MO549INSIDE ANEMIA OF CKD: MICROSIMULATION MODELLING OF THE IMPACT OF POLICY INTERVENTIONS ON ANAEMIA OF CKD IN CANADA
Notice bibliographique
Résumé
Abstract Background and Aims Anaemia is common in patients with chronic kidney disease (CKD) and is associated with increased mortality, cardiovascular complications, reduced quality of life and increased use of healthcare resources. Based on robust epidemiological and clinical data, mathematical modelling is a useful approach for predicting the future burden of disease and the effects of different intervention scenarios, which is essential for health service planning. This analysis uses a microsimulation model, Inside ANEMIA of CKD, to project the impact of a hypothetical intervention scenario that reduces the prevalence of anaemia of CKD on related healthcare costs in Canada from 2020 to 2025. Method A virtual cohort representing the Canadian population was created within the Inside ANEMIA of CKD microsimulation model framework using national demographics and epidemiological data drawn from Statistics Canada and a provincial renal database. In the cohort, virtual individuals were ascribed an age- and sex-stratified CKD status (defined by estimated glomerular filtration rate and albuminuria levels, as per international guidelines) and anaemia status (defined as mild, moderate or severe based on haemoglobin level, as per WHO criteria) based on Canadian prevalence data. Key comorbidities (type 2 diabetes, heart failure and hypertension) were also assigned, reflecting Canada-specific population statistics. Costs related to the treatment of CKD were taken from the published literature, and are shown in Canadian dollars (C$). This modelling analysis evaluated the effects on healthcare costs of a hypothetical intervention scenario in which the prevalence of moderate and severe anaemia is reduced by 20% per year from 2020 to 2025 compared with no intervention (baseline). In each scenario (i.e. intervention or baseline), the modelling analysis estimated CKD-related healthcare costs for patients with moderate or severe anaemia of CKD. The modelling analysis did not adjust for the potential costs of the intervention. Results Preliminary results predict that, with the hypothetical intervention, there could be approximately 435,000 fewer patients with moderate or severe anaemia of CKD in Canada in 2025 compared with no intervention (approximately 497,000 versus 932,000). The intervention is projected to lead to a reduction of C$4.4 billion in annual direct healthcare costs in 2025 for patients with moderate or severe anaemia of CKD compared with no intervention (C$9.1 billion versus C$13.5 billion), assuming that all eligible patients are diagnosed and treated. Conclusion The Inside ANEMIA of CKD microsimulation model predicts that a hypothetical intervention which reduces the prevalence of moderate and severe anaemia of CKD would produce reductions in direct healthcare costs. This suggests that interventions effective at reducing the prevalence of anaemia of CKD would help to reduce the economic burden on healthcare services.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 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) | 0,003 | 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 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 ».