Koutroulos M V, Bakola S A, Kalpakidis S, Avramidou D, Panagaris S, Melissopoulou E, Souleiman H, Partsalidis A, Metaxa E, Feresiadis I, Kampaki E, Papadopoulos V
Department of Internal Medicine, Xanthi General Hospital, Xanthi, Greece.
Hippokratia. 2021 Jul-Sep;25(3):119-125.
Most outcome-predictive models for COVID-19 patients use hospital admission data, offering a spontaneous mortality risk estimation. We aimed to elaborate on a tool that could be applied repeatedly, thus being more suitable for these patients' rapidly changing clinical course.
In this prospective study, we evaluated 560 samples derived from 156 patients hospitalized for COVID-19 in a single center. Age >61 years, male sex, comorbidities >2, need for intensive care unit admission, lactate dehydrogenase (LDH) >408 U/L, Neutrophil/Lymphocyte Ratio (NLR) >17, C-reactive protein (CRP) >10 mg/dl, and D-dimers >3,200 ng/ml were incorporated in an eight-scale score (MaD-CLINYC) after optimal scaling, ridge regression, and bootstrapping, which was documented to correlate with outcome independently of one or more samples analyzed, day from admission at sampling, and need for delivery. Validation process was performed over 574 samples derived from three centers.
The developing and the validation cohort Area under Curve (AUC) was 0.90 (95 % Confidence Interval: 0.82-0.98) and 0.91 (0.88-0.94), respectively (p =0.822). A MaD-CLINYC score ≥4 had 75 % sensitivity and 81 % specificity to predict fatal outcome.
MaD-CLINYC score is a powerful, feasible, easy-to-use, dynamic tool to assess the risk of the outcome, thus assisting clinicians in close monitoring and timely decisions in COVID-19 hospitalized patients. HIPPOKRATIA 2021, 25 (3):119-125.
大多数针对新冠肺炎患者的预后预测模型使用医院入院数据,提供自发死亡风险估计。我们旨在精心设计一种可重复应用的工具,因此更适合这些患者快速变化的临床病程。
在这项前瞻性研究中,我们评估了来自单一中心因新冠肺炎住院的156例患者的560份样本。年龄>61岁、男性、合并症>2种、需要入住重症监护病房、乳酸脱氢酶(LDH)>408 U/L、中性粒细胞/淋巴细胞比值(NLR)>17、C反应蛋白(CRP)>10 mg/dl以及D-二聚体>3200 ng/ml,经过最优尺度变换、岭回归和自抽样法后被纳入一个八级评分(MaD-CLINYC),该评分被证明与预后相关,独立于所分析的一个或多个样本、采样时的入院天数以及分娩需求。验证过程在来自三个中心的574份样本上进行。
开发队列和验证队列的曲线下面积(AUC)分别为0.90(95%置信区间:0.82 - 0.98)和0.91(0.88 - 0.94)(p = 0.822)。MaD-CLINYC评分≥4对预测致命结局具有75%的敏感性和81%的特异性。
MaD-CLINYC评分是一种强大、可行、易于使用的动态工具,用于评估预后风险,从而协助临床医生对新冠肺炎住院患者进行密切监测并及时做出决策。《希波克拉底》2021年,25(3):119 - 125。