NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust And University Of Nottingham, Nottingham, United Kingdom.
NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust And University Of Nottingham, Nottingham, United Kingdom.
Clin Gastroenterol Hepatol. 2019 Oct;17(11):2330-2338.e1. doi: 10.1016/j.cgh.2019.01.042. Epub 2019 Feb 1.
BACKGROUND & AIMS: It is important to rapidly identify patients with advanced liver disease. Routine tests to assess liver function and fibrosis provide data that can be used to determine patients' prognoses. We tested the validated the ability of combined data from the ALBI and FIB-4 scoring systems to identify patients with compensated cirrhosis at highest risk for decompensation.
We collected data from 145 patients with compensated cirrhosis (91% Child A cirrhosis and median MELD scores below 8) from a cohort in Nottingham, United Kingdom, followed for a median 4.59 years (development cohort). We collected baseline clinical features and recorded decompensation events. We used these data to develop a model based on liver function (assessed by the ALBI score) and extent of fibrosis (assessed by the FIB-4 index) to determine risk of decompensation. We validated the model in 2 independent external cohorts (1 in Dublin, Ireland and 1 in Menoufia, Egypt) comprising 234 patients.
In the development cohort, 19.3% of the patients developed decompensated cirrhosis. Using a combination of ALBI and FIB-4 scores, we developed a model that identified patients at low vs high risk of decompensation (hazard ratio [HR] for decompensation in patients with high risk score was 7.10). When we tested the scoring system in the validation cohorts, the HR for decompensation in patients with a high-risk score was 12.54 in the Ireland cohort and 5.10 in the Egypt cohort.
We developed scoring system, based on a combination of ALBI and FIB-4 scores, that identifies patients at risk for liver decompensation. We validated the scoring system in 2 independent international cohorts (Europe and the Middle East), so it appears to apply to diverse populations.
快速识别患有晚期肝病的患者很重要。评估肝功能和纤维化的常规检查提供的数据可用于确定患者的预后。我们检验了 ALBI 和 FIB-4 评分系统联合数据识别代偿性肝硬化患者中最易发生肝失代偿风险的能力。
我们从英国诺丁汉的一个队列中收集了 145 例代偿性肝硬化患者的数据（91%为 Child A 级肝硬化，中位 MELD 评分低于 8），中位随访 4.59 年（发展队列）。我们收集了基线临床特征并记录了失代偿事件。我们使用这些数据基于肝功能（由 ALBI 评分评估）和纤维化程度（由 FIB-4 指数评估）建立了一个模型，以确定失代偿风险。我们在 2 个独立的外部队列（1 个在爱尔兰都柏林，1 个在埃及 Menoufia）中对模型进行了验证，共纳入 234 例患者。
在发展队列中，19.3%的患者发展为失代偿性肝硬化。我们使用 ALBI 和 FIB-4 评分的组合建立了一个模型，该模型可以识别低风险与高风险的患者（高危评分患者的失代偿风险比[HR]为 7.10）。当我们在验证队列中测试评分系统时，高危评分患者的失代偿 HR 在爱尔兰队列中为 12.54，在埃及队列中为 5.10。
我们基于 ALBI 和 FIB-4 评分的组合建立了一个评分系统，可以识别发生肝失代偿风险的患者。我们在 2 个独立的国际队列（欧洲和中东）中验证了该评分系统，因此它似乎适用于不同人群。
