Anumas Suthiya, Chueachinda Supoj, Tantiyavarong Pichaya, Pattharanitima Pattharawin
Chulabhorn International College of Medicine, Thammasat University, Pathum Thani 12120, Thailand.
Division of Nephrology, Department of Internal Medicine, Faculty of Medicine, Thammasat University, Pathum Thani 12120, Thailand.
J Clin Med. 2023 Jun 30;12(13):4412. doi: 10.3390/jcm12134412.
The incidence and risk factors for acute kidney injury in COVID-19 patients vary across studies, and predicting models for AKI are limited. This study aimed to identify the risk factors for AKI in severe COVID-19 infection and develop a predictive model for AKI.
Data were collected from patients admitted to the ICU at Thammasat University Hospital in Thailand with PCR-confirmed COVID-19 between 1 January 2021, and 30 June 2022.
Among the 215 severe-COVID-19-infected patients, 102 (47.4%) experienced AKI. Of these, 45 (44.1%), 29 (28.4%), and 28 (27.4%) patients were classified as AKI stage 1, 2, and 3, respectively. AKI was associated with 30-day mortality. Multivariate logistic regression analysis revealed that prior diuretic use (odds ratio [OR] 7.87, 95% confidence interval [CI] 1.98-31.3; = 0.003), use of a mechanical ventilator (MV) (OR 5.34, 95%CI 1.76-16.18; = 0.003), and an APACHE II score ≥ 12 (OR 1.14, 95%CI 1.05-1.24; = 0.002) were independent risk factors for AKI. A predictive model for AKI demonstrated good performance (AUROC 0.814, 95%CI 0.757-0.870).
Our study identified risk factors for AKI in severe COVID-19 infection, including prior diuretic use, an APACHE II score ≥ 12, and the use of a MV. The predictive tool exhibited good performance for predicting AKI.
新冠病毒病（COVID-19）患者急性肾损伤的发病率和危险因素在不同研究中存在差异，且急性肾损伤（AKI）的预测模型有限。本研究旨在确定重症COVID-19感染患者发生AKI的危险因素，并建立AKI的预测模型。
收集2021年1月1日至2022年6月30日期间泰国法政大学医院重症监护病房收治的经聚合酶链反应（PCR）确诊为COVID-19的患者的数据。
在215例重症COVID-19感染患者中，102例（47.4%）发生了AKI。其中，45例（44.1%）、29例（28.4%）和28例（27.4%）患者分别被分类为AKI 1期、2期和3期。AKI与30天死亡率相关。多因素logistic回归分析显示，既往使用利尿剂（比值比[OR] 7.87，95%置信区间[CI] 1.98 - 31.3；P = 0.003）、使用机械通气（MV）（OR 5.34，95%CI 1.76 - 16.18；P = 0.003）以及急性生理与慢性健康状况评分系统II（APACHE II）评分≥12（OR 1.14，95%CI 1.05 - 1.24；P = 0.002）是AKI的独立危险因素。AKI预测模型表现良好（曲线下面积[AUC] 0.814，95%CI 0.757 - 0.870）。
我们的研究确定了重症COVID-19感染患者发生AKI的危险因素，包括既往使用利尿剂、APACHE II评分≥12以及使用MV。该预测工具在预测AKI方面表现良好。
