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      Trends in Hospitalizations for Acute Kidney Injury — United States, 2000–2014

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      , MD, PhD 1 , , , PhD 1 , , MPH 1
      Morbidity and Mortality Weekly Report
      Centers for Disease Control and Prevention

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          Abstract

          Acute kidney injury is a sudden decrease in kidney function with or without kidney damage, occurring over a few hours or days. Diabetes, hypertension, and advanced age are primary risk factors for acute kidney injury. It is increasingly recognized as an in-hospital complication of sepsis, heart conditions, and surgery ( 1 , 2 ). Its most severe stage requires treatment with dialysis. Acute kidney injury is also associated with higher likelihood of long-term care, incidence of chronic kidney disease and hospital mortality, and health care costs ( 1 , 2 ). Although a number of U.S. studies have indicated an increasing incidence of dialysis-treated acute kidney injury since the late 1990s ( 3 ), no data are available on national trends in diabetes-related acute kidney injury. To estimate diabetes- and nondiabetes-related acute kidney injury trends, CDC analyzed 2000–2014 data from the National Inpatient Sample (NIS) ( 4 ) and the National Health Interview Survey (NHIS) ( 5 ). Age-standardized rates of acute kidney injury hospitalizations increased by 139% (from 23.1 to 55.3 per 1,000 persons) among adults with diagnosed diabetes, and by 230% (from 3.5 to 11.7 per 1,000 persons) among those without diabetes. Improving both patient and provider awareness that diabetes, hypertension, and advancing age are frequently associated with acute kidney injury might reduce its occurrence and improve management of the underlying diseases in an aging population. Using 2000–2014 NIS data, CDC estimated the annual number of hospitalizations with acute kidney injury. NIS contains information from >7 million hospital stays from 44 states each year, estimated to represent >35 million hospitalizations nationally and >95% of the U.S. population ( 4 ). For this report, acute kidney injury hospitalizations were defined in two ways using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). All acute kidney injury was defined as the occurrence of at least one diagnostic code 584 (acute renal failure) or the occurrence of at least one procedure code of 39.95 (hemodialysis) or 54.98 (peritoneal dialysis). To exclude hospitalizations among patients with chronic renal failure on long-term dialysis, visits with the following procedural codes were excluded: V45.1 (renal dialysis status), V56.0 (encounter for dialysis and dialysis catheter care), V56.31 (encounter for adequacy testing for hemodialysis), V56.32 (encounter for adequacy testing for peritoneal dialysis), and V56.8 (other dialysis). Dialysis-treated acute kidney injury was defined by a diagnostic code 584 and a procedure code (39.95 or 54.98), also excluding the V-codes specified above. Hospitalizations were considered to be diabetes-related if diabetes (ICD-9-CM code 250) was listed as a diagnosis. The case definition included any hospitalization with a code for acute kidney injury regardless of cause of hospitalization. NHIS is an annual, in-person household survey of the civilian, noninstitutionalized U.S. population that provides cross-sectional information on the health and use of health care services of the U.S. population. Data from the 2000–2014 NHIS were used to estimate the number of U.S. residents aged ≥20 years with and without diabetes. Diabetes was defined as a “yes” response to the question “Other than during pregnancy, have you ever been told by a doctor or health professional that you have diabetes or sugar diabetes?” All acute kidney injury hospitalizations and dialysis-treated acute kidney injury hospitalizations per 1,000 persons (with and without diabetes) were calculated by dividing the estimated number of acute kidney injury hospitalizations (from NIS) by the estimated population aged ≥20 years with and without diabetes (from NHIS). Trends in all and dialysis-treated acute kidney injury were examined by sex and standardized to the 2000 U.S. standard population. Statistical software was used to obtain point estimates and standard errors based on the Taylor series linearization method and to account for complex sampling designs. Ordinary least squares regression assessed trends over time, reported as p-value for trend with two-sided significance determined as p<0.05. The total number of hospitalizations with acute kidney injury increased from 953,926 in 2000 to 1,823,054 in 2006 and 3,959,560 in 2014 (Table). Diabetes was an associated comorbidity in 38%, 37%, and 40% of all hospitalizations in these years, respectively. During 2000–2014, the rate of all acute kidney injury hospitalizations among persons with diabetes increased by 139%, from 23.1 to 55.3 per 1,000 persons and by 230% among persons without diabetes, from 3.5 to 11.7 per 1,000 persons (both p<0.001) (Table). Similar patterns were seen for dialysis-treated acute kidney injury, but absolute rates were lower. TABLE Age-standardized rate* of hospitalization with acute kidney injury† and dialysis-treated acute kidney injury§ among men and women aged ≥20 years with and without diagnosed diabetes, by sex and diabetes status — United States, 2000, 2006, and 2014 Characteristic 2000 2006 2014¶ Absolute change (95% CI) Percent change(95% CI) All persons with diagnosed diabetes Weighted no. 11,863,011 17,109,522 21,871,994 — — All acute kidney injury (no.) 364,527 666,060 1,571,265 — — Hospitalization rate (95% CI) 23.1 (21.5 to 24.8) 28.5 (27.0 to 29.9) 55.3 (54.1 to 56.6) 32.2 (30.1 to 34.3) 139.2 (121.1 to 157.3) Dialysis-treated acute kidney injury (no.) 4,108 6,300 11,380 — — Hospitalization rate (95% CI) 0.3 (0.1 to 0.6) 0.29 (0.1 to 0.5) 0.4 (0.2 to 0.7) 0.1 (0.0 to 0.5) 56.7 (-149.7 to 263.0) Men with diagnosed diabetes Weighted no. 5,907,203 8,203,503 10,907,239 — — All acute kidney injury 169,589 334,765 830,155 — — Hospitalization rate (95% CI) 23.0 (21.3 to 24.7) 31.5 (29.6 to 32.7) 60.9 (59.6 to 62.2) 37.9 (35.8 to 40.0) 164.6 (144.6 to184.6) Dialysis-treated acute kidney injury (no.) 2,077 3,425 6,410 — — Hospitalization rate (95% CI) 0.3 (0.0 to 0.6) 0.3 (0.1 to 0.6) 0.5 (0.2 to 0.7) 0.2 (0.0 to 0.6) 67.8 (-145.0 to 280.6) Women with diagnosed diabetes Weighted no. 5,955,808 8,906,019 10,964,755 — — All acute kidney injury (no.) 194,938 331,295 741,110 — — Hospitalization rate (95% CI) 23.2 (21.6 to 24.9) 25.8 (24.4 to 27.1) 49.7 (48.6 to 50.9) 26.5 (24.5 to 28.5) 114.0 (97.8 to 130.3) Dialysis-treated acute kidney injury (no.) 2,031 2,875 4,970 — — Hospitalization rate (95% CI) 0.2 (0.0 to 0.5) 0.2 (0.02 to 0.5) 0.3 (0.1 to 0.6) 0.1 (0.0 to 0.5) 43.6 (-154.8 to 242.0) All persons without diagnosed diabetes Weighted no. 189,675,970 202,950,590 217,677,095 — — All acute kidney injury (no.) 589,399 1,156,994 2,388,295 — — Hospitalization rate (95% CI) 3.5 (2.4 to 3.7) 6.5 (6.3 to 6.7) 11.7 (11.5 to 11.8) 8.1 (7.9 to 8.3) 230.4 (216.1 to 244.7) Dialysis-treated acute kidney injury (no.) 8,137 12,219 16,695 — — Hospitalization rate (95% CI) 0.1 (0.02 to 0.1) 0.1 (0.04 to 0.1) 0.08 (0.1 to 0.1) 0.03 (0 to 0.07) 64.1 (-37.4 to 165.6) Men without diagnosed diabetes Weighted no. 90,661,859 97,967,409 104,570,034 — — All acute kidney injury 316,980 617,208 1,282,955 — — Hospitalization rate (95% CI) 4.2 (4.1 to 4.4) 7.7 (7.5 to 8.0) 13.8 (13.6 to 14.0) 9.6 (9.3 to 9.8) 225.5 (212.0 to 239.1) Dialysis-treated acute kidney injury (no.) 4,791 7,107 9,860 — — Hospitalization rate (95% CI) 0.06 (0.03 to 0.1) 0.1 (0.05 to 0.1) 0.1 (0.07 to 0.13) 0.04 (0.0 to 0.08) 61.9 (-29.0 to 152.8) Women without diagnosed diabetes Weighted no. 99,014,111 104,983,181 113,107,061 — — All acute kidney injury (no.) 272,419 539,786 1,105,340 — — Hospitalization rate (95% CI) 2.8 (2.7 to 2.9) 5.2 (5.0 to 5.4) 9.5 (9.4 to 9.6) 6.7 (6.5 to 6.9) 237.7 (222.2 to 253.2) Dialysis-treated acute kidney injury (no.) 3,346 5,112 6,835 — — Hospitalization rate (95% CI) 0.03 (0.01 to 0.1) 0.1 (0.03 to 0.07) 0.06 (0.01 to 0.08) 0.02 (0.0 to 0.05) 68.0 (-52.8 to 188.8) Abbreviation: CI = confidence interval. *Rate per 1000 population and age-standardized based on the 2000 U.S. standard population. † Acute kidney injury identified based on the following International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9 CM) codes: at least one diagnostic code 584 (acute renal failure) or at least one procedure code of 39.95 (hemodialysis) or 54.98 (peritoneal dialysis) and excluding the following codes: V45.1 (renal dialysis status), V56.0 (encounter for dialysis and dialysis catheter care), V56.31 (encounter for adequacy testing for hemodialysis), V56.32 (encounter for adequacy testing for peritoneal dialysis), and V56.8 (other dialysis). § Dialysis-treated acute kidney injury identified based on the following ICD-9 CM codes: at least one diagnostic code 584 (acute renal failure) and at least one procedure code of 39.95 (hemodialysis) or 54.98 (peritoneal dialysis), and excluding the following codes: V45.1 (renal dialysis status), V56.0 (encounter for dialysis and dialysis catheter care), V56.31 (encounter for adequacy testing for hemodialysis), V56.32 (encounter for adequacy testing for peritoneal dialysis), and V56.8 (other dialysis). ¶ All p-values for trend <0.001. The increased rates of acute kidney injury hospitalizations affected both men and women with diabetes. Rates increased 165%, from 23.0 to 60.9 per 1,000 persons (p<0.001) among men and increased 114%, from 23.2 to 49.7 (p<0.001) among women (Figure 1) (Table). Among persons without diabetes, the rate increases were greater (226%, from 4.2 to 13.8 per 1,000 men and 238%, from 2.8 to 9.5 per 1,000 women; p<0.001); however, overall rates were substantially lower (Figure 1) (Table). FIGURE 1 Age-standardized incidence* of hospitalizations with acute kidney injury† among men and women aged ≥20 years with and without diabetes — United States, 2000–2014 * Age-standardized based on the 2000 U.S. standard population. † Acute kidney injury identified by the following International Classification of Diseases, Ninth Revision, Clinical Modification codes: at least one diagnostic code of 584 or at least one procedure code of 39.95 or 54.98 and excluding the following codes: V45.1, V56.0, V56.31, V56.32, and V56.8 00–2014. The figure is a line graph showing age-standardized incidence of hospitalizations with acute kidney injury among men and women aged ≥20 years with and without diabetes in the United States, during 2000–2014. Hospitalization rates for dialysis-treated acute kidney injury increased among men and women with diabetes by 68% (from 0.3 to 0.5 per 1,000 men, p<0.001) and 44% (from 0.2 to 0.3 women, p<0.001), respectively (Figure 2) (Table). Among men and women without diabetes, the rates of dialysis-treated acute kidney injury hospitalizations were much lower, but a significant increasing trend was also observed (both p<0.001) (Figure 2) (Table). FIGURE 2 Age-standardized incidence* of hospitalizations with dialysis-treated acute kidney injury† among men and women aged ≥20 years with and without diagnosed diabetes — United States, 2000–2014 * Age-standardized based on the 2000 U.S. standard population. † Acute kidney injury identified by the following International Classification of Diseases, Ninth Revision, Clinical Modification codes: at least one diagnostic code of 584 and at least one procedure code of 39.95 or 54.98 and excluding the following codes: V45.1, V56.0, V56.31, V56.32, and V56.8. The figure is a line graph showing age-standardized incidence of hospitalizations with dialysis-treated acute kidney injury among men and women aged ≥20 years with and without diagnosed diabetes in the United States during 2000–2014. Discussion The present analysis of nationally representative hospitalization data indicates a substantial increase in the rate of hospitalizations for acute kidney injury in men and women in the United States from 2000 to 2014, irrespective of diabetes status. Compared with persons with diabetes, acute kidney injury hospitalization rates among persons without diabetes were much lower, but the observed relative increase was larger (230% versus 139%). However, the absolute changes were much higher in persons with diabetes than in those without diabetes; persons with diabetes are nearly four times more likely to have acute kidney injury hospitalizations than are persons without diabetes. A similar absolute difference was found for dialysis-treated acute kidney injury. The findings in this report corroborate previous reports from the United States and other countries. In the United States, unadjusted rates of first acute kidney injury hospitalization in the Medicare population with diabetes increased from 29 per 1,000 person-years in 2004 to 51 in 2014 ( 2 ). Among commercially insured patients aged 22–65 years with diabetes, the rate increased from 9.6 in 2005 to 15 in 2014 ( 2 ). Similar trends for the overall population (with and without diabetes) were reported for other large health care delivery systems such as Kaiser Permanente of Northern California ( 6 ). Studies in countries with national health care systems showed that dialysis-treated acute kidney injury increased more than thirteenfold in England during 1998–2013 ( 7 ), with the steepest increase among patients in intensive care units, and nearly threefold in Denmark during 2000–2012, particularly among elderly patients and those with multiple comorbidities ( 8 ). This suggests that acute kidney injury is on the rise in many counties, regardless of the health care system. The increasing rates of acute kidney injury hospitalizations contrast with recently published data for other diabetes-related acute and chronic complications in the United States. A nationwide analysis of trends in five diabetes-related complications, including acute myocardial infarction, stroke, amputations, end-stage renal disease, and deaths from hyperglycemic crisis, indicated that rates of most complications declined during 1990–2010 ( 9 ). This suggests that increased survival among patients with diabetes, coinciding with a rise in other complications, such as septicemia, shock, congestive heart failure, and liver disease, might be contributing to higher rates of acute kidney injury hospitalizations ( 10 ). The findings in this report are subject to at least three limitations. First, NIS data represent the number of acute kidney injury discharge diagnoses per hospital stay, not per patient. Therefore, a patient with multiple admissions during a given year might be counted several times, leading to an overestimate of the acute kidney injury incidence rate. Conversely, using administrative codes to ascertain acute kidney injury likely results in an underestimation of acute kidney injury cases caused by underrecognition and underdiagnosis. Generally, studies using change in laboratory measures, such as serum creatinine and urinary output, to define acute kidney injury provide much higher estimates of acute kidney injury incidence than those using ICD codes ( 3 ). Second, trends in hospitalizations with acute kidney injury codes might be influenced by changes in acute kidney injury definition ( 11 ), increased awareness of acute kidney injury, and changes in clinical practice over time. Data to examine these factors and their influence on hospitalizations with acute kidney injury were not available; however, the observed increases in dialysis-treated acute kidney injury might be less influenced by these factors and suggest a real increase in incidence of acute kidney injury hospitalizations over time. Finally, these data did not permit differentiation between diabetes types and diabetes duration, both of which could affect acute kidney injury hospitalizations. Acute kidney injury increases the risk of developing or exacerbating underlying chronic kidney disease (gradual loss of kidney function over time). National health (Healthy People 2020; https://www.healthypeople.gov ) objectives call for renal evaluation of patients hospitalized for acute kidney injury 6 months after discharge to monitor kidney function and prevent or delay onset of chronic kidney disease. CDC’s Chronic Kidney Disease Surveillance System monitors the prevalence of chronic kidney disease and its risk factors (including acute kidney injury) in the U.S. population and tracks progress in its prevention, management, and control. Improving both patient and provider awareness that diabetes, hypertension, and advancing age are frequently associated with acute kidney injury is important for reversing these trends. Elderly persons have physiologically reduced kidney function and functional reserve with the appearance of global sclerosis, but also more comorbidity than do young adults, all of which heighten older persons’ susceptibility to nephrotoxic medicines, dyes used for imaging, and even dehydration, all preventable risks for acute kidney injury. Better recognition of risk factors for acute kidney injury by health care providers might improve the effectiveness of treatment of underlying conditions and prevent or mitigate additional kidney insult to patients, particularly among those hospitalized or in long-term care. Summary What is already known about this topic? Clinicians increasingly recognize acute kidney injury as an in-hospital complication of sepsis, heart conditions, and surgery. It is associated with higher likelihood of long-term care, increased incidence of chronic kidney disease, increased hospital mortality, and higher health care costs. A number of U.S. studies have indicated an increasing incidence of dialysis-treated acute kidney injury since the late 1990s. What is added by this report? Analysis of data from the 2000–2014 National Inpatient Sample and the National Health Interview Surveys indicates a significant absolute and relative increase in hospitalization rates for acute kidney injury among men and women in the United States. Hospitalization for acute kidney injury among persons with diabetes accounted for approximately 40% of all such hospitalizations; absolute increases in hospitalization rates among persons with diabetes were larger than those among persons without diabetes. What are the implications for public health and health care practice? Diabetes is a known risk factor for acute kidney injury. The increasing number of persons living with diabetes is likely to also increase the number of persons with acute kidney injury. Improved awareness by health care providers that diabetes, hypertension, and advanced age are important risk factors for acute kidney injury might reduce its occurrence and improve management of the underlying diseases in an aging population.

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          Changes in diabetes-related complications in the United States, 1990-2010.

          Preventive care for adults with diabetes has improved substantially in recent decades. We examined trends in the incidence of diabetes-related complications in the United States from 1990 through 2010. We used data from the National Health Interview Survey, the National Hospital Discharge Survey, the U.S. Renal Data System, and the U.S. National Vital Statistics System to compare the incidences of lower-extremity amputation, end-stage renal disease, acute myocardial infarction, stroke, and death from hyperglycemic crisis between 1990 and 2010, with age standardized to the U.S. population in the year 2000. Rates of all five complications declined between 1990 and 2010, with the largest relative declines in acute myocardial infarction (-67.8%; 95% confidence interval [CI], -76.2 to -59.3) and death from hyperglycemic crisis (-64.4%; 95% CI, -68.0 to -60.9), followed by stroke and amputations, which each declined by approximately half (-52.7% and -51.4%, respectively); the smallest decline was in end-stage renal disease (-28.3%; 95% CI, -34.6 to -21.6). The greatest absolute decline was in the number of cases of acute myocardial infarction (95.6 fewer cases per 10,000 persons; 95% CI, 76.6 to 114.6), and the smallest absolute decline was in the number of deaths from hyperglycemic crisis (-2.7; 95% CI, -2.4 to -3.0). Rate reductions were larger among adults with diabetes than among adults without diabetes, leading to a reduction in the relative risk of complications associated with diabetes. When expressed as rates for the overall population, in which a change in prevalence also affects complication rates, there was a decline in rates of acute myocardial infarction and death from hyperglycemic crisis (2.7 and 0.1 fewer cases per 10,000, respectively) but not in rates of amputation, stroke, or end-stage renal disease. Rates of diabetes-related complications have declined substantially in the past two decades, but a large burden of disease persists because of the continued increase in the prevalence of diabetes. (Funded by the Centers for Disease Control and Prevention.).
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            Community-based incidence of acute renal failure.

            There is limited information about the true incidence of acute renal failure (ARF). Most studies could not quantify disease frequency in the general population as they are hospital-based and confounded by variations in threshold and the rate of hospitalization. Earlier studies relied on diagnostic codes to identify non-dialysis requiring ARF. These underestimated disease incidence since the codes have low sensitivity. Here we quantified the incidence of non-dialysis and dialysis-requiring ARF among members of a large integrated health care delivery system - Kaiser Permanente of Northern California. Non-dialysis requiring ARF was identified using changes in inpatient serum creatinine values. Between 1996 and 2003, the incidence of non-dialysis requiring ARF increased from 322.7 to 522.4 whereas that of dialysis-requiring ARF increased from 19.5 to 29.5 per 100,000 person-years. ARF was more common in men and among the elderly, although those aged 80 years or more were less likely to receive acute dialysis treatment. We conclude that the use of serum creatinine measurements to identify cases of non-dialysis requiring ARF resulted in much higher estimates of disease incidence compared with previous studies. Both dialysis-requiring and non-dialysis requiring ARFs are becoming more common. Our data underscore the public health importance of ARF.
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              Section 2: AKI Definition

              (2012)
              Chapter 2.1: Definition and classification of AKI INTRODUCTION AKI is one of a number of conditions that affect kidney structure and function. AKI is defined by an abrupt decrease in kidney function that includes, but is not limited to, ARF. It is a broad clinical syndrome encompassing various etiologies, including specific kidney diseases (e.g., acute interstitial nephritis, acute glomerular and vasculitic renal diseases); non-specific conditions (e.g, ischemia, toxic injury); as well as extrarenal pathology (e.g., prerenal azotemia, and acute postrenal obstructive nephropathy)—see Chapters 2.2 and 2.3 for further discussion. More than one of these conditions may coexist in the same patient and, more importantly, epidemiological evidence supports the notion that even mild, reversible AKI has important clinical consequences, including increased risk of death. 2, 5 Thus, AKI can be thought of more like acute lung injury or acute coronary syndrome. Furthermore, because the manifestations and clinical consequences of AKI can be quite similar (even indistinguishable) regardless of whether the etiology is predominantly within the kidney or predominantly from outside stresses on the kidney, the syndrome of AKI encompasses both direct injury to the kidney as well as acute impairment of function. Since treatments of AKI are dependent to a large degree on the underlying etiology, this guideline will focus on specific diagnostic approaches. However, since general therapeutic and monitoring recommendations can be made regarding all forms of AKI, our approach will be to begin with general measures. Definition and staging of AKI AKI is common, harmful, and potentially treatable. Even a minor acute reduction in kidney function has an adverse prognosis. Early detection and treatment of AKI may improve outcomes. Two similar definitions based on SCr and urine output (RIFLE and AKIN) have been proposed and validated. There is a need for a single definition for practice, research, and public health. 2.1.1: AKI is defined as any of the following (Not Graded): Increase in SCr by ⩾0.3 mg/dl (⩾26.5 μmol/l) within 48 hours; or Increase in SCr to ⩾1.5 times baseline, which is known or presumed to have occurred within the prior 7 days; or Urine volume 4.0 mg/dl (>354 μmol/l), rather than require an acute increase of ⩾0.5 mg/dl (⩾44 μmol/l) over an unspecified time period, we instead require that the patient first achieve the creatinine-based change specified in the definition (either ⩾0.3 mg/dl [⩾26.5 μmol/l] within a 48-hour time window or an increase of ⩾1.5 times baseline). This change brings the definition and staging criteria to greater parity and simplifies the criteria. Recommendation 2.1.2 is based on the RIFLE and AKIN criteria that were developed for average-sized adults. The creatinine change–based definitions include an automatic Stage 3 classification for patients who develop SCr >4.0 mg/dl (>354 μmol/l) (provided that they first satisfy the definition of AKI in Recommendation 2.1.1). This is problematic for smaller pediatric patients, including infants and children with low muscle mass who may not be able to achieve a SCr of 4.0 mg/dl (354 μmol/l). Thus, the pediatric-modified RIFLE AKI criteria 32 were developed using a change in estimated creatinine clearance (eCrCl) based on the Schwartz formula. In pRIFLE, patients automatically reach Stage 3 if they develop an eCrCl 26.5 μmol/l) [within 48 hours or a 50% increase from presumed baseline). Note that a patient can be diagnosed with AKI by fulfilling either criterion 1 or 2 (or 3, urine output) and thus cases B,C,D, and F all fulfill the definition of AKI. Note also that patients may be diagnosed earlier using criterion 1 or 2. Early diagnosis may improve outcome so it is advantageous to diagnose patients as rapidly as possible. For example, case A can be diagnosed with AKI on day 2 by the first criterion, whereas the second criterion is not satisfied until day 3 (increase from 1.3 to 1.9). However, this is only true because the episode of AKI began prior to medical attention, and thus the day 1 SCr level was already increased. If creatinine measurements had available with 48 hours prior to day 1 and if this level had been at baseline (1.0 mg/dl [88.4 μmol/l]), it would have been possible to diagnose AKI on day 1 using the second criterion. Cases F-H do not have a baseline measurement of SCr available. Elevated SCr (reduced eGFR) on day 1 of the hospitalization is consistent with either CKD or AKD without AKI. In Case F, baseline SCr can be inferred to be below the day 1 value because of the subsequent clinical course; thus, we can infer the patient has had an episode of AKI. In case G, AKI can be diagnosed by application of criterion 2, but the patient may have underlying CKD. Case H does not fulfill the definition for AKI based on either criteria, and has either CKD or AKD without AKI. The example of Case A raises several important issues. First, frequent monitoring of SCr in patients at increased risk of AKI will significantly improve diagnostic time and accuracy. If Case A had not presented to medical attention (or if SCr had not been checked) until day 7, the case of AKI would likely have been missed. Frequent measurement of SCr in high-risk patients, or in patients in which AKI is suspected, is therefore encouraged—see Chapter 2.3. The second issue highlighted by Case A is the importance of baseline SCr measurements. Had no baseline been available it would still have been possible to diagnose AKI on day 3 (by either using criterion 2 or by using criterion 1 and accepting the baseline SCr as 1.3); however, not only would this have resulted in a delay in diagnosis, it would have resulted in a delay in staging (see Table 7). On day 7, it can be inferred that the patient's baseline was no higher than 1.0 mg/dl (88 μmol/l) and thus correct staging of Case A as Stage 2 (two-fold increase from the reference SCr, see below and Table 7) on day 3 could have been determined in retrospect. However, if a baseline SCr was available to use as the reference, the correct stage could be determined on day 3. Case B illustrates why criterion 2 can detect cases of AKI missed by criterion 1. It also clarifies why these cases are unusual. Had the SCr increased to 1.5 mg/dl (132.6 μmol/l) as opposed to peaking at 1.4 mg/dl (123.8 μmol/l), it would have been picked up by criterion 1 as well. By contrast Cases C, D, and even F illustrate how criterion 2 may miss cases identified by criterion 1. Note that Case F can only be diagnosed by inference. By day 7, it can be inferred that the baseline was no higher than 1.0 mg/dl (88 μmol/l) and thus it can be determined that the patient presented with AKI. However, if the baseline SCr could be estimated it would be possible to make this inference as early as day 1. Estimating baseline SCr Many patients will present with AKI without a reliable baseline SCr on record. Baseline SCr can be estimated using the Modification of Diet in Renal Disease (MDRD) Study equation assuming that baseline eGFR is 75 ml/min per 1.73 m 2 (Table 9). 22 This approach has been used in many, but not all, studies of AKI epidemiology using RIFLE 2, 5, 25, 30, 31, 32, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63 (see Table 8) and has recently been validated. 64 Hence, most current data concerning AKI defined by RIFLE criteria are based on estimated baseline SCr for a large proportion of patients. Table 9 shows the range of estimated SCr obtained by back-calculation for various age, sex, and race categories. When the baseline SCr is unknown, an estimated SCr can be used provided there is no evidence of CKD (see Appendix B). Fortunately, when there is a history of CKD, a baseline SCr is usually available. Unfortunately, many cases of CKD are not identified, and thus estimating the baseline SCr may risk labeling a patient with AKI when in reality the diagnosis was unidentified CKD. As discussed further in Appendix B, it is essential to evaluate a patient with presumed AKI for presence of CKD. Furthermore, CKD and AKI may coexist. By using all available clinical data (laboratory, imaging, history, and physical exam) it should be possible to arrive at both an accurate diagnosis as well as an accurate estimate of baseline SCr. Importantly, excluding some cases of hemodilution secondary to massive fluid resuscitation (discussed below), the lowest SCr obtained during a hospitalization is usually equal to or greater than the baseline. This SCr should be used to diagnose (and stage) AKI. For example, if no baseline SCr was available in Case A, diagnosis of AKI could be made using the MDRD estimated SCr (Table 9). If Case A were a 70-year-old white female with no evidence or history of CKD, the baseline SCr would be 0.8 mg/dl (71 μmol/l) and a diagnosis of AKI would be possible even on day 1 (criterion 1, ⩾50% increase from baseline). However, if the patient was a 20-year-old black male, his baseline SCr would be estimated at 1.5 mg/dl (133 μmol/l). Since his admission SCr is lower, this is assumed to be the baseline SCr until day 7 when he returns to his true baseline, and this value can be taken as the baseline. These dynamic changes in interpretation are not seen in epidemiologic studies, which are conducted when all the data are present, but are common in clinical medicine. Note that the only way to diagnose AKI (by SCr criteria) in Case H is to use an estimated SCr. Examples of application of AKI stages Once a diagnosis of AKI has been made, the next step is to stage it (Recommendation 2.1.2). Like diagnosis, staging requires reference to a baseline SCr when SCr criteria are used. This baseline becomes the reference SCr for staging purposes. Table 10 shows the maximum stage for each Case described in Table 7. Staging for Case A was already mentioned. The maximum stage is 2 because reference SCr is 1.0 mg/dl (88 μmol/l) and the maximum SCr is 2.0 mg/dl (177 μmol/l). Had the reference SCr been 0.6 mg/dl (53 μmol/l), the maximum stage would have been 3. Case F was staged by using the lowest SCr (1.0 mg/dl [88 μmol/l]) as the reference. Of course, the actual baseline for this case might have been lower but this would not affect the stage, since it is already Stage 3. Note that if this patient was a 35-year-old white male, his MDRD estimated baseline SCr would be 1.2 mg/dl (106 μmol/l) (Table 9) and his initial stage on admission (day 1) would be assumed to be 2. However, once his SCr recovered to 1.0 mg/dl (88 μmol/l) on day 7, it would be possible to restage him as having had Stage 3. Once he has recovered, there may be no difference between Stage 2 or 3 in terms of his care plan. On the other hand, accurately staging the severity of AKI may be important for intensity of follow-up and future risk. Note that Cases G and H can only be staged if the reference SCr can be inferred. Case G may be as mild as stage 1 if the baseline is equal to the nadir SCr on day 7. On the other hand, if this case were a 70-year-old white female with no known evidence or history of CKD, the reference SCr would be 0.8 mg/dl (71 μmol/l) based on an estimated baseline (Table 9). In this case, the severity on day 1 would already be stage 2. Urine output vs. SCr Both urine output and SCr are used as measures of an acute change in GFR. The theoretical advantage of urine output over SCr is the speed of the response. For example, if GFR were to suddenly fall to zero, a rise in SCr would not be detectable for several hours. On the other hand, urine output would be affected immediately. Less is known about the use of urine output for diagnosis and staging compared to SCr, since administrative databases usually do not capture urine output (and frequently it is not even measured, especially outside the ICU). However, studies using both SCr and urine output to diagnose AKI show increased incidence, suggesting that the use of SCr alone may miss many patients. The use of urine output criteria (criterion 3) will also reduce the number of cases where criterion 1 and criterion 2 are discordant (cases B,C,D, and F in Table 7), as many of these cases will be picked up by urine output criteria. Timeframe for diagnosis and staging The purpose of setting a timeframe for diagnosis of AKI is to clarify the meaning of the word “acute”. A disease process that results in a change in SCr over many weeks is not AKI (though it may still be an important clinical entity: see Appendix B). For the purpose of this guideline, AKI is defined in terms of a process that results in a 50% increase in SCr within 1 week or a 0.3 mg/dl (26.5 μmol/l) increase within 48 hours (Recommendation 2.1.1). Importantly, there is no stipulation as to when the 1-week or 48-hour time periods can occur. It is stated unequivocally that it does not need to be the first week or 48 hours of a hospital or ICU stay. Neither does the time window refer to duration of the inciting event. For example, a patient may have a 2-week course of sepsis but only develop AKI in the second week. Importantly, the 1-week or 48-hour timeframe is for diagnosis of AKI, not staging. A patient can be staged over the entire episode of AKI such that, if a patient develops a 50% increase in SCr in 5 days but ultimately has a three-fold increase over 3 weeks, he or she would be diagnosed with AKI and ultimately staged as Stage 3. As with any clinical criteria, the timeframe for AKI is somewhat arbitrary. For example, a disease process that results in a 50% increase in SCr over 2 weeks would not fulfill diagnostic criteria for AKI even if it ultimately resulted in complete loss of kidney function. Similarly, a slow process that resulted in a steady rise in SCr over 2 weeks, and then a sudden increase of 0.3 mg/dl (26.5 μmol/l) in a 48-hour period, would be classified as AKI. Such are the inevitable vagaries of any disease classification. However, one scenario deserves specific mention, and that is the case of the patient with an increased SCr at presentation. As already discussed, the diagnosis of AKI requires a second SCr value for comparison. This SCr could be a second measured SCr obtained within 48 hours, and if it is ⩾0.3 mg/dl (⩾26.5 μmol/l) greater than the first SCr, AKI can be diagnosed. Alternatively, the second SCr can be a baseline value that was obtained previously or estimated from the MDRD equation (see Table 9). However, this poses two dilemmas. First, how far back can a baseline value be retrieved and still expected to be “valid” second, how can we infer acuity when we are seeing the patient for the first time? Both of these problems will require an integrated approach as well as clinical judgment. In general, it is reasonable in patients without CKD to assume that SCr will be stable over several months or even years, so that a SCr obtained 6 months or even 1 year previously would reasonable reflect the patient's premorbid baseline. However, in a patient with CKD and a slow increasing SCr over several months, it may be necessary to extrapolate the baseline SCr based on prior data. In terms of inferring acuity it is most reasonable to determine the course of the disease process thought to be causing the episode of AKI. For example, for a patient with a 5-day history of fever and cough, and chest radiograph showing an infiltrate, it would be reasonable to infer that the clinical condition is acute. If SCr is found to be ⩾50% increased from baseline, this fits the definition of AKI. Conversely, a patient presenting with an increased SCr in the absence of any acute disease or nephrotoxic exposure will require evidence of an acute process before a diagnosis can be made. Evidence that the SCr is changing is helpful in establishing acuity. Clinical judgment While the definitions and classification system discussed in Chapter 2.1 provide a framework for the clinical diagnosis of AKI, they should not be interpreted to replace or to exclude clinical judgment. While the vast majority of cases will fit both AKI diagnostic criteria as well as clinical judgment, AKI is still a clinical diagnosis—not all cases of AKI will fit within the proposed definition and not all cases fitting the definition should be diagnosed as AKI. However, exceptions should be very rare. Pseudo-AKI As with other clinical diagnoses defined by laboratory results (e.g., hyponatremia), the clinician must be cautious to interpret laboratory data in the clinical context. The most obvious example is with laboratory errors or errors in reporting. Erroneous laboratory values should obviously not be used to diagnose disease and suspicious lab results should always be repeated. Another example is when two SCr measurements are obtained by different laboratories. While the coefficient of variation for SCr is very small ( 60, indicating NKD. No indicates GFR <60, and based on prior level of GFR, may indicate stable, new, or worse CKD. Oliguria as a measure of kidney function Although urine flow rate is a poor measure of kidney function, oliguria generally reflects a decreased GFR. If GFR is normal (approximately 125 ml/min, corresponding to approximately 107 ml/kg/h for a 70-kg adult), then reduction in urine volume to <0.5 ml/kg/h would reflect reabsorption of more than 99.5% of glomerular filtrate. Such profound stimulation of tubular reabsorption usually accompanies circulatory disturbances associated with decreased GFR. Oliguria is unusual in the presence of a normal GFR and is usually associated with the non–steady state of solute balance and rising SCr sufficient to achieve the criteria for AKI. As a corollary, if GFR and SCr are normal and stable over an interval of 24 hours, it is generally not necessary to measure urine flow rate in order to assess kidney function. In principle, oliguria (as defined by the criteria for AKI) can occur without a decrease in GFR. For example, low intake of fluid and solute could lead to urine volume of less than 0.5 ml/kg/h for 6 hours or 0.3 ml/kg/h for 24 hours. On the other hand, severe GFR reduction in CKD usually does not lead to oliguria until after the initiation of dialysis. As described in Chapter 2.1, the thresholds for urine flow for the definition of AKI have been derived empirically and are less well substantiated than the thresholds for increase in SCr. Urinary diagnostic indices, such as the urinary concentrations of sodium and creatinine and the fractional reabsorption of sodium and urea, remain helpful to distinguish among causes of AKI, but are not used in the definition (see Appendix D). Kidney damage Table 13 describes measures of kidney damage in AKD and CKD. Kidney damage is most commonly ascertained by urinary markers and imaging studies. Most markers and abnormal images can indicate AKD or CKD, based on the duration of abnormality. One notable exception is small kidneys, either bilateral or unilateral, indicating CKD, which are discussed separately below. Kidney damage is not a criterion for AKI; however, it may be present. Renal tubular epithelial cells and coarse granular casts, often pigmented and described as “muddy brown”, remain helpful in distinguishing the cause of AKI, but are not part of the definition. Small kidneys as a marker of kidney damage Loss of renal cortex is considered a feature of CKD, and is often sought as a specific diagnostic sign of CKD. Kidney size is most often evaluated by ultrasound. In a study of 665 normal volunteers, 69 median renal lengths were 11.2 cm on the left side and 10.9 cm on the right side. Renal size decreased with age, almost entirely because of parenchymal reduction. The lowest 10th percentiles for length of the left and right kidney were approximately 10.5 and 10.0 cm, respectively, at age 30 years, and 9.5 and 9.0 cm, respectively, at age 70 years. Integrated approach to AKI, AKD, and CKD Clinical evaluation is necessary for all patients with alterations in kidney function or structure. The expectation of the Work Group is that the diagnostic approach will usually begin with assessment of GFR and SCr. However, evaluation of kidney function and structure is not complete unless markers of kidney damage—including urinalysis, examination of the urinary sediment, and imaging studies—have been performed. Table 14 shows a summary of the diagnostic approach using measures for kidney function and structure. Based on interpretation of each measure separately, the clinical diagnosis indicated by an “X” can be reached. SPONSORSHIP KDIGO gratefully acknowledges the following sponsors that make our initiatives possible: Abbott, Amgen, Belo Foundation, Coca-Cola Company, Dole Food Company, Genzyme, Hoffmann-LaRoche, JC Penney, NATCO—The Organization for Transplant Professionals, NKF—Board of Directors, Novartis, Robert and Jane Cizik Foundation, Shire, Transwestern Commercial Services, and Wyeth. KDIGO is supported by a consortium of sponsors and no funding is accepted for the development of specific guidelines. DISCLAIMER While every effort is made by the publishers, editorial board, and ISN to see that no inaccurate or misleading data, opinion or statement appears in this Journal, they wish to make it clear that the data and opinions appearing in the articles and advertisements herein are the responsibility of the contributor, copyright holder, or advertiser concerned. Accordingly, the publishers and the ISN, the editorial board and their respective employers, office and agents accept no liability whatsoever for the consequences of any such inaccurate or misleading data, opinion or statement. While every effort is made to ensure that drug doses and other quantities are presented accurately, readers are advised that new methods and techniques involving drug usage, and described within this Journal, should only be followed in conjunction with the drug manufacturer's own published literature.
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                Author and article information

                Journal
                MMWR Morb Mortal Wkly Rep
                MMWR Morb. Mortal. Wkly. Rep
                WR
                Morbidity and Mortality Weekly Report
                Centers for Disease Control and Prevention
                0149-2195
                1545-861X
                16 March 2018
                16 March 2018
                : 67
                : 10
                : 289-293
                Affiliations
                [1 ]Division for Diabetes Translation, CDC.
                Author notes
                Corresponding author: Meda E. Pavkov, mpavkov@ 123456cdc.gov , 770-488-1160.
                Article
                mm6710a2
                10.15585/mmwr.mm6710a2
                5857198
                29543788
                dace56e9-a67f-41c9-81b0-2a1c80c3e5e9

                All material in the MMWR Series is in the public domain and may be used and reprinted without permission; citation as to source, however, is appreciated.

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