Background: 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.
Method: 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.
Results: 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; p = 0.003), use of a mechanical ventilator (MV) (OR 5.34, 95%CI 1.76-16.18; p = 0.003), and an APACHE II score ≥ 12 (OR 1.14, 95%CI 1.05-1.24; p = 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).
Conclusions: 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.
Keywords: COVID-19; acute kidney injury; prediction; risk factors.