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Article Acute Respiratory Distress Syndrome and Risk of AKI Among Article Acute Respiratory Distress Syndrome and Risk of AKI among Critically Ill Patients Michael Darmon, Christophe Clec’h, Christophe Adrie, Laurent Argaud, Bernard Allaouchiche, Elie Azoulay, Lila Bouadma, Maı¨te´ Garrouste-Orgeas, Hakim Haouache, Carole Schwebel, Dany Goldgran-Toledano, Hatem Khallel, Anne-Sylvie Dumenil, Samir Jamali, Bertrand Souweine, Fabrice Zeni, Yves Cohen, and Jean-Franc¸ois Timsit Abstract Background and objectives Increasing experimental evidence suggests that acute respiratory distress syndrome Due to the number of contributing authors, (ARDS) may promote AKI. The primary objective of this study was to assess ARDS as a risk factor for AKI in the affiliations are critically ill patients. provided in the Supplemental Design, setting, participants, & measurements This was an observational study on a prospective database fed by Material. 18 intensive care units (ICUs). Patients with ICU stays .24 hours were enrolled over a 14-year period. ARDS was defined using the Berlin criteria and AKI was defined using the Risk, Injury, Failure, Loss of kidney function, and Correspondence: Dr. Michael Darmon, End-stage kidney disease criteria. Patients with AKI before ARDS onset were excluded. Medical-Surgical Intensive Care Unit, Results This study enrolled 8029 patients, including 1879 patients with ARDS. AKI occurred in 31.3% of Saint Etienne patients and was more common in patients with ARDS (44.3% versus 27.4% in patients without ARDS; University Hospital, P,0.001). After adjustment for confounders, both mechanical ventilation without ARDS (odds ratio [OR], Avenue Albert fi Raimond, 42270 Saint 4.34; 95% con dence interval [95% CI], 3.71 to 5.10) and ARDS (OR, 11.01; 95% CI, 6.83 to 17.73) were in- Priest in Jarez, France. dependently associated with AKI. Hospital mortality was 14.2% (n=1140) and was higher in patients with Email: michael. ARDS (27.9% versus 10.0% in patients without ARDS; P,0.001) and in patients with AKI (27.6% versus 8.1% darmon@chu-st- in those without AKI; P,0.001). AKI was associated with higher mortality in patients with ARDS (42.3% etienne.fr versus 20.2%; P,0.001). Conclusions ARDS was independently associated with AKI. This study suggests that ARDS should be considered as a risk factor for AKI in critically ill patients. Clin J Am Soc Nephrol 9: 1347–1353, 2014. doi: 10.2215/CJN.08300813 Introduction but may also lead to further systemic inflammation AKI is common in critically ill patients and remains via the release of inflammatory cytokines (23–26). associated with poor outcomes (1–3). The main Few studies have specifically addressed the associ- known risk factors for AKI in critically ill patients ation between respiratory failure and AKI (27–32). In areabsoluteorrelativehypovolemia, nephrotoxic addition, most of these studies were performed in – drug exposure, sepsis, and comorbidities (4 8). specific patient populations and failed to adequately An increasing body of evidence points to deleteri- address the effect of ARDS on renal function (27,29– ous interactions between kidney and lung dysfunc- 32). tions (9). Experimental studies suggest that AKI may The primary objective of this study was to assess the fl increase the risk of lung injury, chie y via the activa- influence of ARDS on subsequent AKI in unselected fl tion of proin ammatory and proapoptotic pathways patients in the intensive care unit (ICU). because of renal ischemia/reperfusion (9–13). Several lines of evidence suggest that mechanical ventilation and acute respiratory distress syndrome (ARDS) may Materials and Methods have adverse effects on kidney function via three Study Design and Data Source main mechanisms. First, positive-pressure ventilation We conducted an observational study on a pro- may reduce cardiac output and increase central ve- spective multicenter database (OutcomeRea; http:// nous pressure, thereby diminishing renal blood flow, www.outcomerea.org) to assess influence of refrac- free water clearance, or the GFR (14–17). In addition, tory hypoxemia on subsequent AKI. The database, fl changes in arterial blood O2 or CO2 may in uence fed by 18 French ICUs, collects prospective data on renal vascular resistance, renal perfusion, or diuresis daily disease severity, iatrogenic events, and nosoco- (18–22). Finally, emerging data suggest that ventila- mial infections. Each year, each ICU includes a ran- tor-induced lung injury may not only affect the lung, domsampleofatleast50patientswhohaveICU www.cjasn.org Vol 9 August, 2014 Copyright © 2014 by the American Society of Nephrology 1347 1348 Clinical Journal of the American Society of Nephrology stays .24 hours. Each ICU can choose to obtain patients’ definitions were established before study initiation. The samples by taking either consecutive admissions to se- data quality checking procedure was described elsewhere lected ICU beds throughout the year or consecutive admis- (36). The following information was recorded: age, sex, sions to all ICU beds for 1 month. admission category (medical, scheduled surgery, or un- scheduled surgery), and origin (home, ward, or emergency fi Study Population and Definitions department). Severity of illness was evaluated on the rst fi This study was approved by the institutional review ICU day using the Simpli ed Acute Physiology Score II board of the Clermont Ferrand University Hospital, which (SAPS II), the Sequential Organ Failure Assessment waived the need for informed consent in compliance with (SOFA) score, and the Logistic Organ Dysfunction score – fi French law on database studies. This study was conducted (37 39). Knaus scale de nitions were used to record pre- in accordance with the Declaration of Helsinki. existing chronic organ failures including respiratory, car- We included consecutive patients aged.18 years who diac, hepatic, renal, and immune system failures (40). were entered into the database between January 1997 and Finally, the McCabe scoring system was assessed to obtain April 2011. Patients with preexisting chronic kidney failure comparisons regarding the importance of host factors on (defined as an eGFR,60 ml/min per 1.73 m2), with pre- the basis of the severity of the underlying disease, ranging renal dysfunction (transient AKI) as the main mechanism from 1 (no fatal underlying disease) to 3 (rapidly fatal un- of AKI, with AKI predating ARDS, treatment-limitation derlying disease) (41). decisions, left ventricular dysfunction, or ICU stays ,24 hours (and were thus unlikely to develop AKI after ARDS Quality of the Database onset) were excluded. For most of the study variables, the data-capture soft- AKI was defined according to the Risk, Injury, Failure, ware immediately ran an automatic check for internal Loss of kidney function, and End-stage kidney disease consistency, generating queries that were sent to the ICUs fi (RIFLE) criteria (33) and ARDS was de ned as a PaO2/ for resolution before incorporation of the new data into the , FiO2 ratio 300 mmHg in the absence of cardiogenic pul- database. In each participating ICU, data quality was monary edema (Table 1) (34). Because the 6- and 12-hour checked by having a senior physician from another par- urine outputs were not recorded in the database, AKI def- ticipating ICU review a 2% random sample of the study inition and maximum renal severity were based upon data every other year. A 1-day data-capture training course changes in serum creatinine. held once a year was open to all OutcomeRea investigators Baseline creatinine values were assessed using the four- and study monitors. All qualitative variables used in the k fi . variable Modification of Diet in Renal Disease (MDRD) analyses had coef cients 0.8 and all variables had inter- fi – equation. As recommended by the Acute Dialysis Quality rater coef cients in the 0.67 1 range, indicating good to Initiative Group, a normal eGFR of 75 ml/min per 1.73 m2 excellent reproducibility. before ICU admission was assumed (35). CKD was either defined according to the Acute Physi- Statistical Analyses ology and Chronic Health Evaluation II definition or was Categorical variables are presented as n (%) and contin- identified through a specific code according to data ex- uous variables are medians (interquartile ranges). Com- tracted from the medical record. Transient AKI and left parisons of patients with and without AKI relied on ventricular dysfunction were extracted from medical re- chi-squared tests for categorical data and on the t test or cords and identified through a specific code in the database. Wilcoxon’s test, as appropriate, for continuous data. Risk factors associated with AKI were assessed using a mul- tivariate logistic regression model. The potential link be- Data Collection Data were collected daily by senior physicians and/or tween ARDS and the subsequent development of AKI specifically trained study monitors in the participating was assessed after adjusting for clinically pertinent con- fi ICUs and all of the collected data were extracted from founding factors and for factors signi cant in the univar- medical records. For each patient, the investigators entered iate analysis. These factors were baseline comorbidities fi the data into a computer case-report form using data- (diabetes mellitus, immunode ciency, chronic cardiac capture software (RHEA; OutcomeRea) and imported all and pulmonary dysfunction, and myeloma), sepsis, ad- records into the OutcomeRea database. All codes and ministration of nephrotoxic drugs (aminoglycosides, gly- copeptides, and/or iodinated contrast media), nonrenal organ failures (de fined as the relevant specificSOFAcom- ponent score.2), and age. Each of these variables was Table 1. Severity of ARDS included in a stepwise logistic regression conditional ARDS PaO2/FiO2 Ratio PEEP model in which variables were selected according to their , Severity (mmHg) (cmH2O) P value. Variables with a P value 0.05 were maintained in the final model. Goodness of fit and discrimination of , # $ Mild 200 PaO2/FiO2 300 5 the model were determined using the Hosmer–Lemeshow , # $ Moderate 100 PaO2/FiO2 200 5 statistic and the C statistic (area under the curve), respec- Severe 100#PaO /FiO $5 2 2 tively.
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