Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Islamic Republic of Iran.
Social Determinants of Health Research Center, Hamadan University of Medical Sciences, Hamadan, Islamic Republic of Iran.
Int Urol Nephrol. 2023 Oct;55(10):2657-2666. doi: 10.1007/s11255-023-03575-4. Epub 2023 Mar 29.
The common regression models included estimated glomerular filtration rate (eGFR) in the continuous and categorical form for predicting the mortality in COVID-19 inpatients. However, the relationship may be non-linear, and categorizing implies a loss of information. This study aimed to assess the effect of eGFR on admission on death within 30 days among COVID-19 inpatients using flexible and smooth transformations of eGFR and compare the results against the common models.
A retrospective study was conducted on hospitalized COVID-19 patients between April 2019 and July 2019 in Hamadan, Western Iran. The effect of eGFR on the death within 30 days was evaluated using different modeling: categorization, linear, unrestricted cubic spline (USC) with 4 knots, and fractional polynomial (FP). The results adjusted for older age and intensive care unit (ICU) admission. Discrimination power and model performance of the best-fitting model was evaluated using the area under the ROC (AUROC) and Brier score.
In total, 2945 patients (median age 61 years; interquartile range 48-73 years) were included, of whom the mortality rate was 9.23%. The relationship between the eGFR and death within 30 days is non-linear, so the degree-2 FP with powers (- 2, - 1) is the best-fitting model. Using the FP model, the risk increased exponentially in eGFR < 45 and then increased linearly and slowly. The AUROC of the FP model involving eGFR, older age, and ICU admission was 0.92 (95% CI 0.90-0.93) with a Brier score of 0.09.
There is a non-linear and asymmetric relationship between eGFR and death within 30 days among COVID-19 inpatients. Kidney function can be measured in COCID-19 patients on admission to know better understanding about prognosis of the patients.
在预测 COVID-19 住院患者的死亡率时,常用的回归模型包括连续和分类形式的估计肾小球滤过率(eGFR)。然而,这种关系可能是非线性的,而分类则意味着信息的丢失。本研究旨在评估 COVID-19 住院患者入院时 eGFR 对 30 天内死亡的影响,方法是对 eGFR 进行灵活和光滑的转换,并将结果与常用模型进行比较。
对 2019 年 4 月至 7 月在伊朗西部哈马丹住院的 COVID-19 患者进行回顾性研究。使用不同的模型评估 eGFR 对 30 天内死亡的影响:分类、线性、无限制立方样条(USC)有 4 个节点和分数多项式(FP)。结果调整了年龄较大和入住重症监护病房(ICU)的因素。使用 ROC 下面积(AUROC)和 Brier 评分评估最佳拟合模型的判别能力和模型性能。
共纳入 2945 例患者(中位年龄 61 岁;四分位距 48-73 岁),死亡率为 9.23%。eGFR 与 30 天内死亡之间的关系是非线性的,因此二次 FP 模型(幂(-2,-1)是最佳拟合模型。使用 FP 模型,eGFR<45 时风险呈指数增长,然后呈线性缓慢增长。纳入 eGFR、年龄较大和 ICU 入住的 FP 模型的 AUROC 为 0.92(95%CI 0.90-0.93),Brier 评分为 0.09。
COVID-19 住院患者的 eGFR 与 30 天内死亡之间存在非线性和不对称关系。可以在 COVID-19 患者入院时测量肾功能,以更好地了解患者的预后。