Acute Kidney Injury Is Surprisingly Common and a Powerful Predictor of Mortality in Surgical Sepsis

ORIGINAL ARTICLE

Acute kidney injury is surprisingly common and a powerful predictor of mortality in surgical sepsis

Laura E. White, MD, Heitham T. Hassoun, MD, Azra Bihorac, MD, Laura J. Moore, MD, R. Matt Sailors, Bruce A. McKinley, PhD, Alicia Valdivia, and Frederick A. Moore, MD, Houston, Texas

BACKGROUND: Acute kidney injury (AKI) is a common and often catastrophic complication in hospitalized patients; however, the impact of AKI in surgical sepsis remains unknown. We used Risk, Injury, Failure, Loss, End stage (RIFLE) consensus criteria to define the incidence of AKI in surgical sepsis and characterize the impact of AKI on patient morbidity and mortality. METHODS: Our prospective, institutional review board-approved sepsis research database was retrospectively queried for the incidence of AKI by RIFLE criteria, excluding those with chronic kidney disease. Patients were grouped into sepsis, severe sepsis, and septic shock by refined consensus criteria. Data including demographics, baseline biomarkers of organ dysfunction, and outcomes were compared by Student’s t test and W2 test. Multivariable regression analysis was performed for the effect of AKI on mortality adjusting for age, sex, African-American race, elective surgery, Acute Physiology and Chronic Health Evaluation II score, septic shock versus severe sepsis, and sepsis source. RESULTS: During the 36-month study period ending on December 2010, 246 patients treated for surgical sepsis were evaluated. AKI occurred in 67% of all patients, and 59%, 60%, and 88% of patients had sepsis, surgical sepsis, and septic shock, respectively. AKI was associated with Hispanic ethnicity, several baseline biomarkers of organ dysfunction, and a greater severity of illness. Patients with AKI had fewer ventilator-free and intensive care unitYfree days and a decreased likelihood of discharge to home. Morbidity and mortality increased with severity of AKI, and AKI of any severity was found to be a strong predictor of hospital mortality (odds ratio, 10.59; 95% confidence interval, 1.28Y87.35; p = 0.03) in surgical sepsis. CONCLUSION: AKI frequently complicates surgical sepsis, and serves as a powerful predictor of hospital mortality in severe sepsis and septic shock. (J Trauma Acute Care Surg. 2013;75: 432Y438. Copyright * 2013 by Lippincott Williams & Wilkins) LEVEL OF EVIDENCE: Prognostic and epidemiologic study, level III. KEY WORDS: Sepsis; surgical sepsis; acute kidney injury; epidemiology; multiple-organ failure.

espite advancements in renal replacement therapy (RRT), sepsis requiring surgical intervention for source control or Dacute kidney injury (AKI) is a common complication with sepsis occurring within 14 days of a surgical procedure, carries adverse outcomes in hospitalized patients. AKI affects 25% a mortality rate of 30% to 40% and occurs more frequently to 67% of the critically ill and independently elicits a 30% than other dreaded postoperative complications such as pul- to 60% mortality rate, even after normalization for illness monary embolism or myocardial infarction.5,6 Surgical trauma, severity.1Y3 Much of this increased risk of death is caused by induction of anesthesia, and the frequent requirement for emer- remote organ injury because AKI occurs most often in the gent surgical source control all contribute to the formidable setting of multiple-organ failure (MOF) and is independently clinical challenge of surgical sepsis and provide a unique associated with extrarenal organ dysfunction, regardless of re- stimulus for AKI. quirement for RRT.2 In contrast to sepsis where defined consensus criteria Sepsis is a notorious inciting factor for AKI, attributing have been used for nearly 20 years, AKI lacked a standard to nearly half of all cases and resulting in the highest risk of definition until 2004 when the Acute Dialysis Quality Initiative death above all other etiologies.3,4 Surgical sepsis, defined as group published consensus Risk, Injury, Failure, Loss, and End-stage Kidney (RIFLE) criteria.7 Recent data in surgical patients using consensus criteria demonstrate that increasing Submitted: June 14, 2012, Revised: April 7, 2013, Accepted: April 16, 2013. From the Department of Surgery (L.E.W., H.T.H., L.J.M., M.S., B.A.M., A.V., severity of AKI is associated with worse outcomes after trau- Y F.A.M.), The Methodist Hospital and Research Institute; and The Methodist ma, cardiac surgery, or major abdominal surgery,8 10 and the DeBakey Department of Cardiovascular Surgery (H.T.H.), The Methodist effect of AKI extends well beyond discharge to impact long- Hospital System; and Department of Surgery (L.J.M.), The University of Texas 11 Health Science Center, Houston, Texas; Division of Critical Care Medicine term mortality. (A.B.), Department of Anesthesiology, and Department of Surgery (M.S., Extensive research describes AKI in diverse populations; B.A.M., F.A.M.), The University of Florida College of Medicine, Gainesville, however, no previous studies have specifically examined the Florida. This work was presented as a poster at the 71st annual meeting of the American As- epidemiology and impact of AKI in surgical sepsis. Our sur- sociation for the Surgery of Trauma, September 12Y15, 2012, in Kauai, Hawaii. gical sepsis research team has maintained a unique prospective Address for reprints: Laura E. White, MD, The Methodist Hospital Department of database of patients with surgical sepsis defined by consensus Surgery, 6550 Fannin St, SM 1661, Houston, TX 77030; criteria.12Y14 We hypothesized that AKI is a frequent compli- email: [email protected]. cation of surgical sepsis that serves as a harbinger for increas- DOI: 10.1097/TA.0b013e31829de6cd ing patient morbidity and mortality. To address this hypothesis, J Trauma Acute Care Surg 432 Volume 75, Number 3

Copyright © 2013 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. J Trauma Acute Care Surg Volume 75, Number 3 White et al. we used the well-validated RIFLE criteria to define the inci- AKI was defined by applying RIFLE criteria on pro- dence of AKI in surgical sepsis in a retrospective fashion and spectively collected serum creatinine (SCr) values for all pa- to further characterize the association of AKI with patient tients in the surgical sepsis database. Patients with AKI were morbidity and mortality. stratified into either having AKI or no AKI according to the severity determined by comparing the highest SCr with the reference SCr. For the reference SCr, we used the SCr before PATIENTS AND METHODS admission (if within 6 months of admission, n = 130) when available, and for all others, we used the lowest measured SCr Study Site and Patients at the day of hospital admission (n = 116). The RIFLE creat- This study was conducted at The Methodist Hospital, inine criteria were used, in which ‘‘Risk’’ encompasses an in- a 948-bed, academic tertiary referral hospital located in the crease in SCr of 50% or greater, ‘‘Injury’’ includes an increase Texas Medical Center in Houston, Texas. The general surgery in SCr of 100% or greater, and ‘‘Failure’’ captures an increase intensive care unit (GSICU) is a 27-bed, noncardiac unit serving in creatinine of 200% or greater (or an SCr Q 4 mg/dL, which a diverse group of surgical patients including critically ill gen- represents an acute change of Q 0.5 mg/dL). eral, vascular, oncologic, transplant, thoracic, orthopedic, plastic, To identify patients with chronic kidney disease (CKD), urologic, as well as head and neck surgical patients. All patients we performed review of all admission notes (L.E.W. and A.B.) are screened for sepsis twice daily using our validated physi- to exclude all patients with documented history of CKD 15 ologic sepsis screening tool. Once identified, all patients before admission. Among patients without history of CKD are immediately treated with an evidence-based computerized on admission, we excluded those with a reference estimated clinical decision support protocol including goal-directed fluid glomerular filtration rate of 60 mL/min per 1.72 m2 or less resuscitation with time-appropriate interventions based on clini- (calculated by applying CKD-EPI equation on reference SCr cal consensus and evidence-based guidelines for the manage- [n = 26]).20 Additional specific exclusion criteria used during 16,17 ment of sepsis. With informed consent, all GSICU patients review of admission notes were diagnosis of end-stage renal managed with this protocol have data acquired for our surgical disease, obstructive uropathy, urosepsis, presence of only one sepsis research database. Data collection and entry are per- kidney (congenital or acquired), presence of previous surgi- formed prospectively by a research nurse and informaticist, cal bladder reconstruction, and patients with and presence of respectively, and all cases are reviewed and maintained by previous organ transplantation (n = 9). the surgical sepsis research team. Data reports are coded and password protected to ensure patient confidentiality. The sepsis Statistical Analysis research database and current study is maintained with ap- In comparing two study groups, a two-tailed Student’s proval of the Methodist Hospital Research Institute Institu- t test was used for continuous data. If the assumptions for this tional Review Board. test were not met, the appropriate test (Mann-Whitney U-test) was used. For univariate analysis of categorical variables, we 2 Study Design and Data Collection used Pearson W analysis or Fisher’s exact test as appropriate. Our study population includes GSICU patients enter- For categorical variables, a multiple logistic regression analysis ing into the surgical sepsis database from January 1, 2008, to was performed to determine an association between AKI and December 31, 2010. All study patients are entered into the in-hospital mortality, adjusting for age, sex, African-American database after diagnosis of sepsis, severe sepsis, or septic race, elective surgery, APACHE II score, septic shock versus shock based on our modification of the American College of severe sepsis, and sepsis source (abdominal vs. respiratory vs. Chest Physicians/Society of Critical Care Medicine (ACCP/ other). The goodness of fit of the logistic regression models SCCM) Consensus Conference definitions.18,19 The database was assessed with the Hosmer-Lemeshow test, and c statis- was queried for patient demographics, baseline (at time of sepsis tics evaluated the discriminatory capability of the models. For diagnosis) biomarkers reflecting organ dysfunction (listed in noncategorical variables, linear regression models were fit- Table 2), source of infection, acuity of operation, Acute Phys- ted to compare the effect of AKI on the length of ICU- and iology and Chronic Health Evaluation (APACHE) II score, ventilator-free periods after adjusting for all other variables and sequential organ failure assessment (SOFA) score as pre- as previously mentioned. Least squares means were compared 19 for the AKI-adjusted multiple regression models. The coeffi- viously described. Outcomes included ventilator-free days, 2 dialysis-free days, ICU-free days, secondary infections, early cient of determination, R , was calculated as an indicator of the and late MOF, ICU mortality, hospital mortality, and discharge proportion of variability explained by each model. Diagnostic disposition. plots were examined to assess the assumptions of the regres- Methods for defining sources of infection, secondary sion models, and no serious departures from the assumptions > infections, acuity of operation, APACHE II scores, SOFA scores were observed. All significance tests were 2 sided, with an of (renal component excluded), early and late MOF (Denver MOF 0.05, which we considered to be statistically significant. All score), ICU-free days, dialysis-free days, and ventilator-free analyses were performed using SAS (version 9.2, Cary, NC) days were used as previously described.19 Other outcomes included ICU mortality, hospital mortality, and discharge dis- RESULTS position: patients who were discharged to ‘‘other’’ included those transferred to a long-term acute care facility or a skilled During the 36-month study period, a total of 246 patients nursing facility. who did not meet exclusion criteria were treated for surgical

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Copyright © 2013 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. J Trauma Acute Care Surg White et al. Volume 75, Number 3 sepsis. Most patients presented with severe sepsis (58%) or septic shock (24%) compared with sepsis (18%). When defined TABLE 2. Baseline Evidence of Organ Dysfunction by RIFLE criteria, AKI occurred in 65% of all patients with No AKI n = 85 AKI n = 161 surgical sepsis. When stratified by sepsis severity, AKI affec- Vital signs, mean T SEM ted 59%, 59%, and 86% of patients with sepsis, surgical sepsis, Temperature, -C 37.5 T 0.2 37.5 T 0.1 and septic shock, respectively. AKI developed within the first Heart rate, beats/min 112 T 2 113 T 2 7 days of resuscitation in the majority (80%), and 17% had Respiratory rate, breaths/min 23 T 123T 1 AKI at the time of sepsis diagnosis and ICU admission. Mean arterial pressure, mm Hg 86 T 280T 1* Patients who developed AKI were 59 years on average, BOD mostly women (55%) and mostly white (70%) (Table 1). The White blood cell, K/HL 17.54 T 1 14.7 T 1 most common site of infection was the abdomen (70%), and Hemoglobin, g/dL 10.2 T 0.2 10 T 0.2 most patients underwent emergency surgery (67%). There were Sodium, mEq/L 136 T 1 136 T 1 no significant differences in patient age, sex, race, preexist- Potassium, mEq/L 4.7 T 0.9 4.1 T 0.1 ing conditions, presumed infection sites, and acuity of opera- Chloride, mEq/L 103 T 1 107 T 2 tion among those who developed AKI compared with those CO2, mEq/L 25 T 122T 0** who did not. Blood urea nitrogen, mg/dL 17 T 132T 2** Patients with AKI were more likely to have a lower mean Creatinine, mg/dL 0.8 T 0 1.5 T 0.1** arterial pressure at time of sepsis diagnosis compared with Lactate, Mean, mg/dL 1.6 T 0.1 3.5 T 0.3** those without AKI (Table 2. Patients with AKI also had higher pH 7.39 T 0.01 7.34 T 0.01**

PaO2/FIO2 251 T 22 223 T 17 T. bilirubin, mg/dL 1.1 T 0.1 2.7 T 1 T T TABLE 1. Characteristics of Study Cohort Alk Phos, U/L 132 13 157 13 Aspartate aminotransferase, U/L 35 T 659T 12 All Patients Alanine aminotransferase, U/L 49 T 898T 25 No AKI (n = 85) AKI (n = 161) BNP (pg/mL) 112 T 17.8 181.9 T 52.9 Age, y 58 T 259T 1 International normalized ratio 1.5 T 0 1.7 T 0.1* Male sex, n (%) 31 (36) 72 (45) Platelet count (K/HL) 269 T 17 233 T 11 Race, n (%) Fibrinogen, mg/dL 180 T 33 282 T 27* White 67 (79) 113 (70) D-Dimer, Hg/L 4.6 T 0.4 6.85 T 0.53* African American 12 (14) 34 (21) T3, ng/dL 74 T 365T 3* Asian 3 (4) 6 (4) T4, Hg/dL 6 T 0.2 5 T 0* Other 3 (4) 8 (5) TSH, mIU/L 2.95 T 1.1 3.15 T 0.7* Ethnicity, n (%) Systemic inflammatory response 4 T 04T 0 Hispanic 7 (8) 17 (11) syndrome Severity T T Non-Hispanic 78 (92) 144 (89) APACHE II (at 24 h) 21 1271** T T Preexisting conditions, n (%) SOFAnonrenal (at 24 h) 4 060** Smoker 10 (12) 33 (20) *p G 0.05. G ETOH user 3 (4) 11 (7) **p 0.001. All continuous variables expressed as mean T SEM. Central nervous system 18 (21) 36 (22) BOD, biomarkers of organ dysfunction at time of sepsis diagnosis; SOFAnonrenal, Pulmonary 20 (24) 60 (37) SOFA with renal score excluded. Cardiac 29 (34) 68 (42) Diabetes 22 (26) 38 (24) Vascular 4 (5) 10 (6) Liver 1 (1) 0 (0) serum blood urea nitrogen, creatinine, lactate, international nor- Gastrointestinal 7 (8) 15 (9) malized ratio, fibrinogen, D-Dimer, and TSH levels and lower Immunocompromised 18 (21) 46 (29) CO ,T,T, and pH levels compared with those who did not Coagulopathy 5 (6) 17 (11) 2 3 4 develop AKI. In addition, patients with AKI had a greater se- Any of the previously mentioned 54 (64) 127 (79) verity of illness with higher APACHE II (27T 1vs.21T 1, p G Presumed infection site 0.001) and nonrenal SOFA (6 TG0vs.4T 0, p G 0.001) scores. Abdomen 64 (75) 113 (70) The overall hospital mortality rate for surgical sepsis Pulmonary/thoracic 5 (6) 15 (9) was 17%. Patients with sepsis had the lowest mortality rate Wound/soft tissue 10 (12) 13 (8) (7%), followed by severe sepsis (11%) and septic shock (37%). Line infection 4 (5) 10 (6) For all patients, AKI was associated with significantly fewer Other 2 (2) 10 (6) ventilator-free (18 T 1 vs. 25 T 1, p G 0.001), dialysis-free Elective surgery, n (%) 27 (32) 53 (33) (22 T 1 vs. 28 T 0, p G 0.001), and ICU-free days (14 T 1 vs. Emergency surgery, n (%) 58 (68) 108 (67) 21 T 1, p G 0.001) (Table 3). AKI was associated with an in- *p G 0.05 for AKI versus no AKI T crease in secondary infections, early MOF, ICU mortality All continuous variables expressed as mean SEM. (17% vs. 1%, p G 0.001) and hospital mortality (24% vs. 2%,

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MOF.26 Surgical trauma, induction of anesthesia, and the TABLE 3. Patient Outcomes and Occurrence of RIFLE AKI frequent requirement for emergent surgical source control all No AKI (n = 85) AKI (n = 161) contribute to the formidable clinical challenge of surgical Ventilator-free days 25 T 118T 1* sepsis and provide a unique stimulus for AKI. Dialysis-free days 28 T 022T 1* We hypothesized that AKI is a frequent complication ICU-free days 21 T 114T 1* of surgical sepsis that predicts increasing patient morbidity Secondary infections, % 7 17** and mortality. To address this hypothesis, we used the well- Early MOF, % 1 19** validated RIFLE criteria to identify the incidence of AKI in Late MOF, % 1 6 surgical sepsis and define the impact of AKI on hospital mor- ICU mortality, % 1 17* tality. In the current article, we identify that in surgical sepsis, Hospital mortality, % 2 24* (1) AKI occurs in 67% of all patients, (2) patients who develop Discharged home, %† 63 42** AKI have a significantly higher morbidity and mortality, (3) Discharged other, %† 37 58** patients with AKI who survive are less likely to be discharged home, (4) patients with renal failure have a higher morbidity *p G 0.001 for AKI versus no AKI. **p G 0.05 for AKI versus no AKI. and mortality compared with patients with less severe AKI, †Data available for 205 of 246 patients and (5) AKI serves as a powerful predictor of hospital mortality All continuous variables expressed as mean T SEM. in patients with severe sepsis and septic shock. With the recent introduction of the RIFLE classification for AKI, the adverse effects of small changes in SCr have G p 0.001) and were less likely to be discharged home (42% vs. begun to be recognized and systematically studied. Hence, the G 63%, p 0.001). term AKI has been proposed to replace ‘‘acute renal failure’’ Nearly half (48%) of all patients with AKI had failure, and encompass the entire spectrum of the syndrome, from 30% were categorized as having risk, and 22% had injury minor changes in renal function to the requirement for RRT.27 (Table 4). Patients with the most severe AKI (failure) had fewer Initial studies using established definitions of AKI demon- ventilator-free and ICU-free days compared with patients with strate that among medical patients with sepsis, progression lesser AKI as well as a higher incidence of secondary infec- from severe sepsis to septic shock correlates with a stepwise tions. The hospital mortality rate for patients with the mildest increase in severity of AKI, increasing RIFLE stages of AKI form of AKI (risk) was 4%, but in patients with injury and correlate linearly with hospital mortality, and AKI of any se- failure, mortality rates were 25% and 36%, respectively. verity is an independent predictor of mortality.28,29 We found On multivariable logistic regression analysis, AKI was that in surgical sepsis, progression to renal failure was asso- found to be a strong predictor of hospital mortality (odds ciated with significantly higher morbidity and mortality com- Y ratio [OR], 7.12, 95% confidence interval [CI], 1.35 37.58, pared with milder AKI and no AKI at all, which parallels data p = 0.03) in patients with severe sepsis and septic shock after trauma, cardiac surgery, or major abdominal surgery.8Y10 (Table 5). Other independent predictors were age (OR, 1.04; While we used RIFLE criteria to identify AKI, the Acute Y 95% CI, 1.01 1.07; p = 0.02) and APACHE II score (OR, Kidney Injury Network (AKIN) criteria, introduced by the Y G 1.13; 95% CI, 1.06 1.20; p 0.0001). On multivariable linear Acute Dialysis Quality Initiative in 2007,30 have several key regression analysis, AKI was also found to be a significant refinements of the RIFLE definition. AKIN criteria include independent predictor of fewer ventilator-free (difference between means, 3.8 days; 95% CI, 0.9Y6.6; p = 0.0097) and ICU- free (3.0 days; 95% CI, 0.6Y5.4; p = 0.0162) days (Table 6). TABLE 4. Severity of AKI and Outcomes in Surgical Sepsis No AKI, Risk, Injury, Failure, DISCUSSION 85 (35%) 48 (30%) 35 (22%) 78 (48%) AKI remains one of the most challenging public health Ventilator-free days 25 T 121T 1* 21 T 2* 15 T 1***† T T T T problems in modern medicine, affecting 7% of all hospitalized Dialysis-free days 28 0271252* 19 1***† patients and up to two thirds of the critically ill.1,21 Despite ICU-free days 21 T 117T 1* 17 T 212T 1***† improvements in RRT and advances in supportive care, the Secondary in 6 (7) 5 (10) 4 (11) 18 (23)* fections, n (%) significant morbidity and mortality associated with AKI has Early MOF, n (%) 1 (1) 5 (10)* 5 (14)* 21 (27)*** remained unchanged during the past several decades.4 This is Late MOF, n (%) 1 (1) 2 (4) 1 (3) 7 (9)* likely caused by the fact that AKI rarely occurs in isolation, and ICU mortality (%) 1 4 11* 28***† emerging evidence suggests that altered homeostasis during Hospital mortality, 2 4 26*** 36*** AKI leads to an activated immune response and distant organ n (%) 22 dysfunction. Discharged home, 52 (63) 18 (39)* 14 (54) 19 (38)* Across the spectrum of medical and surgical admissions, n (%) AKI most commonly occurs as a consequence of shock, sepsis, G 3,23 *p 0.05 versus no AKI. major surgery, or hypovolemia. Sepsis is a well-established **p G 0.05 versus risk. Y leading risk factor for AKI,23 25 and mortality rates in patients †p G 0.05 versus injury by t test. ‡p = 5.0 Â 10j7 by W2 test. with both AKI and sepsis are much greater than in patients T with either AKI or sepsis alone, particularly in the setting of All continuous variables expressed as mean SEM.

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TABLE 5. Multivariable Regression Analysis for Hospital Mortality, Ventilator-Free Days, and ICU-Free Days* Hospital Mortality Ventilator-Free Days ICU-Free Days c statistic, 0.894; Hosmer-Lemeshow GOF, 0.812 R2 = 34.5% R2 = 39.9% Predictors OR (CI for OR) p Estimate (SE) p Estimate (SE) p Age, y 1.04 (1.01Y1.07) 0.0208 j0.05 (0.04) 0.2368 0.003 (0.03) 0.9369 Male sex (vs. female) 1.38 (0.56Y3.42) 0.4910 0.14 (1.29) 0.9114 j0.44 (1.11) 0.6922 African-American race (vs. other) 0.86 (0.27Y2.75) 0.7983 j0.55 (1.58) 0.7270 j1.1 (1.38) 0.4282 Elective (vs. emergent) 1.48 (0.54Y4.07) 0.4508 j0.81 (1.38) 0.5579 j1.44 (1.18) 0.2233 APACHE II 1.13 (1.06Y1.20) G0.0001 j0.53 (0.08) G0.0001 j0.57 (0.07) G0.0001 Septic shock (vs. severe sepsis) 1.53 (0.60Y3.92) 0.3732 j0.71 (1.49) 0.6352 j0.97 (1.31) 0.4618 Sepsis source Abdominal vs. other* 0.74 (0.25Y2.19) 0.5819 0.97 (1.57) 0.5384 0.79 (1.36) 0.5610 Respiratory vs. other* 1.08 (0.20Y5.78) 0.9280 j0.61 (2.59) 0.8154 j2.09 (2.27) 0.3593 RIFLE AKI (yes vs. no) 7.12 (1.35Y37.58) 0.0208 j3.76 (1.44) 0.0097 j2.97 (1.22) 0.0162

*Other includes urinary tract infection, central line infections, soft tissue, other GOF, goodness of fit. an increase in the absolute value of SCr of 0.3 mg/dL or greater patients remain persistently catabolic, display signs of poor for Stage 1 AKI (RIFLE ‘‘risk’’ category) as well as a 48-hour wound healing and muscle wasting, and are ultimately dis- time window for detection of changes in kidney function charged to long-term acute care facilities where they experience (compared with 7 days for RIFLE criteria). In large epidemi- indolent death. We hypothesize that AKI predisposes patients ologic studies, AKIN and RIFLE criteria are found to have to develop PICS because these patients had prolonged hos- strikingly similar efficacy in clinical application, including pital stays, had increased morbidity, and were less likely to be diagnosis of AKI, severity classification, and association with discharged home. Clinical data also indicate that even small mortality.31 We chose RIFLE criteria because of the 7-day changes in SCr can portend dramatic increases in patient period, which would recognize patients who have a slower morbidity and mortality and the effect of AKI extends well rise in creatinine (948 hours) during surgical sepsis who would beyond initial hospitalization to impact long-term mortality, otherwise be missed with the AKIN classification. Further- extending more than a decade beyond hospital discharge.11 more, to address potential limitations, we compared the RIFLE The relationship between AKI and PICS remains un- criteria to the new expanded RIFLE consensus criteria,32 which defined; however, data suggest that immune dysregulation include an increase in SCr of 0.3 mg/dL or greater and queried may play a key role. Patients with PICS have a persistent acute our surgical sepsis database for the incidence of AKI. We phase response (characterized by elevated C-reactive protein found the sensitivity, specificity, and accuracy of both the and undetectable prealbumin levels) with elevated white blood RIFLE and expanded RIFLE criteria to be roughly equivalent cell counts but with a very low percentage of lymphocytes.35 predictors of mortality (data not shown). Recent laboratory studies demonstrate the long-term emergence We did not see an increase in early or late MOF in pa- of myeloid derived suppressor cells during sepsisVimmature tients with AKI during surgical sepsis; however, recent data innate immune cells that suppress lymphocytes but simulta- suggest that the late peak in MOF has largely disappeared, pri- neously cause persistent inflammation. We believe they play marily owing to the implementation of evidence-based guide- central role in PICS, and this is a current focus of our ongoing lines.33 We believe that a new phenotype of MOF has emerged, research related to MOF pathogenesis.35 Similarly, emerging the persistent inflammatory/immunosuppression catabolism syn- evidence suggests that altered homeostasis during AKI leads drome (PICS).34 PICS is characterized by prolonged ICU stays, to an activated innate and adaptive immune response and manageable organ dysfunctions, and recurrent infections with distant organ dysfunction.22,36Y40 These data challenge tradi- mild systemic inflammatory response syndrome that rarely tional concepts of the role of the T lymphocyte in innate and induces septic shock. Despite adequate nutritional support, adaptive immune responses and suggest that AKI should not

TABLE 6. Comparison of Adjusted Mean Ventilator-Free and ICU-Free Days Stratiﬁed by the Occurrence of RIFLE AKI*

RIFLE AKI Adjusted Mean (95% CL) No RIFLE AKI Adjusted Mean (95% CL) Difference Between Means (95% CL) p** Ventilator-free days 18.6 (17.1Y20.1) 22.3 (20.1Y24.6) 3.8 (0.9Y6.6) 0.0097 ICU-free days 14.9 (13.6Y16.2) 17.9 (16.0Y19.8) 3.0 (0.6Y5.4) 0.0162

*Adjusted for all other variables (age, race, sex, elective vs. emergent surgery, severity of sepsis, and sepsis source). **p value for difference between means. CL, conﬁdence limit.

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Copyright © 2013 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. J Trauma Acute Care Surg Volume 75, Number 3 White et al. be regarded as a treatable component of MOF but as an in- 2. Mehta RL, Pascual MT, Soroko S, Savage BR, Himmelfarb J, Ikizler TA, dependent contributor to immune dysregulation and mortality. et al. Spectrum of acute renal failure in the intensive care unit: the PICARD Y Limitations of our study include its retrospective nature experience. Kidney Int. 2004;66:1613 1621. 3. Uchino S, Kellum JA, Bellomo R, Doig GS, Morimatsu H, Morgera S, and relatively small sample size; however, the well-defined et al. Acute renal failure in critically ill patients: a multinational, mul- selection criteria for both surgical sepsis and AKI and com- ticenter study. JAMA. 2005;294:813Y818. bined with a rigorous method for prospective data collection 4. Dennen P, Douglas IS, Anderson R. Acute kidney injury in the intensive ensure a high quality of data to characterize AKI in surgical care unit: an update and primer for the intensivist. Crit Care Med. 2010; sepsis. In our patients, it can also be clinically challenging 38:261Y275. 5. Moore LJ, Moore FA, Jones SL, Xu J, Bass BL. Sepsis in general surgery: to distinguish prerenal azotemia from true AKI; however, Y the RIFLE criteria allow for the development of AKI during a deadly complication. Am J Surg. 2009;198:868 874. 6. Moore LJ, Moore FA, Todd SR, Jones SL, Turner KL, Bass BL. Sepsis in a 7-day period, thus capturing AKI occurring after adequate general surgery: the 2005Y2007 national surgical quality improvement volume resuscitation, a clinical outcome target, which has program perspective. Arch Surg. 2010;145:695Y700. been validated by our computerized clinical decision support 7. Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P. Acute renal system in our patients with surgical sepsis.5 Our patients av- failureVdefinition, outcome measures, animal models, fluid therapy and eraged 59 years of age and were mostly white, a demographic information technology needs: the Second International Consensus Con- which may not mirror all other surgical ICUs. In addition, the ference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care. 2004;8:R204YR212. clinical diagnosis of severe sepsis and septic shock includes 8. Costantini TW, Fraga G, Fortlage D, Wynn S, Fraga A, Lee J, et al. Re- evidence of acute organ decompensation such as renal dys- defining renal dysfunction in trauma: implementation of the Acute Kidney function; however, the RIFLE classification is more inclusive. Injury Network staging system. J Trauma. 2009;67:283Y287; discussion The ACCP/SCCM SCr criteria for renal dysfunction in severe 287Y288. sepsis/septic shock specifiesanincreaseinSCrequalto 9. Shiao CC, Wu VC, Li WY, Lin YF, Hu FC, YoungGH, et al. Late initiation or greater than 0.5 mg/dL from baseline measured within of renal replacement therapy is associated with worse outcomes in acute 24 hours of sepsis resuscitation as opposed to the 1.5 times kidney injury after major abdominal surgery. Crit Care. 2009;13:R171. 18,19 10. Hobson CE, Yavas S, Segal MS, Schold JD, Tribble CG, Layon AJ, et al. increase for RIFLE. Therefore, RIFLE criteria captures Acute kidney injury is associated with increased long-term mortality after more patients with AKI who had reference creatinine level cardiothoracic surgery. Circulation. 2009;119:2444Y2453. of less than 1.0 mg/dL, commonly found in elderly patients 11. Bihorac A, Yavas S, Subbiah S, Hobson CE, Schold JD, Gabrielli A, et al. and women. Accordingly, RIFLE criteria identified a high Long-term risk of mortality and acute kidney injury during hospitalization incidence of AKI (59%) in patients with surgical sepsis who after major surgery. Ann Surg. 2009;249:851Y858. lacked evidence of baseline organ dysfunction per the ACCP/ 12. Berenholtz SM, Pronovost PJ, Ngo K, Barie PS, Hitt J, Kuti JL, et al. Developing quality measures for sepsis care in the ICU. Jt Comm J Qual SCCM definitions. Patient Saf. 2007;33:559Y568. In conclusion, AKI frequently complicates surgical sepsis 13. Dellinger RP, Levy MM, Carlet JM, Bion J, Parker MM, Jaeschke R, et al. and serves as a powerful predictor of patient morbidity and Surviving Sepsis Campaign: international guidelines for management of mortality. Using defined consensus criteria to identify early severe sepsis and septic shock: 2008. Crit Care Med. 2008;36:296Y327. AKI may facilitate goal-directed therapy and reduce morbidity 14. Hollenberg SM, Ahrens TS, Annane D, Astiz ME, Chalfin DB, Dasta JF, and mortality in patients with surgical sepsis. et al. Practice parameters for hemodynamic support of sepsis in adult patients: 2004 update. Crit Care Med. 2004;32:1928Y1948. 15. Moore LJ, Jones SL, Kreiner LA, McKinley B, Sucher JF, Todd SR, et al. AUTHORSHIP Validation of a screening tool for the early identification of sepsis. J Trauma. 2009;66:1539Y1546; discussion 1546Y1547. L.E.W. and A.B. conducted the literature search for this study, which 16. McKinley BA, Moore LJ, Sucher JF,Todd SR, Turner KL, Valdivia A, et al. H.T.H., A.B., L.J.M., B.A.M., and F.A.M. designed. L.E.W., M.S., B.A.M., Computer protocol facilitates evidence-based care of sepsis in the surgical Y and A.V. contributed to data collection. L.E.W., H.T.H., A.B., M.S., and intensive care unit. J Trauma. 2011;70:1153 1167. B.A.M. analyzed the data, which H.T.H., A.B., L.J.M., M.S., and F.A.M. 17. Moore LJ, Turner KL, Todd SR, McKinley B, Moore FA. Computerized interpreted. L.E.W., H.T.H., and F.A.M. wrote the manuscript. L.E.W. clinical decision support improves mortality in intra abdominal surgical prepared the tables. sepsis. Am J Surg. 2010;200:839Y843; discussion 843Y844. 18. Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, et al. Definitions for sepsis and organ failure and guidelines for the use of in- novative therapies in sepsis. The ACCP/SCCM Consensus Conference DISCLOSURE Committee. American College of Chest Physicians/Society of Critical Care Medicine. 1992. Chest. 1992;136(Suppl 5):e28. H.T.H. received support by grants from the NIH/NHLBI (KO8HL089181) 19. Moore LJ, McKinley BA, Turner KL, Todd SR, Sucher JF,Valdivia A, et al. and the American Vascular Association/American College of Surgeons The epidemiology of sepsis in general surgery patients. J Trauma. 2011;70: Lifeline award; A.B. received support from NIH NIGMS Grant K23 672Y680. GM087709; F.A.M. received research support from the Methodist 20. 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