The Predictive Value of the Oxford Acute Disease Severity Score for Clinical Outcomes in Patients with Acute Kidney Injury: A Secondary Analysis of a Large Prospective Observational Study

Background: To compare the performance of the Oxford Acute Severity of Illness Score (OASIS), the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, the Simplied Acute Physiology Score II (SAPS II) and the Sequential Organ Failure Assessment (SOFA) score in predicting 28-day mortality in acute kidney injury (AKI) patients. Methods: Data were extracted from the Beijing Acute Kidney Injury Trial (BAKIT). 2,954 patients with complete clinical data were included in this study. We calculated the OASIS, APACHE II, SAPS II and SOFA within the rst day of ICU admission. Receiver operating characteristic (ROC) curves were used to analyse and evaluate the predictive effects of the four scoring systems on the 28-day mortality risk of AKI patients and each subgroup. The best cut-off value was identied by the highest combined sensitivity and specicity using Youden’s index. The signicance level was set at 5%. Results: Among the 2,954 patients, the 28-day mortality rate was 17.0% (501 patients died). The OASIS, APACHE II, SAPS II and SOFA of nonsurviving patients were higher than those of surviving patients with AKI. The 28-day mortality of AKI patients increased accordingly with the increase in OASIS. Among the four scoring systems, the area under the curve (AUC) of OASIS was the highest. The comparison of AUC values of different scoring systems showed that there were no signicant differences among OASIS, APACHE II and SAPS II, which were better than SOFA. Moreover, logistic analysis revealed that OASIS was an independent risk factor for 28-day mortality in AKI patients, whether as a continuous variable or a categorical variable. OASIS also had good performance in predicting ICU mortality and in-hospital mortality in AKI patients and had good predictive ability for the 28-day mortality of each subgroup of AKI patients. Conclusion: OASIS, and good discrimination and predicting the 28-day risk accuracy than

The Acute Physiology and Chronic Health Evaluation II (APACHE II) score is the most commonly used disease severity scoring system in ICUs around the world [5], it includes 12 physiological and laboratory parameters and two disease-related variables [6]. The Simpli ed Acute Physiology Score II (SAPS II) was rst described in 1984 as an alternative to the APACHE scoring system [7], and it is an effective tool for evaluating AKI patient outcomes [8,9]. However, all of the above models require considerable effort for data collection. Although the Sequential Organ Failure Assessment (SOFA) score [10] is simple to use and accurate in predicting the mortality outcome of AKI patients [11][12][13], it depends on laboratory results, and some important prognostic factors were not included.
In 2013, Johnson et al performed a retrospective cohort study of 72,474 ICU patients in 68 ICUs at 49 U.S. hospitals from 2007 to 2011 and developed a new reduced severity of illness score using machine learning algorithms, the Oxford Acute Severity of Illness Score (OASIS), which contained 10 parameters without any laboratory tests and had discrimination and calibration equivalent to more complex existing models [14].
The predictive value of OASIS was validated in mixed ICU patient populations, but its performance in AKI patients remains unknown. The aim of this multicentre study was to evaluate the performance of OASIS for the assessment of mortality in AKI patients in China.

Study setting and data collection
This study used a database from the Beijing Acute Kidney Injury Trial (BAKIT) [15], a prospective, multicentre, observational study that investigated the epidemiology of acute kidney injury (AKI) in critically ill patients in 30 ICUs at 28 tertiary hospitals in Beijing, China, conducted between March 1 and August 31, 2012 (for a complete list of these hospitals and the persons responsible for the data acquisition, see Additional le 1). The study subjects included all adult patients (age ≥ 18 years) admitted consecutively to the ICU. Only the initial ICU admission was considered in this study. The following patients were excluded: patients with preexisting end-stage chronic kidney disease, patients already receiving renal replacement therapy (RRT) before admission to the ICU, and patients who had received kidney transplantation in the previous 3 months [16]. Pre-existing comorbidities were diagnosed based on the International Classi cation of Diseases (ICD-10) codes. The patients were followed up until death, until hospital discharge, or for 28 days.
Thorough follow-up of all patients included in the study was conducted in the rst 10 days after ICU admission. The collected data included demographics, anthropometrics, admission diagnosis, comorbidities, daily vital signs and laboratory data (which were used to automatically calculate the APACHE II score, the SAPS II and the SOFA score), days from hospital to ICU admission, ICU length of stay (LOS), hospital LOS, use of vasoactive drugs, the occurrence of AKI, and length of mechanical ventilation (MV). RRT data were also reported.
Mortality data up to 28 days after ICU discharge were collected from hospital records, including records from hospital admissions and visits to outpatient clinics. AKI severity was classi ed according to the Kidney Disease Improving Global Outcomes (KDIGO) guidelines [17].
We calculated the OASIS within the rst day of ICU admission. The parameters used to calculate the OASIS are shown in Table S1.

Outcomes
The primary outcome was 28-day mortality, and the secondary outcomes were ICU mortality and hospital mortality. The ICU LOS and hospital LOS were calculated only for statistical description. ICU mortality and ICU LOS were determined by the rst ICU stay only.

Statistical analysis
Nonnormally distributed continuous variables are expressed as the medians with interquartile ranges (IQRs) and were compared using the Mann-Whitney U test or Kruskal-Wallis analysis-of-variance test with Bonferroni correction. Categorical variables are expressed as the number of cases and proportions and were compared using the Mantel-Haenszel chi-square test.
Receiver operating characteristic (ROC) curves were drawn according to the sensitivity and speci city of the four scoring systems for predicting the 28-day mortality risk of patients. The ROC curve comparison function of Medcalc software was used for pairwise comparisons of the area under the curve (AUC), the larger the AUC, the higher the predictive value. AUCs of ≥ 0.9, 0.8 to 0.89, 0.7 to 0.79, 0.6 to 0.69 or < 0.6 were classi ed as excellent, very good, good, fair, and poor, respectively [18].
Cut-off values, sensitivities, speci cities, positive predictive values and negative predictive values were calculated by ROC analysis. The best cut-off values for the prediction of 28-day mortality, ICU mortality and hospital mortality were determined by the maximum of the Youden index (i.e., sensitivity plus speci city minus one) calculated from the ROC analysis. The Hosmer-Lemeshow goodness-of-t test was used to test the calibration of the scoring system.
We used a logistic regression model to evaluate the effect of OASIS on the 28-day mortality in AKI patients. Because OASIS was collinear with APACHE II and SAPS II scores, the variables considered for multivariable analysis included age, sex, OASIS, SOFA, use of vasoactive drugs, MV, RRT and underlying diseases. OASIS was entered as a continuous variable and a categorical variable, respectively.
To verify the predictive effect of OASIS on the 28-day mortality of patients with different AKI grades and among different populations of AKI patients, subgroup analyses were performed by ROC analysis.
All statistical analyses were performed using SPSS software (IBM Corp., Statistics for Windows, version 22.0, Armonk, NY, USA), with a two-sided P values < 0.05 considered statistically signi cant.

Study population
During the study period, 9,079 patients were admitted consecutively. Of them, patients were excluded because of the following reasons: 5,725 patients had an ICU LOS of less than 24 hours, 110 patients were younger than 18 years old, one patient received renal transplantation during the past 3 months, 95 patients had received RRT before admission to the ICU, and 11 had insu cient clinical recordings. Thus, 3,107 patients were enrolled in the BAKIT study. Of these patients, 194 were excluded because of incomplete data for calculating OASIS, and nally, 2,954 patients were included in our study (Fig. 1).
Comparison of characteristics between the survival and nonsurvival groups of AKI patients AKI patient characteristics according to 28-day mortality are shown in Table 2. Nonsurviving AKI patients were older (P < 0.001), had higher illness severity scores and were more likely to be diagnosed with sepsis. Positive uid balance in the rst 24 hours was more common among nonsurvivors.

The 28-day Mortality Of Aki Patients According To Oasis
The distribution of OASIS in AKI patients is shown in Fig. 2. OASIS ranged from 6 to 64, and the median value was 31 (IQR: 24, 39). The distributions of the OASIS with corresponding 28-day mortality are also presented in Fig. 2. As each score increased, the 28-day mortality of AKI patients increased accordingly, indicating more serious illness and worse prognosis.
Comparison of ROC curve and AUCs of the four scoring systems in evaluating the 28-day mortality of AKI patients In Fig. 3 , respectively, which were higher than that of SOFA (0.686; P < 0.001). Table 3 shows the pairwise comparison of the ROC curves, and there were no statistically signi cant differences between the AUC values of OASIS, APACHE II, and SAPS II in predicting 28-day mortality. The predictive ability of OASIS, APACHE II, SAPS II and SOFA score for poor outcomes The ROC curves for the prediction of 28-day mortality, ICU mortality and in-hospital mortality by each severity scale are shown in Table 4. The sensitivities, speci cities, positive predictive values, and negative predictive values of the optimal cut-off values (from the Youden index) for each scale to predict the three outcomes are listed in Table 5. The cut-off value of OASIS for the prediction of 28-day mortality was 33 with a sensitivity of 87.75%and speci city of 46.26%, as calculated by the ROC curve analysis. OASIS ≥ 33 predicts poor short-term prognosis in patients with AKI.  were signi cantly associated with a higher risk of death in multivariable analysis. Multivariable logistic regression to assess the association of OASIS with 28-day mortality.
a. OASIS was entered as a continuous variable.
b. OASIS was entered as a categorical variable, the cut-off value of OASIS was 33.
AKI, acute kidney injury; RRT, renal replacement therapy; OASIS, the Oxford Acute Severity of Illness Score; SOFA, Sequential Organ Failure Assessment; MV, mechanical ventilation; OR, odds ratio; CI, con dence interval.

Subgroup Analyses
According to the KDIGO criteria, AKI patients were divided into stage 1, stage 2 and stage 3. Patient characteristics by AKI stage are shown in Table S2. The ROC curves of OASIS, APACHE II, SAPS II and SOFA score for predicting of 28-day mortality in each subgroup are shown in Table 7. OASIS had a good predictive effect in each subgroup. Table 7 shows the calibration of the risk scores. OASIS had good calibration in each subgroup, except the stage 3 subgroup. To verify the predictive effect of OASIS on the 28-day mortality among different populations of AKI patients, we divided the AKI patients into elective surgery, nonelective surgery, MV, non-MV, Sepsis, nonsepsis, RRT, non-RRT, over 65 years and up to 65 years groups, as shown in Table S3. OASIS had a good prediction effect in most subgroups.

Disscussion
In this large, multicentre prospective study, we evaluated the ability of the OASIS, APACHE II, SAPS II and SOFA score to predict the 28-day mortality in AKI patients, and we found that the performance of OASIS was the best, followed by APACHE II and SAPS II, but there were no signi cant differences among the three scoring systems. The predictive value of the SOFA score was the worst, and the difference was statistically signi cant compared with the other three scores. OASIS was signi cantly associated with a higher risk of death in the logistic regression model, whether as a continuous variable or a categorical variable, which further indicated that OASIS had good value in judging the severity of AKI patients. OASIS has been studied in the mixed ICU [19], in the cardiac ICU [20][21][22], in patients with sepsis [23][24][25][26][27] , respectively, which were higher than that of the SOFA score (0.686; P < 0.001) (Fig. 3). Although the subjects of the two studies were different, we both found that OASIS had good predictive value for mortality in ICU patients. In contrast, another study found that SAPS II (AUC = 0.741 (0.703 ~ 0.778)) and SOFA score (AUC = 0.687 (0.645 ~ 0.728)) showed signi cantly and slightly better discrimination than OASIS (AUC = 0.684 (0.643 ~ 0.725)) [27].
More clinical studies are needed to investigate the validity of OASIS.
In our study, with the increase in OASIS, the mortality rate of patients increased (Fig. 2). In AKI patients, OASIS of the nonsurvivors was higher than that of the survivors (39 vs 28, P < 0.001), which is consistent with the nding of another study (38 vs 33, P < 0.001) [23], indicating that OASIS has a good predictive value for the 28-day mortality. Moreover, it has a good predictive value for both the ICU mortality and the in-hospital mortality, which is similar to the ndings of the original study, hospital and ICU mortality increased exponentially as OASIS increased [14]. In contrast to that in the original study, the AUC value of OASIS in our study (AUC = 0.771) was signi cantly lower than that of the former (AUC = 0.902), but signi cantly higher than that of Chen et al (AUC = 0.652) [23]. The reasons are as follows: rst, the original research was performed in a mixed ICU, and the other study was conducted in septic patients, while our subjects were AKI patients. Second, the original research admitted 72,474 ICU patients in 68 ICUs at 49 U.S hospitals, the other study was conducted using data from a public database and a total of 10,305 septic patients were included. The large sample size of the studies reduced selection bias and made the results more convincing. Third, the above two studies were retrospective cohort studies, while ours was a prospective observational study. Retrospective studies are prone to confusion and bias.
ROC curve analysis showed that the cut-off value of OASIS for predicting 28-day mortality in AKI patients was 33, OASIS had the highest sensitivity (87.75 %) for predicting 28-day mortality, but a lower speci city (46.26%). In another study, the best threshold of OASIS was 34.5, with a speci city of 55.80% and a sensitivity of 64.93% [23]. We divided AKI patients into 3 subgroups according to the KDIGO criteria, OASIS increased with the increase of the AKI classi cation (Table S2), Table 7 shows that OASIS had a good predictive value in each subgroup. We also divided AKI patients into groups based on their characteristics. Other studies also grouped subjects to determine the predictive value of OASIS, for example, septic patients were grouped according to age [24], cardiac intensive care unit (CICU) populations were grouped by admission diagnosis [20], and ICU patients were grouped by BMI [19]. Subgroup analysis may be more predictive of patient outcomes. In addition, OASIS includes elective surgery, which is not included in other scores. There were 1,459 (49.4%) elective surgery patients in our study, so it may be more meaningful to use OASIS to evaluate their prognosis.4 There were some limitations in the present study. First, we did not consider factors such as the aetiology, duration, and whether RRT was used for AKI, which might affect the predictive power of OASIS. Second, although this was a prospective study, OASIS was not included in the study design, resulting in incomplete OASIS data for some patients. Third, all AUC values were less than 0.8, indicating that the four risk scores may be inaccurate for AKI patients, which prompt further prospective studies and the development of new scales in this population. OASIS is not widely used at present, probably because it is simpler than APACHE II and SAPS II, but more complex than the SOFA score. Moreover, the values used Page 17/21 are all the worst ones selected from the daily minimum and maximum values. If the data records of patients are incomplete, the application of OASIS will be limited. At present, most studies on OASIS are retrospective studies [14,19,21,22,[24][25][26][27][28], therefore, large-scale prospective studies are needed to further verify the predictive value of OASIS.

Conclusion
Because of the simplicity and effectiveness of OASIS, this study recommends the use of OASIS to evaluate 28-day mortality in patients with AKI admitted to the ICU. OASIS ≥ 33 should be considered an indicator of a negative short-term outcome.

Declarations
Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.