• Raúl Lombardi, Nicolás Nin, Oscar Peñuelas, Alejandro Ferreiro, Fernando Rios, Maria Carmen Marin, Konstantinos Raymondos, Jose A Lorente, Younsuck Koh, Javier Hurtado, Marco Gonzalez, Fekri Abroug, Manuel Jibaja, Yaseen Arabi, Rui Moreno, Dimitros Matamis, Antonio Anzueto, Andres Esteban, and VENTILA Group.
• *Servicio Médico Integral, Montevideo, Uruguay†Hospital Español, Montevideo, Uruguay‡Hospital Universitario de Getafe, Madrid, Spain§CIBER Enfermedades Respiratorias, Barcelona, Spain||Hospital de Clínicas, Universidad de la Republica, Montevideo, Uruguay¶Hospital Nacional Alejandro Posadas, Buenos Aires, Argentina#Hospital Regional 1° Octubre, ISSSTE, Ciudad de México, México, Mexico**Medizinische Hochschule Hannover, Hannover, Germany††Asan Medical Center, University of Ulsan, Seoul, Republic of Korea‡‡Clínica Medellín and Universidad Pontificia Bolivariana, Medellín, Colombia§§Hospital Fattouma Bourguina, Monastir, Tunisia||||Hospital Eugenio Espejo, Quito, Ecuador¶¶King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia##UCINC, Hospital de Sao José, Centro Hospitalar de Lisboa Central, E.P.E., Lisbon, Portugal***Papageorgiou Hospital, Thessaloniki, Greece†††South Texas Veterans Health Care System and University of Texas Health Science Center, San Antonio, Texas.
• Shock. 2017 Oct 1; 48 (4): 411-417.

BackgroundAcute kidney injury (AKI) is a frequent complication in patients under mechanical ventilation (MV). We aimed to assess the risk factors for AKI with particular emphasis on those potentially preventable.Study Design, Setting, And ParticipantsRetrospective analysis of a large, multinational database of MV patients with >24 h of MV and normal renal function at admission. AKI was defined according to creatinine-based KDIGO criteria. Risk factors were analyzed according to the time point at which AKI occurred: early (≤48 h after ICU admission, AKIE) and late (day 3 to day 7 of ICU stay, AKIL). A conditional logistic regression model was used to identify variables independently associated with AKI.ResultsThree thousand two hundred six patients were included. Seven hundred patients had AKI (22%), the majority of them AKIE (547/704). The risk factor profile was highly dependent upon the timing of AKI onset. In AKIE risk factors were older age; SAPS II score; postoperative and cardiac arrest as the reasons for MV; worse cardiovascular SOFA, pH, serum creatinine, and platelet count; higher level of peak pressure and Vt/kg; and fluid overload at admission. In contrast, AKIL was linked mostly to events that occurred after admission (lower platelet count and pH; ICU-acquired sepsis; and fluid overload). None ventilation-associated parameters were identify as risk factors for AKIL.ConclusionsIn the first 48 h, risk factors are associated with the primary disease and the patient's condition at admission. Subsequently, emergent events like sepsis and organ dysfunction appear to be predictive factors making prevention a challenge.

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