Date Published: June 20, 2019
Publisher: Public Library of Science
Author(s): Fiorenza Ferrari, Mariangela Valentina Puci, Ottavia Eleonora Ferraro, Gregorio Romero-González, Faeq Husain-Syed, Lilia Rizo-Topete, Mara Senzolo, Anna Lorenzin, Eva Muraro, Antonio Baracca, Mara Serrano-Soto, Alejandra Molano Triviño, Ana Coutinho Castro, Massimo De Cal, Valentina Corradi, Alessandra Brendolan, Marta Scarpa, Maria Rosa Carta, Davide Giavarina, Raffaele Bonato, Giorgio Antonio Iotti, Claudio Ronco, Zaccaria Ricci.
AKI is associated with increased risk of death, prolonged length of stay and development of de-novo chronic kidney disease. The aim of our study is the development and validation of prediction models to identify the risk of AKI in ICU patients up to 7 days. We retrospectively recruited 692 consecutive patients admitted to the ICU at San Bortolo Hospital (Vicenza, Italy) from 1 June 2016 to 31 March 2017: 455 patients were treated as the derivation group and 237 as the validation group. Candidate variables were selected based on a literature review and expert opinion. Admission eGFR< 90 ml/min /1.73 mq (OR 2.78; 95% CI 1.78–4.35; p<0.001); SOFAcv ≥ 2 (OR 2.23; 95% CI 1.48–3.37; p<0.001); lactate ≥ 2 mmol/L (OR 1.81; 95% CI 1.19–2.74; p = 0.005) and (TIMP-2)•(IGFBP7) ≥ 0.3 (OR 1.65; 95% CI 1.08–2.52; p = 0.019) were significantly associated with AKI. For the q-AKI score, we stratified patients into different AKI Risk score levels: 0–2; 3–4; 5–6; 7–8 and 9–10. In both cohorts, we observed that the proportion of AKI patients was higher in the higher score levels.
Acute Kidney Injury (AKI) occurs in approximately 50% of patients admitted to an Intensive Care Unit (ICU). Increasing severity of AKI is associated with increased risk of death, prolonged length of stay, increased Intensive Therapy Unit utilisation, and the development of de-novo chronic kidney disease [1–5].
We have shown that AKI development within the first week of an ICU stay, as defined by the KDIGO criteria , might be identified from a prediction model that uses data routinely available one hour after admission.