2, 47% stage 2, 4% stage 3 CKD). 829 individuals had a fracture during the follow-up (380 non-CKD [4.0%], 400 CKD stage 2 [4.4%] and 49 CKD stage 3 [6.5%]). Decreased levels of eGFR and CKD stage 3 were associated with increased fracture incidence in unadjusted and adjusted models (Adjusted hazard ratio [HR] = 1.25 [1.05 to 1.49] for eGFR 60 vs 90 ml/min/1,73m2; HR = 1.65 [1.15 to 2.38] for eGFR 45 vs 90 ml/min/1,73m2; HR = 1.39 [1.02 to1.90] for CKD stage 3 vs non-CKD). eGFR levels of 75 to 120 ml/min/1,73m2 and CKD stage 2 were not associated with fractures. The cut-off for increased fracture risk was at 73 ml/min/1,73m2. Indeed, each 10 ml/min/1,73m2 reduction of eGFRwas linearly associated with fractures below but not above 73 ml/min/1,73m2 (HR = 1.22 [1.06 to 1.40] below; HR = 0.98 [0.92 to 1.05] above). CKD stage 3 was associated with increased fracture in younger individuals (HR=2.43 [1.27 to 4.64] at 45 years) but not in older individuals (HR= 1.11 [0.73 to 1.68] at 65 years; HR for interaction 0.68 [0.44 to 1.03]). Gender did not consistently modify the association between early CKD and fracture incidence. Predicted fracture probabilities for stage 3 CKD were greater than osteoporosis in younger but not in older individuals (6.6% for stage 3 CKD and 5.0% for osteoporosis at 45 years; 4.8% for stage 3 CKD and 8.6% for osteoporosis at 65 years). Compared to models including early CKD, models that excluded early CKD in fracture prediction had lower discrimination (p= 0.045) and underestimated fracture risk in individuals with stage 3 CKD (predicted/observed ratio of 0.77 without CKD and 1.00 to 1.04 with early CKD). CONCLUSIONS: In middle-aged adults, even early CKD is associated with increased fracture incidence, especially in younger individuals. Excluding early CKD in fracture prediction models resulted in lower discrimination and underestimation of fracture risk in individuals with CKD.
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».