PDF(Pubmed)
Abstract：
Sickle cell disease (SCD) is a lifelong blood disorder affecting approximately 100,000 people in the United States and is one of the most common monogenic diseases. A serious complication of SCD is acute chest syndrome (ACS). ACS is a condition with a high rate of morbidity and mortality. The aim of the study was to assess hemolysis and lipid parameters in a cohort of confirmed SCD patients to predict ACS development in the following year.Standard lipid were performed (triglycerides, total cholesterol, high-density cholesterol, low-density cholesterol) panel to calculate of non-HDL-C, large buoyant LDL cholesterol (lbLDL-C) and small dense LDL cholesterol (sdLDL-C) with Sampson equation. Hemolysis and hematologic parameters were also evaluated.Among 91 patients included between September 2018 and June 2021, thirty-seven patients had history of ACS and 6 patients developed ACS during following year. In unadjusted logistic regression, total bilirubin was associated with ACS occurrence (RR: 1.2 [1.05-1.51] p = 0.013). Concerning lipid profile, non-HDL-C (RR: 0.87 [0.0.67-0.99] p = 0.04) and sdLDL-C (RR: 0.78 [0.49-0.96] p = 0.03) were associated with ACS occurrence decrease. C-reactive protein was associated with ACS occurrence (RR: 1.27 [1.065-1.85] p = 0.011).Based on these findings, this study demonstrated that several biomarker easily available can be used at steady state to predict ACS in the following year. The validation of these results are required to ensure the reproducibility of the findings.
摘要：
镰状细胞病(SCD)是在美国影响约100,000人的终身血液疾病,并且是最常见的单基因疾病之一。SCD的严重并发症是急性胸部综合征（ACS）。ACS是具有高发病率和死亡率的病症。该研究的目的是评估一组确诊的SCD患者的溶血和脂质参数，以预测第二年的ACS发展。进行标准脂质(甘油三酯，总胆固醇,高密度胆固醇,低密度胆固醇)面板计算非HDL-C，大浮力低密度脂蛋白胆固醇(lbLDL-C)和小密度低密度脂蛋白胆固醇(sdLDL-C)的Sampson方程。还评估了溶血和血液学参数。在2018年9月至2021年6月期间纳入的91例患者中，有37例患者有ACS病史，6例患者在第二年发展为ACS。在未调整的逻辑回归中，总胆红素与ACS发生相关(RR:1.2[1.05-1.51]p=0.013).关于血脂，non-HDL-C(RR:0.87[0.0.67-0.99]p=0.04)和sdLDL-C(RR:0.78[0.49-0.96]p=0.03)与ACS发生率降低相关.C反应蛋白与ACS发生相关(RR:1.27[1.065-1.85]p=0.011)。基于这些发现,这项研究表明,在稳态下,可以使用几种容易获得的生物标志物来预测次年的ACS.需要对这些结果进行验证以确保结果的可重复性。
