Horvath Angela, Lind Theresa, Frece Natalie, Wurzer Herbert, Stadlbauer Vanessa
Medical University of Graz, Graz, Austria.
Center for Biomarker Research in Medicine (CBmed), Graz, Austria.
Front Med (Lausanne). 2022 Oct 11;9:1016180. doi: 10.3389/fmed.2022.1016180. eCollection 2022.
Risk prediction is an essential part of clinical care, in order to allocate resources and provide care appropriately. During the COVID-19 pandemic risk prediction became a matter of political and public debate as a major clinical need to guide medical and organizational decisions. We previously presented a simplified risk stratification score based on a nomogram developed in Wuhan, China in the early phase of the pandemic. Here we aimed to validate this simplified risk stratification score in a larger patient cohort from one city in Austria. Age, oxygen saturation, C-reactive protein levels and creatinine levels were used to estimate the in-hospital mortality risk for COVID-19 patients in a point based score: 1 point per age decade, 4 points for oxygen saturation <92%, 8 points for CRP > 10 mg/l and 4 points for creatinine > 84 μmol/l. Between June 2020 and March 2021, during the "second wave" of the pandemic, 1,472 patients with SARS-CoV-2 infection were admitted to two hospitals in Graz, Austria. In 961 patients the necessary dataset to calculate the simplified risk stratification score was available. In this cohort, as in the cohort that was used to develop the score, a score above 22 was associated with a significantly higher mortality ( < 0.001). Cox regression confirmed that an increase of one point in the risk stratification score increases the 28-day-mortality risk approximately 1.2-fold. Patients who were categorized as high risk (≥22 points) showed a 3-4 fold increased mortality risk. Our simplified risk stratification score performed well in a separate, larger validation cohort. We therefore propose that our risk stratification score, that contains only two routine laboratory parameter, age and oxygen saturation as variables can be a useful and easy to implement tool for COVID-19 risk stratification and beyond. The clinical usefulness of a risk prediction/stratification tool needs to be assessed prospectively (https://www.cbmed.at/covid-19-risk-calculator/).
风险预测是临床护理的重要组成部分，以便合理分配资源并提供护理。在新冠疫情期间，风险预测作为指导医疗和组织决策的一项重大临床需求，成为了政治和公众辩论的焦点。我们之前基于在中国武汉疫情早期开发的列线图提出了一个简化的风险分层评分。在此，我们旨在对来自奥地利一个城市的更大规模患者队列中的这一简化风险分层评分进行验证。年龄、血氧饱和度、C反应蛋白水平和肌酐水平被用于通过一个基于点数的评分来估计新冠患者的院内死亡风险：每十岁年龄计1分，血氧饱和度<92%计4分，CRP>10mg/l计8分，肌酐>84μmol/l计4分。在2020年6月至2021年3月疫情的“第二波”期间，1472例感染新冠病毒的患者被收治到奥地利格拉茨的两家医院。在961例患者中，有计算简化风险分层评分所需的数据集。在这个队列中，与用于开发该评分的队列一样，评分高于22分与显著更高的死亡率相关（<0.001）。Cox回归证实，风险分层评分每增加1分，28天死亡风险增加约1.2倍。被归类为高风险（≥22分）的患者死亡风险增加3至4倍。我们的简化风险分层评分在一个单独的、更大的验证队列中表现良好。因此，我们建议我们的风险分层评分，该评分仅包含年龄和血氧饱和度这两个常规实验室参数作为变量，可成为新冠风险分层及其他方面有用且易于实施的工具。风险预测/分层工具的临床实用性需要前瞻性评估（https://www.cbmed.at/covid-19-risk-calculator/）。
