Acute Kidney Injury (AKI) is a common complication for patients admitted to the intensive care unit (ICU).1 Among its causes, sepsis-associated AKI (S-AKI) is the most frequent, accounting for 50% of cases.2 The pathophysiology of S-AKI is still poorly understood. The absence of characteristic histopathologic findings suggests that it could be a functional phenomenon, at least in the initial stages.3,4 Despite its limitations, AKI diagnosis and staging are based both on diuresis and serum creatinine values.5 Following the last consensus guidelines, persistent (pAKI) and transient AKI (tAKI) are defined as an AKI episode lasting more or less than 48−72h, respectively.6 Among them, pAKI might have a bigger impact on patient survival.7

The use of urine biochemistry and indices for guiding therapeutics presents multiple limitations. Fractional excretion of sodium (FENa) was originally conceived to be used on dehydrated patients and applying it in the context of sepsis may be misleading. Recent studies have shown that septic patients exhibit a low FENa when AKI develops, reflecting hyperactivation of the renin-angiotensin-aldosterone system (RAAS) and microcirculatory stress.8 Therefore, a FENa lower than 1% does not necessarily represent a hypovolemic state in septic patients, as it is essentially a constant variant.9

Alternative parameters have been explored, including Fractional excretion of potassium (FEK) and urinary strong ion difference (uSID).10,11 Elevated SIDu, in the presence of metabolic acidosis, might reflect the kidney’s inability to acidify urine (less tubular ammonia secretion). Thus, “intrinsic” damage may be manifested this way at the tubular level.10 Additionally, high FEK values reflect RAAS hyperactivation during early AKI and kidney stress. In this regard, both uSID and FEK may be valuable tools for detecting early physiologic disruptions, as well as predicting pAKI.

Given this background, the main objective of this study was to evaluate sensitivity, specificity, and under the ROC curve of FENa, FEK and uSID in a specific population of S-AKI patients, employing the latest consensus definitions. Additionally, we aimed to ratify previous findings regarding these indices.

A total of 199 patients with S-AKI diagnosis admitted to the ICU were initially evaluated. 119 patients were excluded (Fig. 1). The most frequent causes of exclusion were chronic kidney disease KDIGO stage 3b or higher and the lack of urinary biochemistry within the 24h of AKI diagnosis. Overall, 80 patients were finally included in the analysis.

Baseline clinical, demographic and laboratory data are presented in Table 1. The cohort comprised older adults (mean age 70.7 years old, SD 15.3) and 59.5 % were male. It is worth mentioning that hypertension and diabetes mellitus were the most prevalent comorbidities, 61.3 % and 17.5 %, respectively, with no difference between groups. Only 7 individuals (8.7%) had a baseline estimated glomerular filtration rate lower than 60ml/min and were more prevalent in the pAKI group (15%). No differences in regular medications received in the ambulatory setting were found.

The severity of illness in patients with pAKI was greater, reflected by higher APACHE and SOFA scores at ICU admission, IMV requirement and septic shock incidence. A roughly six-fold increase in the mortality rate during hospital stay among patients developing pAKI was observed. Overall, 9 subjects (11.5%) required RRT (Table 2).

Regarding baseline biochemical parameters, individuals with pAKI presented lower pH and base excess values. On the other hand, they had higher plasma creatinine, urea, FENa and FEK. Of note, pAKI patients had higher exposure to nephrotoxic drugs such as vancomycin and colistin. No differences were found regarding 24-h or 72-h cumulative net fluid balance (Table 2).

The ROC analysis is presented in Fig. 2. uSID had no diagnostic utility (AUC=0.52, p=0.69). FENa presented moderate accuracy showing an AUC of 0.71 (95% CI 0.60−0.83; p=0.001), while FEK presented low accuracy with an AUC of 0.69 (95% CI 0.57−0.80; p=0.04). The optimal Youden point for identifying pAKI was at a FENa higher than 0.51 % with a specificity of 72.5% and a sensitivity of 65.0%. In the case of FEK, a value higher than 21.9 % presented the best relation, with a specificity of 67.5% and a sensitivity of 65.0%.

Figure 2.

ROC curve showing the area under de curve of FENa, FEK and uSID.

FENa: fractional excretion of sodium; FEK: fractional excretion of potassium; uSID: urinary strong ion difference.

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The main finding of our study was the fact that FENa and FEK presented moderate and low diagnostic accuracy for the discrimination between pAKI and tAKI in critically ill septic patients, respectively.16 However, we did not find a diagnostic utility for uSID in this setting.

FENa is a widespread tool for interpreting AKI used from the 70s due to the work of Espinel et al.17 However, the paradigm of prerenal and intrinsic AKI is under question. It is well known that patients with sepsis present a FENa <1% on the first days of AKI development.18 Also, in S-AKI, FENa is lower compared to other AKI etiologies. Based on these findings, different authors rejected FENa as a marker of pAKI in sepsis.19 In 2013, Vanmassenhove et al. in a prospective study, analyzed FENa and other biomarkers in 107 sepsis patients at admission. They found a lower value of FENa (0.36%) with a 92 % negative predictive value for intrinsic AKI or not restoring diuresis. They concluded that FENa values should be revised for this population. Our study aligns with this conclusion, with a FENa of 0.51 % representing the optimal Youden point. The AUC shows moderate accuracy for predicting pAKI,16 which is why our results must be interpreted carefully. Considering this limitation, this finding suggests that FENa still could be used as a complementary test for predicting pAKI in this setting, with a lower cut-off. It is an accessible tool for its availability in every ICU and has a lower cost than novel biomarkers.

In the last decade, Maciel et al. started to explore FEK as a diagnostic tool for pAKI.10,11 They considered it as fairly accurate for predicting pAKI, with an AUC of 0.71 (95% CI: 0.61−0.81; p<0.001) on the day of AKI diagnosis. A FEK of 18.3% was found to be the best cut-off value for discriminating pAKI, with a PPV of 69.3% and NPV of 72.6%. We confirmed these findings with similar values. FEK in this setting may be representing RAAS hyperactivation during sepsis. Medullary hypoxia produced by intrarenal shunt in sepsis may contribute to this, generating a loop diuretic effect due to Na-K-2Cl carrier dysfunction.20

Alterations in UCl are a part of AKI development.8 Kellum proposed that an adequate response to metabolic acidosis should be a negative uSID. During AKI, this mechanism could be damaged and would manifest as the renal incapability of Cl− excretion during metabolic acidosis, with a greater uSID.21 Balsonaro et al. showed in a retrospective cohort with sepsis, an excellent diagnostic performance for uSID on differentiating AKI from controls, while the AUC for distinguishing between pAKI and tAKI was more modest.10 We couldn’t reproduce this finding in our cohort. Two reasons may explain this. First, our patients did not present severe metabolic acidosis, although patients with pAKI were more acidotic. Second, we obtained data from the day of AKI diagnosis. In this early stage, urine acidification mechanisms may have not been activated yet.22

Some strengths must be noted. Firstly, we aimed to study a restricted sample of critical patients with S-AKI. Previous research has studied the general ICU population, including different causes of AKI, which makes it difficult for result interpretation. Secondly, we accurately determined the precise time frame in which AKI developed and when urinary biochemistry data was collected. The timing on which the urinary indices are performed is crucial to validate the diagnostic method for pAKI. Thirdly, we gathered information on factors associated with AKI, such as prior medications and nephrotoxic agents, on the day of AKI onset. Lastly, despite focusing on a S-AKI population, we employed a pragmatic approach and did not exclude patients with common confounders like exposure to nephrotoxic drugs, ACEI/ARBs, and diuretics. This approach enhances the applicability of our findings to clinicians managing patients in everyday practice.

Several limitations are present in this study. Although we studied a restricted population, there are factors other than sepsis that may be influencing kidney recovery in the pAKI group. Shock, nephrotoxic drugs and severity scores such as APACHE II and SOFA are higher in this group. Secondly, we couldn’t compare curves with novel biomarkers such as NGAL or KIM-1 because it is not routinely employed in our unit. Thirdly, the single-center nature of the study hinders the external validation of the study. On this line, factors regarding hemodynamic monitoring and fluid management may vary between centers and could be influencing renal outcomes.

Our data suggests that urine biochemistry utility in septic patients must be revised. FEK and FENa are related to AKI severity. In the setting of S-AKI, FENa and FEK could be helpful complementary tools for predicting pAKI on the day of AKI diagnosis.

During the preparation of this work, the author did not use a generative AI tool in the writing process.

The authors declare no conflict of interest relevant to the content of this paper.