title: RIFLE-based data collection/management system applied to a prospective cohort multicenter Italian study on the epidemiology of acute kidney injury in the intensive care unit.
abstract: The epidemiology of acute kidney injury (AKI) has been difficult to explore in the past, due to different definitions across various studies. Nevertheless, this is a very important topic today in light of the high morbidity and mortality of critically ill patients presenting renal dysfunction during their stay in the intensive care unit (ICU). The case mix has changed over the years, and AKI is a common problem in critically ill patients often requiring renal replacement therapy (RRT). The RIFLE and AKIN initiatives have provided a unifying definition for AKI, making possible large retrospective studies in different countries. The present study aims at validating a unified web-based data collection and data management tool based on the most recent AKI definition/classification system. The interactive database is designed to elucidate the epidemiology of AKI in a critically ill population. As a test, we performed a prospective observational multicenter study designed to prospectively evaluate all incident admissions in ten ICUs in Italy and the relevant epidemiology of AKI. Thus, a simple user-friendly web-based data collection tool was created with the scope to serve for this study and to facilitate future multicenter collaborative efforts. We enrolled 601 consecutive incident patients into the study; 25 patients with end-stage renal disease were excluded, leaving 576 patients for analysis. The median age was 66 (IQR 53-76) years, 59.4% were male, while median Simplified Acute Physiology Score II and Acute Physiology and Chronic Health Evaluation II scores were 43 (IQR 35-54) and 18 (IQR 13-24), respectively. The most common diagnostic categories for ICU admission were: respiratory (27.4%), followed by neurologic (17%), trauma (14.4%), and cardiovascular (12.1%). Crude ICU and hospital mortality were 21.7% and median ICU length of stay was 5 (IQR 3-14) days. Of 576 patients, 246 patients (42.7%) had AKI within 24 h of ICU admission, while 133 developed new AKI later during their ICU stay. RIFLE-initial class was Risk in 205 patients (54.1%), Injury in 99 (26.1%) and Failure in 75 (19.8%). Progression of AKI to a worse RIFLE class was seen in 114 patients (30.8% of AKI patients). AKI patients were older, with higher frequency of common risk factors. 116 AKI patients (30.6%) fulfilled criteria for sepsis during their ICU stay, compared to 33 (16.7%) of non-AKI patients (p < 0.001). 48 patients (8.3%) were treated with RRT in the ICU. Patients were started on RRT a median of 2 (IQR 0-6) days after ICU admission. AKI patients were started on RRT a median of 1 (IQR 0-4) day after fulfilling criteria for AKI. Median duration of RRT was 5 (IQR 2-10) days. AKI patients had a higher crude ICU mortality (28.8 vs. 8.1%, non-AKI; p < 0.001) and longer ICU length of stay (median 7 vs. 3 days, non-AKI; p < 0.001). Crude ICU mortality and ICU length of stay increased with greater severity of AKI. 225 (59.4% of AKI patients) had complete recovery of renal function, with a serum creatinine at time of ICU discharge which was ≤120% of baseline; an additional 51 AKI patients (13.5%) had partial renal recovery, while 103 (27.2%) had not recovered renal function at the time of death or ICU discharge. The study supports the use of RIFLE as an optimal classification system to stage AKI severity. AKI is indeed a deadly complication for ICU patients, where the level of severity is correlated with mortality and length of stay. The tool developed for data collection was user-friendly and easy to implement. Some of its features, including a RIFLE class alert system, may help the treating physician to systematically collect AKI data in the ICU and possibly may guide specific decisions on the institution of RRT.
authors.affiliation: Departments of Intensive Care and Anesthesiology, St. Bortolo Hospital, Viale Rodolfi 37, Vicenza, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Garzotto
authors.forename: Pasquale
authors.initials: P
authors.lastname: Piccinni
authors.forename: Dinna
authors.initials: D
authors.lastname: Cruz
authors.forename: Silvia
authors.initials: S
authors.lastname: Gramaticopolo
authors.forename: Marzia
authors.initials: M
authors.lastname: Dal Santo
authors.forename: Giovanni
authors.initials: G
authors.lastname: Aneloni
authors.forename: Jeong Chul
authors.initials: JC
authors.lastname: Kim
authors.forename: Monica
authors.initials: M
authors.lastname: Rocco
authors.forename: Elisa
authors.initials: E
authors.lastname: Alessandri
authors.forename: Francesco
authors.initials: F
authors.lastname: Giunta
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Michetti
authors.forename: Michele
authors.initials: M
authors.lastname: Iannuzzi
authors.forename: Clara
authors.initials: C
authors.lastname: Belluomo Anello
authors.forename: Nicola
authors.initials: N
authors.lastname: Brienza
authors.forename: Mauro
authors.initials: M
authors.lastname: Carlini
authors.forename: Paolo
authors.initials: P
authors.lastname: Pelaia
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Gabbanelli
authors.forename: Claudio
authors.initials: C
authors.lastname: Ronco
mesh_terms: D058186:Acute Kidney Injury / Q000453:epidemiology*; D000328:Adult; D000368:Aged; D015331:Cohort Studies; D003628:Database Management Systems / Q000639:trends; D016208:Databases, Factual / Q000639:trends; D005260:Female; D006801:Humans; D015994:Incidence; D007362:Intensive Care Units; D020407:Internet / Q000639:trends; D007558:Italy / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies