Study Population

This is a single-center retrospective study conducted at a tertiary referral hospital. We studied all adult patients (age ≥18 years) admitted to the ICU at Mayo Clinic in Rochester, MN, from January 1, 2011 through December 31, 2011. We included patients who had at least one SCr measured during the ICU admission. Patients with a history of stage 5 chronic kidney disease (CKD) or end-stage renal disease (ESRD), patients who received any dialysis modalities within 14 days prior to the ICU admission, and those who did not provide research authorization were excluded from the study. Stage 5 CKD and ESRD were identified based on ICD-9 code assignment (Additional file 1: Table S1) or baseline outpatient SCr-calculated eGFR of <15 ml/min/1.73 m2. For patients with multiple ICU admissions, only the first ICU admission during the study period was included in the analysis. This study was approved by the Mayo Clinic institutional review board.

We divided eligible patients into two groups, based on the availability of outpatient SCr between 365 and 7 days prior to hospital admission (Fig. 1). One group included patients without baseline outpatient SCr (n = 3504). This is the cohort of patients for whom the use of surrogates for baseline SCr was actually applied. This cohort was used to compare the incidence and outcomes of AKI using SCr GFR-75 versus SCr ADM in order to represent the real-world finding. The second group included patients with baseline outpatient SCr (n = 4268).

Fig. 1 Study inclusion and exclusion flow diagram Full size image

Simulated cohort

AKI diagnosis based on outpatient SCr baseline can be used as a reference standard to assess the sensitivity and specificity of AKI diagnosis using various surrogate estimates. However, due to significant differences in clinical characteristics between patients with and without outpatient SCr (Table 1), the finding in the cohort of patients with outpatient SCr might not be generalizable to patients without outpatient SCr. Therefore, we developed a propensity score model in which the outcome was whether baseline SCr was missing (n = 3504) or not (n = 4268) to predict the likelihood of missing baseline SCr. The propensity model included age, race, diabetes mellitus, hypertension, coronary artery disease, stroke, peripheral vascular disease, congestive heart failure, and APACHE III at ICU admission as covariates. We applied this model to the group of patients with baseline outpatient SCr and then selected patients with a propensity score of ≥0.354 (post-hoc cut-off) to generate a study cohort of patients with similar characteristics to patients whose baseline SCr was not available, while preserving known baseline SCr (n = 3566). We used this simulated cohort to analyze the sensitivity and specificity of AKI diagnosis based on different surrogates. AKI diagnosis based on outpatient SCr was used as the reference standard.

Table 1 Clinical characteristics and outcomes of eligible critically ill patients admitted to the ICU during the study period Full size table

Data collection

Clinical characteristics, demographic information, and laboratory data were collected using manual and automated retrieval from the institutional electronic medical records. We utilized data from the Mayo Clinic Life Science System (MCLSS) and the Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC) database. The MCLSS database contained demographic characteristics, clinical data, hospital admission information, diagnosis codes, procedure codes, laboratory test results, and flowsheet data of both in- and outpatients at our institution [21]. The METRIC database contained ICU admission information, pertinent vital signs, fluid input/output, and medication administration record data of all patients admitted in ICU at our institution [22]. Data variables collected included age, sex, race, known comorbidities at hospital admission, ICU type, severity of illness at ICU admission, ICU length of stay, and ICU discharge status. SCr measurements were collected for each eligible patient up to one year prior to ICU admission. The baseline outpatient SCr was defined as the most recent outpatient SCr measured between 365 and 7 days prior to the hospital admission. The eGFR was derived using the MDRD equation, with CKD being defined as a calculated eGFR of <60 ml/min/1.73 m2. We identified comorbidities from clinical notes in electronic medical record using a validated electronic note search strategy [21]. The severity of illness at ICU admission was evaluated using the Acute Physiology and Chronic Health Evaluation (APACHE) III score [23].

AKI diagnosis and classification

We identified and staged AKI based solely on the SCr criterion of the KDIGO definition [11]. AKI was defined as an increase in SCr in the ICU of ≥0.3 mg/dL or relative change of ≥50 % from the baseline. The baseline SCr was calculated using two different methods; 1) the first SCr available during hospital admission (SCr ADM ), and 2) an estimated SCr using the MDRD formula, based on an assumed GFR of 75 ml/min/1.73 m2 (SCr GFR-75 , as recommended by the ADQI working group). We used the following equation for backward calculation of SCr GFR-75 :

$$ \mathrm{S}\mathrm{C}{\mathrm{r}}_{\mathrm{GFR}\hbox{-} 75} = {\left(75/\left[186\ *\ \left(\mathrm{ag}{\mathrm{e}}^{\hbox{-} 0.203}\right)\ *\ \left(0.742\ \mathrm{f}\mathrm{o}\mathrm{r}\ \mathrm{women}\right)\ *\ \left(1.21\ \mathrm{f}\mathrm{o}\mathrm{r}\ \mathrm{black}\right)\right]\right)}^{\hbox{-} 0.887} $$

Clinical outcomes

The primary outcome was all-cause mortality at 60 days following ICU admission. We reviewed patient vital statistics by reviewing the patient registration and electronic medical records. In patients whose vital status at 60 days after ICU admission was unknown, the Social Security Death Index was used [24].

Statistical analysis

Continuous variables were reported as mean with standard deviation (SD) or median with interquartile range (IQR), as appropriate. All categorical variables were reported as counts with percentages. The difference in the AKI diagnosis using SCr ADM andSCr GFR-75 was assessed using McNemar’s test. The agreement of AKI diagnosis and staging, based on SCr ADM and SCr GFR-75 , was assessed using Cohen’s weighted kappa coefficient with linear weight between AKI stages. According to the results of AKI diagnosis, based on SCr ADM and SCr GFR-75 , we classified patients into 4 groups: (1) patients who had AKI regardless of baseline SCr calculation method, (2) patients who had AKI based only on SCr ADM , (3) patients who had AKI only based on SCr GFR-75 , and (4) patients who did not have AKI, regardless of baseline SCr determination methodology. We adjusted the odds ratio (OR) for age, ICU type, and APACHE III scores to assess 60-day mortality for the first three groups, using the fourth group as the reference group. The association between AKI stages and 60-day mortality was assessed using a logistic regression analysis. The predictive performance of the SCr criterion, using SCr ADM and SCr GFR-75 , for 60-day mortality was assessed by C-statistics, after which we compared their performances using Delong’s test. We calculated net reclassification improvement to evaluate how using SCr GFR-75 as baseline renal function for AKI diagnosis changed risk classification for 60-day mortality.

Sensitivities and specificities were compared using McNemar’s test. To determine the optimal GFR used for SCr estimation, we estimated based on an assumed GFR with an increment of 5 ml/min/1.73 m2, ranging from 30 to 120 ml/min/1.73 m2. The sensitivity and specificity of AKI diagnosis, according to the estimated SCr of each assumed GFR, was calculated using AKI diagnosis according to the baseline outpatient SCr as a reference standard. The Youden index, which yielded the highest sum of sensitivity and specificity, was used to identify the optimal GFR used for SCr estimation. The subgroup analyses, based on sex, age, and the presence of abnormal renal function at presentation, were performed to investigate the optimal GFR used in each subgroup. A two-sided p value of less than 0.05 was considered statistically significant. All analyses were performed using JMP statistical software (version 10.0, SAS, Cary, NC).