Role Of Urinary Kidney Stress Biomarkers For Early Recognition Of Subclinical Acute Kidney Injury in Critically Ill COVID-19 Patients

3. Results 

3.1. Characteristics of Study Population 

During the period between May and August 2020, a total of 420 individuals were admitted to the critical areas of the INER. Of those, 69 were negative for SARS-CoV-2 infection; in 44 the infection could not be confirmed; 60 remained in the emergency room due to hospital saturation; and 20 died there. Informed consent could not be obtained for 196 patients. We thus included the 51 patients who provided informed consent for participating in the study (Figure 1). Of those, 30 were male (58.8%); the median age was 53 years (IQR: 40–61); 14 had hypertension (27.5%); 16 had diabetes (31.4%); and 21 were obese 41.2%. Of the 51 individuals that were studied, 25 developed AKI during hospitalization (the AKI group, 49.0%) and 26 did not develop AKI (the non-AKI group, 51.0%). A total of 11 individuals had AKI stage 1 (21.5%); 8 had AKI stage 2 (15.6%); and 6 had AKI stage 3 (11.7%). The baseline characteristics of study population and comparisons between the AKI group vs. the non-AKI group are shown in Table 1. 

Figure 1. Study diagram. Numbers of individuals that were assessed for eligibility and individuals that were included in the study

3.2. Performance of Biomarkers as AKI Predictors 

Based on the highest AUC, specificity, and accuracy values, the biomarker with best performance for AKI prediction during the whole hospitalization period was NGAL at a cutoff of 45 ng/mL. Considering that most patients developed AKI during the first 7 days at the hospital, we also determined the performance of biomarkers for AKI prediction on day 7 (Table 2). The performance of NGAL was significantly better on day 7 than during the whole hospitalization period (AUC = 0.771 vs. AUC = 0.706; p = 0.001). The combination of [TIMP-2] × [IGFBP7] at a cutoff of 0.2 (ng/mL)2/1000 were the second best AKI predictors, and the performance of these biomarkers during the whole hospitalization was similar to that of day 7 (AUC= 0.682 vs. AUC= 0.671; p = 0.632).

Table 1. Baseline characteristics of the study population

AKI, acute kidney injury; BMI, body mass index; IMV, invasive mechanical ventilation; PaO2/FiO2, partial arterial oxygen pressure/inspired oxygen fraction; pCO2, partial pressure of carbon dioxide; PEEP, positive end-expiratory pressure; SOFA, sequential organ failure assessment; eGFR, estimated glomerular filtration rate; Systemic steroids: dexamethasone, methylprednisolone; prednisone; NGAL, neutrophil gelatinase-associated lipocalin; TIMP-2, tissue inhibitor of metalloproteinases 2; IGFBP7, insulin-like growth factor binding protein 7. * Data are expressed as medians (interquartile ranges). Comparisons of the AKI group vs. the non-AKI group were made using the chi-squared test for categorical variables and Mann–Whitney U for continuous variables. Bold values denote statistical significance at the p ≤ 0.05 level.

Table 2. Performance of urinary biomarkers for the prediction of acute kidney injury in critically ill COVID-19 patients. 

AKI, acute kidney injury; AUC, area under the receiver-operating characteristics curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; NGAL; neutrophil gelatinase-associated lipocalin; TIMP-2, tissue inhibitor of metalloproteinases-2; IGFBP7, insulin-like growth factor binding protein 7. 

3.3. Time to AKI Was Significantly Shorter in Individuals with Higher Values of Urinary NGAL and [TIMP-2] × [IGFBP7] 

As NGAL 45 ng/mL had the highest specificity and accuracy values, we selected this cutoff value for the survival analysis of the time to AKI during hospitalization. Individuals with NGAL ≥ 45 ng/mL were compared vs. those with <45 ng/mL. Urinary NGAL could not be measured in 3 patients. The time to AKI was significantly shorter in individuals with NGAL ≥ 45 ng/mL than in those with <45 ng/mL; p = 0.028 (Figure 2). Similarly, [TIMP-2] × [IGFBP7] 0.2 (ng/mL)2/1000 had the highest specificity and accuracy, so this cutoff was selected for the survival analysis of the time to AKI during hospitalization. We found that the time to AKI was significantly shorter in individuals with [TIMP-2] × [IGFBP7] ≥ 0.2 ng/mL than in those with <0.2 (ng/mL)2/1000; p = 0.017 (Figure 3).

3.4. Elevated Values of Urinary [TIMP-2] × [IGFBP7] were Risk Factors for AKI 

The univariate analysis indicated that patients with AKI were older (hazard ratio, HR = 0.94, 95% CI: 0.90–0.99; p = 0.034); had a higher frequency of hypertension (HR = 6.02, 95% CI: 1.42–25.40; p = 0.014); had levels of [TIMP-2] × [IGFBP7] ≥ 0.2 (ng/mL)2/1000 (HR = 5.11, 95% CI: 1.20–21.67; p = 0.027); and NGAL ≥ 45 ng/mL (HR = 4.00, 95% CI: 1.15–13.81; p = 0.028). After adjusting for possible confounding variables, the multivariate analysis indicated that the risk factors for AKI during the hospitalization period were male gender (HR = 7.57, 95% CI: 1.28–44.8; p = 0.026) and [TIMP-2] × [IGFBP7] ≥ 0.2 (ng/mL)2/ 1000 (HR = 7.23, 95% CI: 0.99–52.4; p = 0.050) (Table 3). At day 7 of hospitalization, after adjusting by age and sex, we found that only [TIMP-2] × [IGFBP7] ≥ 0.2 (ng/mL) 2/1000 remained associated with risk for AKI (HR = 5.91, 95% CI: 1.06–32.7; p = 0.042). 

3.5. Mortality was Higher in Individuals with AKI 

We constructed a Kaplan–Meyer curve for mortality comparing the group of 25 patients who developed AKI during follow-up with the group of 26 individuals without AKI. The mortality of individuals who developed AKI at any time during hospitalization was significantly higher than in those who never had AKI, p = 0.019 (Figure 4).

Figure 2. Cumulative AKI events according to urinary NGAL concentrations. AKI in individuals with urinary NGAL > 45 ng/mL (back line) vs. AKI in individuals with urinary NGAL < 45 ng/mL (grey line) during hospitalization (p = 0.028). Time 0 corresponds to hospital admission. 

Table 3. Risk factors for acute kidney injury in critically ill COVID-19 patients.

HR, hazard ratio; CI, confidence interval; NGAL; neutrophil gelatinase-associated lipocalin; TIMP-2, tissue inhibitor of metalloproteinases 2; IGFBP7, insulin-like growth factor binding protein 7; CPK, creatine phosphokinase. The variables were entered into the model when the alpha level of risk factor was less than 0.15. Age and gender were added into the model regardless of the alpha level. Bold values denote statistical significance at the p ≤ 0.05 level.

Figure 3. Cumulative AKI events according to urinary [TIMP-2] × [IGFBP7] concentrations. AKI in individuals with urinary [TIMP-2] × [IGFBP7] > 0.2 (ng/mL)2/1000 (black line) vs. AKI in individuals with urinary [TIMP-2] × [IGFBP7] < 0.2 (ng/mL)2/1000 (grey line) during hospitalization (p = 0.013). Time 0 corresponds to hospital admission. 

Of the 25 individuals with AKI, 13 had transient AKI (25.5 %) and 12 had persistent AKI (23.5%). The CKD-EPI on discharge was similar in individuals with persistent AKI (79.5 mL/min/1.73m2 , IQR: 17–111) and in those with transient AKI (93 mL/min/1.73m2 , IQR: 88–104; p = 0.53). Logistic regression analysis was used to identify the association between the relevant covariates with mortality. The univariate analysis indicated that mortality was more frequent in patients who were 60 years of age or older (HR = 5.33, 95% CI: 1.23–23.09; p = 0.025); and had persistent AKI (HR = 10.83, 95% CI: 1.67–69.91; p = 0.012). After adjusting for possible confounding variables, only persistent AKI remained associated with mortality (HR = 7.42, 95% CI: 1.04–53.04; p = 0.046) (Table 4).