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      Acute Kidney Injury Ascertainment Is Affected by the Use of First Inpatient Versus Outpatient Baseline Serum Creatinine

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          Abstract

          To the Editor: An important methodological issue concerning acute kidney injury (AKI) definitions 1 is the choice of “baseline” serum creatinine (SCr).2, 3, 4 The most recent consensus definition proposes a rolling 48-hour window for AKI ascertainment during hospitalization, or the use of a baseline value that is “known or presumed to have occurred in the past 7 days.” 1 However, significant misclassification in assigning AKI status can occur when admission or nadir inpatient SCr (as has been done in a number of studies) is used rather than a preadmission outpatient baseline. 4 A well-recognized concern with the use of admission SCr to define baseline kidney function is that it will be higher than a patient’s true baseline if community-acquired AKI is present, and therefore community-acquired AKI will be missed if the admission SCr is used to define baseline. However, animal and human studies have recently shown that creatinine generation can also quickly fall with acute illness, so falsely low readings may result.5, 6 It is unknown whether changes in creatinine generation affect AKI ascertainment. Therefore, to quantitate variation in first inpatient SCr level and the impact on AKI ascertainment (Figure 1a), we compared preadmission baseline and first inpatient SCr in a large, population-based, hospitalized cohort. We also identified predictors of lower first inpatient SCr. Figure 1 (a) Potential serum creatinine (SCr) trajectories and acute kidney injury (AKI) misclassification. The lack of a preadmission baseline SCr may lead to a failure to recognize AKI (green line); in this case, the first admission SCr is used as “baseline,” and criteria for AKI are not met despite the fact that the individual has community-acquired AKI. The use of nadir SCr (blue line) or first inpatient (red line) in the absence of a known baseline may lead to misclassification as AKI when no AKI is present. (b) Lower first inpatient SCr may lead to misclassification. Here, the use of first inpatient SCr (red line) in the absence of a known baseline may lead to misclassification as AKI when no AKI is present. The use of first inpatient SCr (orange line) may also lead to misclassification of AKI severity. We identified all hospitalized adults without end-stage renal disease at 21 Kaiser Permanente Northern California hospitals between 2006 and 2011 (Supplementary Figure S1); only the first eligible hospitalization per subject was included. Kaiser Permanente Northern California is a large integrated health care delivery system caring for > 4.1 million persons in the San Francisco Bay Area that is highly representative of the statewide population. 7 The study was approved by the institutional review boards of the Kaiser Foundation Research Institute and the University of California, San Francisco. Baseline SCr was the most recent outpatient SCr from a maximum of 365 days and a minimum of 7 days preadmission. 8 We selected this as the gold standard because this definition has been used in prior studies examining the impact of baseline SCr on AKI ascertainment, including the prospective Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) study.4, 8 A peak inpatient SCr ≥ 50% relative, ≥ 0.3 mg/dl absolute increase from the outpatient baseline, or need for acute dialysis defined AKI for this analysis. 1 Covariates included demographics, comorbidities, severity of illness, 9 preadmission estimated glomerular filtration rate (eGFR), and proteinuria. Comorbidities (diabetes, hypertension, cancer, coronary disease, chronic heart failure, prior ischemic stroke) were ascertained for up to 5 years before hospitalization using previously validated methods based on inpatient and ambulatory diagnoses and procedures, laboratory results, and pharmacy databases (codes available upon request).10, 11 We identified coronary revascularization, sepsis, and acute heart failure occurring during the index hospitalization using relevant diagnosis and procedure codes. To further describe acute severity of illness, we determined whether patients were admitted to the intensive care unit during their stay and calculated the Laboratory-based Acute Physiology Score (LAPS) and COmorbidity Point Score (COPS), along with a validated predicted mortality score based on automated inpatient, outpatient and laboratory data. 9 Preadmission eGFR (in ml/min per 1.73 m2) was estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation 12 and baseline SCr information described previously. We ascertained proteinuria based on a urine dipstick result of 1+ or greater (in the absence of a concomitant urinary tract infection). 10 The first inpatient SCr was expressed as a percentage change compared with baseline SCr. We used multivariable logistic regression to identify predictors of a first inpatient SCr that was < 90% of baseline SCr stratified by AKI status. Analyses were conducted using SAS version 9.3 (SAS Institute, Cary, NC). Of 214,802 eligible hospitalizations, 37,827 (17.6%) met our AKI criteria. AKI was associated with a higher prevalence of sepsis (20% vs. 7%), diabetes mellitus (40.3% vs. 26.3%), hypertension (79.5% vs. 65.5%), and chronic kidney disease (51.6% vs. 28.8%) (all P < 0.001) (Supplementary Table S1). Among all patients, 21.7% had a first inpatient SCr that was ≥ 110% above outpatient baseline (Table 1 and Figure 2). Not surprisingly, a greater proportion of patients with AKI (74.6%) experienced this pattern. Figure 2 Change between baseline and first inpatient serum creatinine (SCr) concentration, overall and stratified by acute kidney injury (AKI) status. Each column represents the proportion of individuals meeting those criteria. Table 1 Distribution of change between baseline and first inpatient serum creatinine (SCr) concentration, overall and stratified by acute kidney injury (AKI) statusa Ratio between first inpatient and outpatient baseline SCr Overall(N = 214,802) AKIb (n = 37,827) No AKI(n = 176,975) < 0.70 17,573 (8.2) 488 (1.3) 17,085 (9.7) 0.70–0.79 32,351 (15.1) 1056 (2.8) 31,295 (17.7) 0.80–0.89 47,202 (22.0) 1978 (5.3) 45,224 (25.6) 0.90–0.99 40,338 (18.8) 2618 (6.9) 37,720 (21.3) 1.00–1.09 30,745 (14.3) 3455 (9.1) 27,290 (15.4) 1.10–1.19 15,379 (7.2) 3459 (9.1) 11,920 (6.7) 1.20–1.29 8876 (4.1) 4015 (10.6) 4861 (2.7) 1.30–1.39 5119 (2.4) 3828 (10.1) 1291 (0.7) 1.40–1.49 3472 (1.6) 3183 (8.4) 289 (0.2) 1.50–1.99 7283 (3.4) 7283 (19.3) 0 (0.0) ≥ 2.00 6464 (3.0) 6464 (17.1) 0 (0.0) a Overall P value < 0.001. b It should be noted that among those with AKI, a ratio between first inpatient and outpatient baseline SCr > 1.1 may or may not meet criteria for AKI. For example if the baseline SCr is 1.0 mg/dl, 110% of baseline would be 1.1 mg/dl and would not meet criteria for AKI; such an individual might have evolving AKI and a subsequent rise in SCr that meets criteria for AKI. In contrast, if the baseline SCr is 3.1 mg/dl, 110% of baseline would be 3.41 mg/dl, and this individual would meet criteria for AKI, which would be community acquired. In all, 45% of the patients had a first inpatient SCr that was < 90% of the outpatient baseline; 9.4% of those with AKI experienced this pattern. Regardless of AKI status, older age, history of cancer, and intensive care unit admission were associated with a first inpatient SCr that was < 90% of outpatient baseline SCr (Table 2). Patients with diabetes mellitus, hypertension, sepsis, and greater severity of illness (measured by predicted mortality) were less likely to have a low first inpatient SCr, reflecting the fact that many of these patients present with AKI in evolution. It should be noted that several of these factors (e.g., sepsis and acute illness) are associated with acute reductions in creatinine generation, so the severity of AKI may be difficult to ascertain based on changes in SCr alone. In the future, novel biomarkers or real-time measurement of GFR may better define AKI severity. Table 2 Correlates of having a first inpatient serum creatinine (SCr) value < 90% of outpatient baselinea Characteristic AKI(n = 37,827) No AKI(n = 176,975) Age, yr  < 45 REF REF  45–74 1.53 (1.28–1.84) 1.33 (1.28–1.37)  ≥75 2.06 (1.71–2.50) 1.37 (1.32–1.43) Male gender 0.95 (0.88–1.02) 0.85 (0.83–0.87) Race/ethnicity  White REF REF  Black/African American 1.03 (0.92–1.16) 0.88 (0.85–0.91)  Asian/Pacific Islander 1.12 (1.00–1.26) 0.97 (0.94–1.00)  Other/unknown 199 (0.5) 891 (0.5) Medical history  Diabetes mellitus 0.82 (0.76–0.89) 0.93 (0.91–0.95)  Hypertension 0.90 (0.82–0.99) 0.92 (0.90–0.94)  Systemic cancer 1.26 (1.15–1.37) 1.06 (1.04–1.09)  Coronary heart disease 1.12 (0.97–1.28) 1.01 (0.96–1.05)  Chronic heart failure 0.99 (0.87–1.13) 0.91 (0.87–0.96)  Ischemic stroke 0.92 (0.71–1.19) 1.11 (1.03–1.19) During index hospitalization  Coronary revascularization 1.43 (1.24–1.63) 0.84 (0.80–0.88)  Sepsis 0.88 (0.80–0.97) 0.67 (0.65–0.70)  Heart failure 0.91 (0.78–1.05) 0.50 (0.48–0.53) Admitted to intensive care unit 2.33 (2.15–2.52) 1.26 (1.23–1.29) Predicted Mortality Score category  < 0.1% REF REF  0.1 to < 0.5% 1.08 (0.87–1.35) 0.94 (0.90–0.97)  0.5 to < 2% 1.04 (0.85–1.28) 0.89 (0.85–0.92)  2 to < 5% 0.83 (0.68–1.03) 0.84 (0.80–0.87)  5 to < 10% 0.61 (0.49–0.76) 0.74 (0.70–0.77)  10 to < 15% 0.44 (0.34–0.57) 0.70 (0.65–0.74)  15 to < 30% 0.39 (0.30–0.50) 0.70 (0.66–0.75)  ≥ 30% 0.23 (0.16–0.33) 0.54 (0.48–0.61)  Unknown 0.81 (0.64–1.04) 0.80 (0.76–0.84) Prior documented proteinuria 0.94 (0.84–1.04) 0.87 (0.84–0.90) Outpatient baseline eGFR  ≥ 60 ml/min per 1.73 m2 1.32 (0.81) 1.00 (0.39)  45–59 ml/min per 1.73 m2 1.03 (0.94–1.14) 1.38 (1.34–1.42)  30–44 ml/min per 1.73 m2 1.03 (0.92–1.14) 1.52 (1.47–1.57)  <30 ml/min per 1.73 m2 0.87 (0.76–0.99) 1.57 (1.49–1.67) eGFR, estimated glomerular filtration rate; REF, reference. Boldface data represent statistically significant associations. a Multivariable logistic regression was used to identify predictors of a first inpatient SCr < 90% of baseline and are expressed as odds ratios (95% confidence intervals). Our results have important implications for AKI ascertainment. Of the patients, 45% had a first inpatient SCr that was < 90% of the outpatient baseline. Consequently, using the first inpatient SCr in place of the outpatient baseline may misclassify some individuals as having AKI when no AKI is, in fact, present (as the SCr rises back to the actual baseline) (Figure 1b). In fact, in our study population, 6605 individuals would have met AKI criteria, had the first inpatient SCr been used in place of the outpatient baseline (Figure 3). The inclusion of patients without actual AKI because of this misclassification can bias associations between AKI and true AKI risk factors towards the null. Even among those who met our criteria for AKI, nearly 1 in 12 had a first inpatient SCr that was < 90% of outpatient baseline; here, using an inpatient SCr that is lower than outpatient baseline may lead to misclassification of AKI severity. In contrast, using the outpatient baseline SCr identified 21,864 individuals who were not identified as having AKI using the first inpatient SCr, likely due to the presence of community-acquired AKI. A total of 15,963 individuals were identified as having AKI using either the outpatient baseline or first inpatient SCr. Thus, the overall incidence of AKI was higher when the outpatient baseline SCr was used (37,827 vs. 22,568). Figure 3 Differences in acute kidney injury (AKI) ascertainment when the outpatient baseline or first inpatient serum creatinine (SCr) are used to ascertain AKI status. A total of 37,827 individuals met criteria for AKI using the outpatient baseline SCr as described (red circle); of these individuals, only 15,963 would have been identified, had the first inpatient SCr been used to define baseline due to the presence of AKI at hospital admission (overlap between blue and red circle). Due to the variation described in this analysis (with a large proportion of individuals presenting with an SCr below their outpatient baseline), an additional 6605 individuals would have been misclassified as having AKI, had the first inpatient SCr been used to define AKI. We note that, in some populations (i.e., those of older age and with cancer), the first inpatient SCr was more likely to be <90% of preadmission baseline, as might be expected, as these conditions are more likely to be associated with reductions in muscle mass over time. Further studies are needed to better understand whether these differences reflect ongoing malnutrition due to chronic illness, and, if so, how best to estimate baseline SCr in these populations. In clinical practice, careful evaluation of both the outpatient baseline SCr and first inpatient SCr in these populations who are more likely to have a low first inpatient SCr is warranted to help with the clinical ascertainment of AKI. Due to the presence of community-acquired AKI at admission, a significant proportion of patients who met our AKI definition would not have met criteria for AKI had the first inpatient SCr been used as baseline (Figure 3). Study strengths include the large number of patients with outpatient baseline SCr measurements within an integrated health care delivery system, which allowed for analysis of patient-level factors stratified by AKI status, an important determinant of admission SCr. Kaiser Permanente Northern California is highly representative of the local and statewide population, so results are likely more generalizable than those from specialized populations (e.g., the predominantly male Veterans Affairs population). A potential limitation is that we focused on individuals with an available outpatient SCr, so no inferences can be made about how to estimate baseline SCr without outpatient data. In those circumstances, given the importance of baseline SCr for AKI classification 4 and given the variation between first inpatient and outpatient baseline SCr that we have shown, clinicians should use all available resources to identify an outpatient baseline SCr. Disclosure All the authors declared no competing interests.

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          Estimating baseline kidney function in hospitalized patients with impaired kidney function.

          Inaccurate determination of baseline kidney function can misclassify acute kidney injury (AKI) and affect the study of AKI-related outcomes. No consensus exists on how to optimally determine baseline kidney function when multiple preadmission creatinine measurements are available. The accuracy of commonly used methods for estimating baseline serum creatinine was compared with that of a reference standard adjudicated by a panel of board-certified nephrologists in 379 patients with AKI or CKD admitted to a tertiary referral center. Agreement between estimating methods and the reference standard was highest when using creatinine values measured 7-365 days before admission. During this interval, the intraclass correlation coefficient (ICC) for the mean outpatient serum creatinine level (0.91 [95% confidence interval (CI), 0.88-0.92]) was higher than the most recent outpatient (ICC, 0.84 [95% CI, 0.80-0.88]; P<0.001) and the nadir outpatient (ICC, 0.83 [95% CI, 0.76-0.87; P<0.001) serum creatinine. Using the final creatinine value from a prior inpatient admission increased the ICC of the most recent outpatient creatinine method (0.88 [95% CI, 0.85-0.91]). Performance of all methods declined or was unchanged when the time interval was broadened to 2 years or included serum creatinine measured within a week of admission. The mean outpatient serum creatinine measured within a year of hospitalization most closely approximates nephrologist-adjudicated serum creatinine values.
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            Risk-adjusting hospital inpatient mortality using automated inpatient, outpatient, and laboratory databases.

            To develop a risk-adjustment methodology that maximizes the use of automated physiology and diagnosis data from the time period preceding hospitalization. : Retrospective cohort study using split-validation and logistic regression. Seventeen hospitals in a large integrated health care delivery system. Patients (n = 259,699) hospitalized between January 2002 and June 2005. Inpatient and 30-day mortality. Inpatient mortality was 3.50%; 30-day mortality was 4.06%. We tested logistic regression models in a randomly chosen derivation dataset consisting of 50% of the records and applied their coefficients to the validation dataset. The final model included sex, age, admission type, admission diagnosis, a Laboratory-based Acute Physiology Score (LAPS), and a COmorbidity Point Score (COPS). The LAPS integrates information from 14 laboratory tests obtained in the 24 hours preceding hospitalization into a single continuous variable. Using Diagnostic Cost Groups software, we categorized patients as having up to 40 different comorbidities based on outpatient and inpatient data from the 12 months preceding hospitalization. The COPS integrates information regarding these 41 comorbidities into a single continuous variable. Our best model for inpatient mortality had a c statistic of 0.88 in the validation dataset, whereas the c statistic for 30-day mortality was 0.86; both models had excellent calibration. Physiologic data accounted for a substantial proportion of the model's predictive ability. Efforts to support improvement of hospital outcomes can take advantage of risk-adjustment methods based on automated physiology and diagnosis data that are not confounded by information obtained after hospital admission.
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              Commonly used surrogates for baseline renal function affect the classification and prognosis of acute kidney injury.

              Studies of acute kidney injury usually lack data on pre-admission kidney function and often substitute an inpatient or imputed serum creatinine as an estimate for baseline renal function. In this study, we compared the potential error introduced by using surrogates such as (1) an estimated glomerular filtration rate of 75 ml/min per 1.73 m(2) (suggested by the Acute Dialysis Quality Initiative), (2) a minimum inpatient serum creatinine value, and (3) the first admission serum creatinine value, with values computed using pre-admission renal function. The study covered a 12-month period and included a cohort of 4863 adults admitted to the Vanderbilt University Hospital. Use of both imputed and minimum baseline serum creatinine values significantly inflated the incidence of acute kidney injury by about half, producing low specificities of 77-80%. In contrast, use of the admission serum creatinine value as baseline significantly underestimated the incidence by about a third, yielding a low sensitivity of 39%. Application of any surrogate marker led to frequent misclassification of patient deaths after acute kidney injury and differences in both in-hospital and 60-day mortality rates. Our study found that commonly used surrogates for baseline serum creatinine result in bi-directional misclassification of the incidence and prognosis of acute kidney injury in a hospital setting.
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                Author and article information

                Contributors
                Journal
                Kidney Int Rep
                Kidney Int Rep
                Kidney International Reports
                Elsevier
                2468-0249
                31 August 2017
                January 2018
                31 August 2017
                : 3
                : 1
                : 211-215
                Affiliations
                [1 ]Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
                [2 ]Departments of Epidemiology, Biostatistics and Medicine, University of California, San Francisco, San Francisco, California, USA
                [3 ]Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
                [4 ]Division of Nephrology, Kaiser Permanente Oakland Medical Center, Oakland, California, USA
                [5 ]Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA
                Author notes
                [] Corresponding author: Kathleen D. Liu, Division of Nephrology, Box 0532, University of California, San Francisco, San Francisco, CA 94143-0532.Division of NephrologyBox 0532, University of California, San FranciscoSan FranciscoCA 94143-0532 Kathleen.liu@ 123456ucsf.edu
                Article
                S2468-0249(17)30369-8
                10.1016/j.ekir.2017.08.011
                5762956
                29340333
                2891aca7-edda-49ae-9070-bbdef753b807
                © 2017 International Society of Nephrology. Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 21 March 2017
                : 31 July 2017
                : 21 August 2017
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                Research Letter

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