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首页> 外文期刊>Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association - European Renal Association >A predictive algorithm for the management of anaemia in haemodialysis patients based on ESA pharmacodynamics: Better results for less work
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A predictive algorithm for the management of anaemia in haemodialysis patients based on ESA pharmacodynamics: Better results for less work

机译:基于ESA药效学的血液透析患者贫血管理的预测算法:效果更好,工作量更少

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Background. Many anaemia management algorithms recommend changes to erythropoiesis-stimulating agent (ESA) doses based on frequent measurement of haemoglobin levels in keeping with the ESA datasheets. We designed a predictive anaemia algorithm based on ESA pharmacodynamics, which we hoped would improve compliance with haemoglobin targets and reduce workload. Methods. A new algorithm was designed which predicted the 3-month steady-state haemoglobin concentration following a change in ESA dose and only recommended a change if it was outside the range 10.5-12.5 g/dL. Data were collected prospectively for 3 months prior and 15 months subsequent to implementing the algorithm. Results. A total of 214 prevalent dialysis patients were included in the audit. After 12 months, the haemoglobin concentration was 11.4 g/dL, near the midpoint of the target range, with a narrowing of the distribution (SD 1.46 to 1.25 g/dL, P < 0.0001). The proportion of patients with a haemoglobin level in the target range increased from 56% to 66% (P < 0.001) principally due to a reduction in the number of patients with high haemoglobin levels. There was no significant change in the ESA dose over the audit period. The number of prescription changes fell from 1/2.5 months to 1/6.1 months after 12 months (P < 0.001). Conclusions. Switching prevalent haemodialysis patients to a predictive anaemia management algorithm improved compliance with haemoglobin targets, reduced the number of patients with high haemoglobin levels and reduced the number of ESA dose changes required.
机译:背景。许多贫血处理算法都建议根据对血红蛋白水平的频繁测量来更改促红细胞生成素(ESA)剂量,并与ESA数据表保持一致。我们设计了基于ESA药效学的预测性贫血算法,希望该算法可改善对血红蛋白靶标的依从性并减少工作量。方法。设计了一种新算法,该算法可预测ESA剂量变化后3个月的稳态血红蛋白浓度,并且仅在超出10.5-12.5 g / dL范围内时才建议更改。在实施该算法之前的3个月和之后的15个月中对数据进行了前瞻性收集。结果。审核中总共包括214名透析患者。 12个月后,血红蛋白浓度为11.4 g / dL,接近目标范围的中点,分布范围变窄(SD 1.46至1.25 g / dL,P <0.0001)。血红蛋白水平在目标范围内的患者比例从56%增加到66%(P <0.001),这主要是由于高血红蛋白水平的患者人数减少了。在审核期间,ESA剂量没有明显变化。更换处方的次数从1 / 2.5个月减少到12个月后的1 / 6.1个月(P <0.001)。结论将流行的血液透析患者转换为预测性贫血管理算法可以改善对血红蛋白靶标的依从性,减少高血红蛋白水平的患者数量,并减少所需的ESA剂量变化次数。

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