#2617 Impact of CKD screening in high‑risk populations and guideline-directed therapy on RRT, CV events, and mortality in Europe: an IMPACT CKD analysis
Notice bibliographique
Résumé
Abstract Background and Aims Despite the rising and substantial burden of chronic kidney disease (CKD), there is a lack of recognition of CKD as a health priority in Europe. This contributes to underdiagnosis of CKD despite the potential for early detection and effective intervention to delay progression to late-stages (associated with costly and resource-intensive renal replacement therapy [RRT; i.e., dialysis and transplantation]). Further, diagnosed patients are undertreated when compared to current and upcoming CKD guidelines, leading to increased risk for progression to RRT and cardiovascular (CV) or other events. Early detection and intervention in high-risk populations, such as those with diabetes mellitus (DM) and hypertension (HTN) have shown cost-effectiveness; however, the broader implications of these strategies on CKD progression and clinical outcomes in a European context remains underexplored. Our study aims to illustrate the clinical benefit of targeted screening followed by an optimal compliance to guideline-directed treatment use to provide insight into potential CKD policies across Europe. Method Four country populations (Germany, Netherlands, Spain, United Kingdom [UK]) were simulated for 10-years (baseline: 2022; simulated years: 2023-2032) using the validated IMPACT CKD model to compare two scenarios: targeted screening for people with DM and/or HTN followed by 90% compliance to guideline-directed therapy versus current practice (i.e., underdiagnosis without screening and low treatment rates). Annual targeted screening was modelled using estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (UACR) testing. Initiation of therapies for people with diagnosed CKD was based on Kidney Disease Improving Global Outcomes guidelines. A 90% compliance to guideline-directed therapies was assumed to approximate maximum clinical benefit. Current practice was modelled based on the observed diagnosed rate without screening and the observed treatment rate in each country. The incremental population initiated on recommended therapies were modelled to experience a multiplicative treatment effect on GFR decline, CV events, and acute kidney injury (AKI) events. The model projected CKD and RRT prevalence, incidence of CV and AKI events with results shown for year 10 (2032), as well as cumulative all-cause mortality over the simulated 10-years. Results Results compare the high-risk population screening followed by guideline-directed treatment scenario to continuation of current practices for the four countries (Fig. 1). The identification of undiagnosed CKD, as well as lower rates of progression due to guideline-directed treatment was associated with a small rise in the number of total CKD patients, with increases in stage 1-2 by 3.5% to 5.0%, and stage 3-5 by 0.2% to 1.2%. There was a reduction in the number of undiagnosed CKD stage 1-2 patients by 49.2% to 71.6%, and stage 3-5 by 60.2% to 69.8%. The largest reductions were predicted for CV events (44.6% to 49.1%) followed by dialysis (22.6% to 41.9%). The strategy resulted in a decrease in cumulative 10-year all-cause mortality between 4.5% to 9.1% in CKD patients. Conclusion The study predicted significant clinical benefits from targeted CKD screening followed by guideline-directed interventions across all four European countries. Notably, this approach was forecasted to reduce undiagnosed CKD cases, dialysis, CV events, and mortality. These findings underscore the potential of acting earlier on CKD to mitigate the future CKD burden.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».