General Surgery and Organ Transplantation Unit, Sapienza University, Rome, Italy.
Hepato-biliopancreatic and Transplant Surgery Unit, University of Modena, Modena, Italy.
Liver Int. 2021 Jul;41(7):1629-1640. doi: 10.1111/liv.14889. Epub 2021 Apr 22.
BACKGROUND & AIMS: Sarcopenia in liver transplantation (LT) cirrhotic candidates has been connected with higher dropouts and graft losses after transplant. The study aims to create an 'urgency' model combining sarcopenia and Model for End-stage Liver Disease Sodium (MELDNa) to predict the risk of dropout and identify an appropriate threshold of post-LT futility.
A total of 1087 adult cirrhotic patients were listed for a first LT during January 2012 to December 2018. The study population was split into a training (n = 855) and a validation set (n = 232).
Using a competing-risk analysis of cause-specific hazards, we created the Sarco-Model . According to the model, one extra point of MELDNa was added for each 0.5 cm /m reduction of total psoas area (TPA) < 6.0 cm /m . At external validation, the Sarco-Model showed the best diagnostic ability for predicting the risk of 3-month dropout in patients with MELDNa < 20 (area under the curve [AUC] = 0.93; P = .003). Using the net reclassification improvement, 14.3% of dropped-out patients were correctly reclassified using the Sarco-Model . As for the futility threshold, transplanted patients with TPA < 6.0 cm /m and MELDNa 35-40 (n = 16/833, 1.9%) had the worse results (6-month graft loss = 25.5%).
In sarcopenic patients with MELDNa < 20, the 'urgency' Sarco-Model should be used to prioritize the list, while MELDNa value should be preferred in patients with MELDNa ≥ 20. The Sarco-Model played a role in more than 30% of the cases in the investigated allocation scenario. In sarcopenic patients with a MELDNa value of 35-40, 'futile' transplantation should be considered.
肝移植（LT）肝硬化候选者的肌肉减少症与移植后更高的辍学率和移植物丢失有关。本研究旨在创建一个结合肌肉减少症和终末期肝病钠模型（MELDNa）的“紧急”模型，以预测辍学风险并确定 LT 后无效的适当阈值。
共纳入 1087 例 2012 年 1 月至 2018 年 12 月接受首次 LT 的成人肝硬化患者。研究人群分为训练组（n=855）和验证组（n=232）。
使用特定原因风险的竞争风险分析，我们创建了 Sarco-Model。根据该模型，对于 TPA<6.0cm/m 的每 0.5cm/m 的总腰大肌面积（TPA）减少，MELDNa 增加 1 分。在外部验证中，Sarco-Model 在预测 MELDNa<20 患者 3 个月辍学风险方面显示出最佳诊断能力（曲线下面积[AUC]为 0.93；P=0.003）。使用净重新分类改善，14.3%的辍学患者使用 Sarco-Model 得到正确重新分类。至于无效阈值，TPA<6.0cm/m 和 MELDNa 35-40 的移植患者（n=16/833，1.9%）结果最差（6 个月移植物丢失率=25.5%）。
在 MELDNa<20 的肌肉减少症患者中，应使用“紧急”Sarco-Model 对名单进行优先排序，而 MELDNa 值应优先用于 MELDNa≥20 的患者。Sarco-Model 在研究分配方案中的 30%以上的病例中发挥了作用。对于 MELDNa 值为 35-40 的肌肉减少症患者，应考虑“无效”移植。
