Erythropoietic agents, iron and hemoglobin—What happens beyond the trial setting: Observational data from the ANZDATA Registry
Notice bibliographique
Résumé
BACKGROUND: The issues surrounding anemia management in patients receiving dialysis therapy are complex and widely debated. Although numerous trials have been published, clinical practice patterns may differ, particularly in the presence of uncertainty about the optimal management of anemia in this setting. METHODS: We examined data from the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) regarding use of erythropoietic agents (EA), hemoglobin, and ferritin concentrations and transferrin saturation in 8476 prevalent dialysis patients in Australia and New Zealand during the 6 months preceding March 31, 2001. From this cross-sectional survey, we examined the distribution of reported hemoglobin concentration, transferrin saturation, and ferritin concentration. Among hemodialysis patients, other predictors of hemoglobin examined included urea reduction ratio (URR), age, sex, and the presence of comorbidities. RESULTS: In Australia, 87% of dialysis patients received an EA; in contrast, only 42% of New Zealand patients received an EA. Hemoglobin concentrations were significantly higher in Australia, where 16% of reported values were <100 g/L, compared to New Zealand where 37% reported values were <100 g/L. Transferrin saturation and serum ferritin concentrations were significantly correlated, but less strongly among those receiving EA than those not receiving these agents. Both transferrin saturation and serum ferritin were significantly and independently associated with hemoglobin concentration, as were age and sex. The association with ferritin was inverse: higher serum ferritin concentrations were associated with lower hemoglobin concentrations. There was poor agreement (kappa = 0.15) between categories of low transferrin saturation (<20%) and low ferritin concentrations (<200 ng/mL). Among the Australian hemodialysis patients, there was no significant variation in Hb between categories where reported URR was >/=65%, whereas the group with a reported URR <65% had a significantly lower hemoglobin concentration. CONCLUSIONS: There was a wide variation in reported hemoglobin concentrations in this population. Potential contributing factors include variable patient responsiveness to EA and iron, differing regulations in Australia and New Zealand regarding government subsidy of EA, and the lack of consensus among physicians regarding hemoglobin target values. Although a cross-sectional study cannot directly address the predictive value of iron indices for iron deficiency, it appears likely that transferrin and ferritin have different relationships with hemoglobin, and measurement of both may have greater clinical utility than either parameter alone.
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 | 0,094 | 0,274 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».