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本文引用的文献

1
Hidden in Plain Sight - Reconsidering the Use of Race Correction in Clinical Algorithms.隐匿于众目睽睽之下——重新审视临床算法中种族校正的应用
N Engl J Med. 2020 Aug 27;383(9):874-882. doi: 10.1056/NEJMms2004740. Epub 2020 Jun 17.
2
Quantifying Sex-Based Disparities in Liver Allocation.量化肝移植分配中的性别差异。
JAMA Surg. 2020 Jul 1;155(7):e201129. doi: 10.1001/jamasurg.2020.1129. Epub 2020 Jul 15.
3
Reply to: "The decreasing predictive power of MELD in an era of changing etiology of liver disease".回复:“在肝病病因不断变化的时代,终末期肝病模型(MELD)预测能力的下降”
Am J Transplant. 2020 Mar;20(3):901-902. doi: 10.1111/ajt.15733. Epub 2019 Dec 27.
4
MELD-GRAIL-Na: Glomerular Filtration Rate and Mortality on Liver-Transplant Waiting List.MELD-GRAIL-Na:肝移植等待名单上的肾小球滤过率和死亡率。
Hepatology. 2020 May;71(5):1766-1774. doi: 10.1002/hep.30932. Epub 2020 Jan 29.
5
The decreasing predictive power of MELD in an era of changing etiology of liver disease.在肝病病因不断变化的时代,MELD 的预测能力下降。
Am J Transplant. 2019 Dec;19(12):3299-3307. doi: 10.1111/ajt.15559. Epub 2019 Sep 4.
6
Reconsidering the Consequences of Using Race to Estimate Kidney Function.重新审视使用种族来估算肾功能的后果。
JAMA. 2019 Jul 9;322(2):113-114. doi: 10.1001/jama.2019.5774.
7
Changes in united network for organ sharing policy for simultaneous liver-kidney allocation.器官共享联合网络关于同时进行肝肾分配政策的变化。
Clin Liver Dis (Hoboken). 2017 Feb 3;9(1):21-24. doi: 10.1002/cld.609. eCollection 2017 Jan.
8
A Model for Glomerular Filtration Rate Assessment in Liver Disease (GRAIL) in the Presence of Renal Dysfunction.存在肾功能障碍时肝病肾小球滤过率评估模型(GRAIL)
Hepatology. 2019 Mar;69(3):1219-1230. doi: 10.1002/hep.30321. Epub 2019 Feb 20.
9
Effects of Allocating Livers for Transplantation Based on Model for End-Stage Liver Disease-Sodium Scores on Patient Outcomes.基于终末期肝病模型-钠评分分配肝脏用于移植对患者结局的影响。
Gastroenterology. 2018 Nov;155(5):1451-1462.e3. doi: 10.1053/j.gastro.2018.07.025. Epub 2018 Jul 26.
10
The Impact of Albumin Use on Resolution of Hyponatremia in Hospitalized Patients With Cirrhosis.白蛋白在肝硬化住院患者低钠血症纠正中的作用。
Am J Gastroenterol. 2018 Sep;113(9):1339. doi: 10.1038/s41395-018-0119-3. Epub 2018 Jun 8.

MELD 3.0:适应新时代的终末期肝病模型。

MELD 3.0: The Model for End-Stage Liver Disease Updated for the Modern Era.

机构信息

Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California.

Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California.

出版信息

Gastroenterology. 2021 Dec;161(6):1887-1895.e4. doi: 10.1053/j.gastro.2021.08.050. Epub 2021 Sep 3.

DOI:10.1053/j.gastro.2021.08.050
PMID:34481845
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8608337/
Abstract

BACKGROUND & AIMS: The Model for End-Stage Liver Disease (MELD) has been established as a reliable indicator of short-term survival in patients with end-stage liver disease. The current version (MELDNa), consisting of the international normalized ratio and serum bilirubin, creatinine, and sodium, has been used to determine organ allocation priorities for liver transplantation in the United States. The objective was to optimize MELD further by taking into account additional variables and updating coefficients with contemporary data.

METHODS

All candidates registered on the liver transplant wait list in the US national registry from January 2016 through December 2018 were included. Uni- and multivariable Cox models were developed to predict survival up to 90 days after wait list registration. Model fit was tested using the concordance statistic (C-statistic) and reclassification, and the Liver Simulated Allocation Model was used to estimate the impact of replacing MELDNa with the new model.

RESULTS

The final multivariable model was characterized by (1) additional variables of female sex and serum albumin, (2) interactions between bilirubin and sodium and between albumin and creatinine, and (3) an upper bound for creatinine at 3.0 mg/dL. The final model (MELD 3.0) had better discrimination than MELDNa (C-statistic, 0.869 vs 0.862; P < .01). Importantly, MELD 3.0 correctly reclassified a net of 8.8% of decedents to a higher MELD tier, affording them a meaningfully higher chance of transplantation, particularly in women. In the Liver Simulated Allocation Model analysis, MELD 3.0 resulted in fewer wait list deaths compared to MELDNa (7788 vs 7850; P = .02).

CONCLUSION

MELD 3.0 affords more accurate mortality prediction in general than MELDNa and addresses determinants of wait list outcomes, including the sex disparity.

摘要

背景与目的

终末期肝病模型(MELD)已被确立为预测终末期肝病患者短期生存率的可靠指标。目前使用的版本(MELDNa)由国际标准化比值、血清胆红素、肌酐和钠组成,用于确定美国肝移植的器官分配优先级。本研究的目的是通过纳入更多变量并使用当代数据更新系数,进一步优化 MELD。

方法

纳入美国国家登记处 2016 年 1 月至 2018 年 12 月期间登记在肝移植等待名单上的所有候选者。采用单变量和多变量 Cox 模型预测等待名单登记后 90 天内的生存率。采用一致性统计量(C 统计量)和重新分类来测试模型拟合度,并使用 LiverSimulatedAllocationModel 估计用新模型替代 MELDNa 的影响。

结果

最终的多变量模型具有以下特点:(1)纳入女性和血清白蛋白等额外变量;(2)胆红素与钠、白蛋白与肌酐之间存在交互作用;(3)肌酐上限为 3.0mg/dL。最终模型(MELD3.0)的区分度优于 MELDNa(C 统计量分别为 0.869 和 0.862;P<0.01)。重要的是,MELD3.0正确地重新分类了 8.8%的死亡患者,使其处于更高的 MELD 等级,从而大大提高了他们接受移植的机会,尤其是女性患者。在 LiverSimulatedAllocationModel 分析中,与 MELDNa 相比,MELD3.0导致等待名单上的死亡人数减少(7788 例与 7850 例;P=0.02)。

结论

与 MELDNa 相比,MELD3.0总体上提供了更准确的死亡率预测,并解决了等待名单结果的决定因素,包括性别差异。