ABSTRACT
BACKGROUND AND AIMS: Acute Kidney Injury (AKI) has remarkable cardiovascular and mortality outcomes, both short and long term potentially preventable with adequate ICU support, thus, early diagnosis is mandatory. Full AKI diagnosis according to KDIGO criteria can result in delayed interventions at admission in ICU, giving potential benefits to alternatives in early diagnosis. Cruz and NEFROINT research group described a scale for prediction of severe AKI, based on risk factors and establishing creatinine cuts as markers of kidney distress.1 Our aim is to describe the predictive capacity of small changes in serum creatinine correlating with clinical risk factors in adult critical care patients. 1. Clin J Am Soc Nephrol (2014) 9, 663-672. METHOD: We retrospectively selected from our Critical Care Nephrology database adult patients admitted in any of our hospital's ICU between February to August 2020, excluding those at admission with diagnosis of AKI, serum creatinine > 2.5 mg/dl, or those receiving dialysis (acute or chronic) or kidney transplantation. We defined AKI according to KDIGO criteria. We calculated Cruz et al scale of prediction of severe AKI. The minimally acceptable criteria for this test was a sensitivity of 95%. A point estimate and confidence intervals of sensitivity and specificity were derived from a contingency table. RESULTS: From 1204 new ICU patients, according to selection criteria we found 372 patients (women 40.3%), with mean age of 60.9 years (range 18-98), mainly hospitalized for medical conditions. Mean values of APACHE II was 22.9. Hemodynamic support was required in 41.1% of patients and mechanical ventilation in 58.6% of patients. (Table 1). AKI KDIGO 2-3 was diagnosed in 65 (26.8%) of patients. Creatinine at admission was statistically different in patients that developed AKI (CI 0.95 -0.51 - 0.15 mg/dl, p=0.0004). Requirement of hemodynamic (p = 0.003) and ventilatory support (p = 0.009), sepsis (p = 0.003), and diagnosis of COVID-19 (p = 0.03) were more frequent in patients who developed AKI. Clinical risk for severe AKI was present in 356 patients (95.7%): 66,5% at very high risk, 9,8% at high risk and 19,2% at moderate risk. Patients without risk criteria were classified as low risk (4,3%). In patients with risk factors for AKI, and a significative increase in creatinine adjusted to risks, diagnostic performance for predicting diagnosis of KDIGO 2-3 AKI had a sensitivity, specificity, positive and negative predictive value of 89% (CI95% 79 - 95%), 58% (CI95% 52 - 64%), 0.31 (CI95% 0.25 - 0.39) and 0.96 (CI95% 0.92 - 0.98) respectively (Figure). Renal replacement therapy was required in 39 (60%) of patients with severe AKI (incidence 10.5%). (Table 2) CONCLUSION: Regardless of the risk stratification for AKI, the absence of significant early changes in serum creatinine rules out the possibility of progression to KDIGO 2-3 AKI in the first seven days after ICU admission.
ABSTRACT
BACKGROUND AND AIMS: Clinical outcomes of Acute Kidney Injury (AKI) in ICU mainly depend on opportune preventive strategies. Thus, early identification of AKI is mandatory, and alternative diagnostic strategies become plausible: one of them, Renal Angina Index (RAI), described by Matsuura1, predicts the development of AKI KDIGO 2-3, at 7th day after admission to the intensive care unit according to a cut-off point >6 on a scale with a 'creatinine score' (determined by the difference in serum creatinine between that at ICU admission and the first 24 hours in the ICU) and the impact of the patients medical history. 1Kidney Int Rep (2018) 3, 677-683. Our aim is to describe predictive capacity of the Renal Angina Index (RAI) in adult critical care patients in our population. METHOD: We retrospectively selected from our Critical Care Nephrology database adult patients admitted in any of our hospitals ICU between February to August 2020, excluding those at admission with diagnosis of AKI, serum creatinine > 2.5 mg/dl, or those receiving dialysis (acute or chronic) or kidney transplantation. We defined AKI according to KDIGO criteria. The RAI score was defined as the worst condition score multiplied by the creatinine score. The performance of the RAI score was assessed by Receiver Operating Characteristic (ROC) analysis power to detect a difference of 0.2 between the area under the curve (AUC), under the null hypothesis of AUC = 0.5 (no diagnostic accuracy). The optimal cut point was estimated with the Youden method. RESULTS: From 1204 new ICU patients, we included 372 patients (women 40.3%), with mean age 60.9 (18-98) (table 1). Main indication for ICU admission was medical conditions. Mean APACHE II was 22.9, hemodinamic support was required in 41,1% patients, mechanical ventilation in 58.6% patients and diabetes mellitus was present in 21.5% patients. AKI KDIGO 2-3 developed in 26.8% of patients. Mean creatinine at admission was statistically different in patients with AKI (CI 0.95 - 0.51 - -0.15 mg/dl, p=0.0004). The requirement of hemodynamic (p = 0.003) and ventilatory support (p = 0.009), sepsis (p = 0.003), and COVID-19 (p = 0.03) were more frequent in patients who developed AKI. Renal replacement therapy was required in 39 (60%) of patients with severe AKI (incidence 10,5%). RAI cutt-off point determined by Youden method in the overall sample was 24, being significantly higher in patients who developed AKI (16.54 Vs 7.47, CI 0.95 -13.5-4.99, p <0.001). A cut-off point of 24 was required for the Best predictive capacity for severe AKI, with sensitivity, specificity, positive and negative likelihood ratio of 34%, 94%, 5.5 and 0.7 respectively. CONCLUSION: In our population, RAI score requires a cutoff point much higher than that originally described to predict the development of severe AKI. Losing its discriminatory capacity.