Assessment of the RIFLE criteria for the diagnosis of Acute Kidney Injury; a retrospective study in South-Western Ghana

Acute kidney injury (AKI) is classically defined as an abrupt and sustained decrease in renal function [1‐3]. However, there is neither agreement on the best method of assessing renal function nor consensus on the exact cutoffs for the diagnosis of AKI. This challenge not only leads to conflicting reports in literature but is also believed to be a major obstacle to research in this field [2, 4, 5].

There are no reliable estimates of AKI incidence across Africa [6], however, recent studies from Uganda report an AKI prevalence of 16.3 among sepsis patients [7]. But, findings from studies from other parts of the world indicate that AKI is common especially among hospitalized patients and affects some 3–7 % of patients in hospitals and 25–30 % of intensive care patients [8]. AKI ultimately results in morbidity, or will consequently demand the use of renal replacement therapy procedures such as dialysis or will result in mortality [9‐11].

AKI in sub Saharan-African countries including Ghana is mostly attributed to infections like HIV/AIDS, malaria, diarrhoeal diseases; nephrotoxins and obstetric and surgical complications [12‐14]. Also AKI in Ghana has been associated with the use poorly prepared herbal preparations [12]. Consequently, the International Society of Nephrology (ISN) introduced the ISN 0 by 25 to reduce the occurrence and impact of AKI [15].

A standard way of diagnosing AKI has been introduced with the acute kidney injury network (AKIN), RIFLE, and the kidney disease improving global outcomes (KDIGO) guidelines [16, 17] to ensure effective diagnosis and proper management [16]. The Acute Dialysis Quality Initiative (ADQI) formulated the Risk, Injury, Failure, Loss, and End-stage Kidney (RIFLE) classification for the diagnosis of acute kidney injury [18]. RIFLE, an international consensus classification for acute kidney injury, defines three grades of severity—risk (class R), injury (class I), failure (class F) and two outcome classes (loss and end-stage kidney disease).

The evaluation of renal function in people with suspected acute renal failure (ARF) or AKI is based solely on urinalysis, urea and creatinine estimation which cannot predict the severity of the renal impairment. However, studies in Europe and Australia have established the use of the RIFLE criteria in the diagnosis and subsequent management of people with AKI [19, 20]. Despite its increasing incidence, AKI in our setting [13] is still diagnosed by the estimation of serum creatinine. For this reason we chose to use the RIFLE criteria to access AKI among Ghanaian patients. This we believe will enhance monitoring of the progression of acute kidney Injury severity and possibly restoration of renal function in hospitalized patients.

Thus this study sought to use retrospective data of ICU patients in the Efia Nkwanta Regional Hospital to determine the incidence of AKI, and access whether it is feasible to use the RIFLE criteria in this context. This will be achieved by assessing AKI among in-patients under the estimated glomerular filtration rate (eGFR) and the increase in factor (SCr/ePCr) criteria and also comparing the distribution of AKI among gender from the eGFR and the SCr/ePCr criteria.

A total of 1763 data of ICU patients were sampled within the period from July to December 2014. Of these, 483 were below the age of 18, whereas the bio data for another 210 patients was incomplete. Thus, overall data of 1070 participants was used. Serum creatinine had been estimated for all of these participants on admission to ICU or when it became apparent that they had AKI and thus were referred to the ICU. Therefore, we calculated the estimated serum baseline creatinine for the purposes of this study.

Table 1 shows the demographic characteristics of study participants. In overall, 1070 participants were studied of which 47.29 and 52.71 % were males and females respectively. The highest and lowest frequency were found among the age groups 20–39 years and <20 years respectively. Most of the participants (82.06 %) were in age range 31–59 years.

Table 2 shows the distribution of hospital admission serum creatinine, estimated glomerular filtration rate, back serum creatinine and the increase in baseline serum creatinine among gender. Males had higher SCr (P = 0.0001), eGFR (P < 0.0001), ePCr (P = < 0.0001) than females. However, females also had higher SCr/ePCr (P = 0.0212).

The Table 3 shows RIFLE classification from the GFR and SCr/ePCr criteria. The percentage ratios from the SCr/ePCr criteria were higher as compared to that of the eGFR criteria.

The number of Risk patients from the SCr/ePCr criteria was more than that from the eGFR criteria. However, the number of Injury and normal patients from the eGFR criteria were all higher as than the SCr/ePCr criteria.

Table 4 outlines the proportions of RIFLE classes from the GFR Criteria. Males had more injury (P = 0.06715) and failure (P = 0.1196) than females. Females had more risk per the same criteria than males (P = 0.0107).

Table 5 shows the distribution of RIFLE classes among gender from the SCr/ePCr criteria. Females had more risk (P = 0.3222) and injury (0.2030) than males while failure was significantly higher in males than females (P =0.0071).

Figure 1 summarizes the distribution of the mean ages in the RIFLE classes (AKI). Mean ages for males and females who had AKI were significantly higher than those who had no AKI (P = < 0.0001). The older people tended to get more Risk and younger people more Failure. There was an association between the mean ages and the type of RIFLE class (AKI) developed in the patient.

This single-centre retrospective study used laboratory data to access the incidence of AKI among ICU patients in Ghana. We found that the RIFLE criteria detected AKI among ICU patients and SCr/ePCr (hospital admission serum creatinine/estimated plasma creatinine) gave females more risk and injury than males. In addition, mean age varied by RIFLE class with Risk tending to be associated with older mean age than Injury, Failure and no AKI respectively.

The occurrence of AKI in the patients from eGFR and the SCr/ePCr criteria were inconsistent with a prospective cohort study conducted by Macariello et al., [26] in Brazil. This discrepancy could be due to the multi-center prospective cohort design employed, differences in variables selected (eg. old age and patients with three or more organ dysfunction) and the sample size (214) used in their study. From the RIFLE criteria when more than one sub-criteria is used on a single patient the patient is classified under the worst class [23] a finding confirmed by observations in this study (Fig. 2). This outcome ultimately helps in the early detection of patients at risk so that they can be effectively managed to prevent adverse outcomes.

However, the occurrence of AKI among patients from the SCr/ePCr criteria in this study was in line with that of Hoste et al., [27] in a retrospective cohort study conducted at Pennsylvania on 5383 patients in seven intensive care units admitted during a 1-year period using the SCr/ePCr criteria. He and the colleagues found out that there was more AKI incidence than non-AKI among the studied population. The use of the SCr/ePCr criteria in this study gave a higher risk incidence which confirmed the Pennsylvania study [27].

The proportion of patients under the RIFLE classes from the SCr/ePCr criteria gave 89.7 % in R, 2.7 % in I, 5.8 % in F and 1.8 % in non-AKI contradicts the findings of an earlier study [28] in patients undergoing cardiac surgery, where there were 15.1, 9.1, 4.8, 71 % in the Risk, Injury, Failure and non-AKI classes respectively. The differences in the occurrence of AKI among the patients may be due to our inability to consider the disease condition(s) of the patients in this study, the kind of study design (prospective multicenter analysis) and the sample size used in earlier study.

Multi-centre and cohort studies [29, 30] in Canada also commented on the lack of linearity in using the eGFR criteria in the assessment of AKI in hospitalized patients. In this study, the use of the SCr/ePCr criteria gave more AKI in the patients (98.72 %) than the eGFR criteria (37.28 %) and confirms the findings of Ostermann et al., [30].

The mean ages (years) of patients under the RIFLE classes were 47.4, 45.42 and 42.4 from class R to F respectively, 40.6 under the non-AKI category which showed that there was a significant correlation between the mean ages and AKI. The percentage ratio of RIFLE classes R to F from the eGFR criteria were 0.34, 0.12 and 0.11 respectively while that from the SCr/ePCr criteria were 1.43, 1.53 and 3.36 respectively. This depicts that the probability of an individual from the non-AKI group falling into any of the RIFLE classes from the SCr/ePCr criteria will be higher than that of the eGFR criteria. The use of this criterion will go a long way in providing solutions to the challenges associated with the diagnosis of AKI in the hospital setting. This will subsequently lead to the establishment of diagnosis so that the necessary interventions can be provided.

The strengths of our study is the fact that it is the first of its kind, to our knowledge, to assess AKI in sub Saharan Africa using RIFLE criteria or any of the guidelines (AKIN or KDIGO) to provide epidemiological data on AKI.

Our study however has a few limitations: first, the RIFLE criteria require urine sample measurement at specific time intervals to help in the classification of patients under the various strata of the criteria. The absence of urine in this study however will not be a problem since the other two estimated parameters (percentage decrease in eGFR and serum creatinine baseline increase) can equally help to evaluate AKI in hospitalized patients using the RIFLE criteria [31]. Second, even though the MDRD equation has not been validated in the Ghanaian population and used mostly in the assessment of CKD [32], the RIFLE criteria requires that this equation be used in the assessment of AKI and also as with many AKI studies, the absence of baseline serum creatinine means that estimation of these values was required to define AKI. Finally, the use of a single centre, a retrospective design, limited descriptive information of participants, potential sources of chance, bias and confounding in their findings will also limit the scope of our outcomes.

However, in a situation where there is no correlation between the eGFR and the measured urine in classifying AKI patients under the RIFLE criteria, preference is given to the eGFR since it best predicts the function of the kidneys [31].

Research Implications of Findings: Our findings imply that the RIFLE criteria which aids in early detection and staging of AKI for better outcomes and management is useful in the Ghanaian population.