Urinary Neutrophil Gelatinase–Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study : Kidney360

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Original Investigation: Acute Kidney Injury and ICU Nephrology

Urinary Neutrophil Gelatinase–Associated Lipocalin Predicts Intensive Care Unit Admission Diagnosis: A Prospective Cohort Study

Katz-Greenberg, Goni1,2; Malinchoc, Michael3; Broyles, Dennis L.3; Oxman, David4; Hamrahian, Seyed M.2; Maarouf, Omar H.2

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Kidney360 3(9):p 1502-1510, September 29, 2022. | DOI: 10.34067/KID.0001492022
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Serum creatinine (sCr) has been shown to lack specificity for diagnosing early AKI (1,2). Using the rise in sCr to detect AKI is a unidimensional prototype that does not reflect the complexity of tissue injury triggered by various insults. Not only is sCr a delayed marker of injury, but it also fails to detect subclinical AKI that is clinically significant (3). The shortcoming of sCr stems from its link to deficits in glomerular filtration more than that of tubular injury. Given that acute tubular necrosis is the most common cause of AKI, especially in the intensive care unit (ICU), this represents a serious shortcoming (4). In contrast to sCr, neutrophil gelatinase–associated lipocalin (NGAL), also known as lipocalin 2 (LCN2), is a 25-kDa glycoprotein that is upregulated in the kidney early after tubular injury and can serve as the earliest known marker of kidney injury (5). In a recent meta-analysis of more than 13,000 study subjects, urinary NGAL (uNGAL) was shown to identify reliably patients at high risk of developing AKI (6).

Among critically ill patients, AKI is associated with significant morbidity and mortality (7). The predominant etiology of AKI is acute tubular necrosis precipitated by heterogeneous conditions, including sepsis, low cardiac output states, hypovolemia, medication toxicity, and major surgery, which patients frequently experience simultaneously (8). Changes to sCr in the ICU often lag behind reductions in the GFR, making use of sCr as a biomarker for deterioration of kidney function problematic (9). As timely diagnosis of AKI may change patient management and outcomes, early recognition is critical in the ICU (10,11).

Although there are several reports demonstrating the utility of NGAL in predicting AKI in sepsis (12,13), clinical outcome (14), and the potential need for RRT in addition to its correlation with mortality (14–17), to the best of our knowledge, the utility of uNGAL in distinguishing the ICU admission diagnosis has not been studied.

To study the role of uNGAL in the early diagnosis of AKI in ICU and its ability to distinguish among ICU admission diagnosis, we conducted a prospective observational study in critically ill patients and examined uNGAL values among various admitting diagnoses to the ICU and its correlation with patient factors and clinical outcomes.

Materials and Methods

We screened all adult patients admitted to various ICUs at Thomas Jefferson University Hospital between March and June 2019. Patients were excluded from consideration if they were <18 years of age, had known ESKD or stage 5 CKD, or were kidney transplant recipients. The study was approved by the Institutional Review Board of Thomas Jefferson University (IRB #18D.724).

Within 3–6 hours of admission to an ICU, 10 ml of urine was collected and centrifuged at 2000 g for 20 minutes. Urine was collected once on admission because previous studies have shown that uNGAL levels that predict AKI remain elevated in the first 1–2 days of insult (12,13,18). This negates the need for serial measurements of uNGAL. The supernatant was frozen at –80°C and reserved for batch analysis approximately 3–4 months later. We measured uNGAL by ELISA provided by BioPorto (Hellerup, Denmark) at the Thomas Jefferson University Hospital Laboratory.

AKI and its stage were determined following the Kidney Disease Improving Global Outcomes (KDIGO) criteria during the first 7 days of ICU admission. There were two approaches to the AKI classification. The first approach classified AKI as none, stage 1, stage 2 and stage 3—thus, a four-level classification. The second approach aggregated stages 1, 2, and 3—thus, a two-level or binary classification (none, yes).

The admitting diagnosis of each patient is defined as the primary diagnosis adopted by the ICU team upon admission and subsequent care. The chart of each patient was reviewed by two members of the study committee who are physicians to determine the admitting diagnosis on the basis of each patient’s working diagnosis and approach to therapy. When there was overlap, the primary diagnosis was based on the ICU team’s priority assessment list and subsequent primary intervention.

The main statistical end point was the measurement of uNGAL at ICU admission. The distribution of the uNGAL results was graphically examined and found to be highly right skewed. Accordingly, for statistical modeling, the natural log transformation of uNGAL was used to render a more normal distribution. The data were summarized using either n (%), median (range), or mean (SD). In the univariate analyses, uNGAL was compared among patient factors using either the Wilcoxon rank sum test or the Kruskal–Wallis test.

Using multivariate linear regression, patient factors were identified that were significantly associated with uNGAL at ICU admission. Only patient factors that were statistically significant in the univariate analyses were considered when developing the multivariate models. Models were calculated for each AKI coding approach, and the independent predictors were selected using the F test to determine the statistical significance of a given patient factor after adjusting for the most significant univariate factor. As noted, the log of uNGAL was the dependent variable and patient factors (AKI, etc.) were the predictor variables. Thus, the coefficients of the predictor variables are on a log scale. The inverse log transformation of the coefficients was used to calculate the percent change in uNGAL for a unit change in the predictor variable. Further, the inverse log transformation of the predicted values, from the models’ coefficients, was used to calculate and plot the geometric means of uNGAL.

All data were analyzed using R v3.4 (R Foundation for Statistical Computing, Vienna, Austria). All tests were two-sided, with a P value of ≤0.05 denoting statistical significance.


Patient Characteristics

Of the 129 consecutive patients admitted to the ICU during the study period, 22 (17%) were excluded due to refusal to consent (n=4), ESKD (n=6), lack of urine output (n=7), or missing admission data (n=5); the remaining 107 patients were included in our study. The mean age of participants in our cohort was 60.49±16.28 years of whom 74 (69%) were men. Twenty two (20%) patients had CKD, and five (5%) patients were initiated on hemodialysis during their stay. The overall in-hospital mortality rate was 11%. Of note, the median uNGAL value upon admission to ICU was 445.7 ng/ml. Table 1 describes the patients’ characteristics.

Table 1. - Patient characteristics
Characteristic Participants (N=107)
Age, yr
 Mean±SD 60.49±16.28
 Median (range) 61 (24–99)
 Men 74 (69)
 Women 33 (31)
UTI 12 (11)
Diabetes mellitus 38 (35)
Hypertension 61 (57)
Liver disease 24 (22)
CHF 38 (35)
Vascular disease 17 (16)
HIV 2 (2)
CKD 22 (20)
In-hospital mortality 12 (11)
In-hospital dialysis 5 (5)
Mechanical ventilation 79 (73)
Use of diuretic 56 (52)
Vasopressor agent 68 (63)
Known nephrotoxic agent 71 (66)
Renal consult 93 (86)
WBC (×1000/ml), mean±SD 13±11
SBP (mm Hg), mean±SD 120±24
iv fluids (ml), mean±SD 1462±1474
CCI, mean±SD 2.5±2.1
Data presented as n (%) unless otherwise indicated. UTI, urinary tract infection; CHF, congestive heart failure; WBC, white blood cells; SBP, systolic BP; CCI, Charlson Comorbidity Index.

AKI, defined according to the KDIGO criteria, occurred in 20 (19%) patients. Of those, five (5%) developed stage 1 AKI, five (5%) developed stage 2 AKI, and ten (9%) developed stage 3 AKI. Baseline characteristics in all AKI stages were compared with patients in this study who did not develop AKI (Table 2). There was a significant predilection to AKI in males in addition to a positive correlation with the length of stay (LOS) and initiating RRT in AKI patients. Of note, developing AKI in this cohort did not correlate with in-hospital mortality. There were no differences with respect to age, ethnicity, or common cardiovascular comorbidities such as diabetes, hypertension, and congestive heart failure in patients who developed AKI in the ICU (Table 2).

Table 2. - Association of ICU patient factors with three levels of AKI stage
Patient Demographics Total, N=107 No AKI, N=87 AKI Stage 1, N=5 AKI Stage 2, N=5 AKI Stage 3, N=10 Comparison P Value
 Men 74 (69) 59 (68) 4 (80) 1 (20) 10 (100) 0.02
 Women 33 (31) 28 (32) 1 (20) 4 (80) 0 (0)
Age, yr, mean (SD) 60 (16) 61 (16) 68 (23) 54 (19) 55 (14) 0.6
Race 0.16
 Black 31 (29) 23 (26) 1 (20) 4 (80) 3 (30)
 White 69 (64) 58 (67) 3 (60) 1 (20) 7 (70)
 Hispanic 2 (2) 2 (2) 0 0 0
 Other 2 (2) 1 (1) 1 (20) 0 0
 Unknown 3 (3) 3 (3) 0 0 0
UTI 12 (11) 9 (10) 1 (20) 0 (0) 2 (20) 0.63
Diabetes mellitus 37 (35) 29 (34) 2 (40) 1 (20) 5 (50) 0.67
Hypertension 59 (55) 48 (56) 3 (60) 4 (80) 4 (40) 0.53
CHF 37 (35) 30 (36) 1 (20) 1 (20) 5 (50) 0.58
LOS, mean (SD) 11 (10) 10 (9) 9 (6) 15 (15) 24 (11) 0.003
Mortality 12 (11) 10 (12) 1 (20) 0 (0) 1 (10) 0.5
uNGAL (ng/ml), median (SD) 446 (978) 100 (165) 1255 (478) 1775 (1329) 2437 (1811) <0.001
Data presented as n (%) unless otherwise indicated. Statistically significant P values are shown in italic. ICU, intensive care unit; UTI, urinary tract infection; CHF, congestive heart failure; LOS, length of stay; uNGAL, urinary neutrophil gelatinase–associated lipocalin.

Association between uNGAL Value and Patient Characteristics and Outcomes

uNGAL values measured upon admission to the ICU in patients with AKI were significantly higher (mean uNGAL 1129 ng/ml) compared with patients who did not develop AKI (mean uNGAL 26 ng/ml; Supplemental Figure 1). The significant rise in uNGAL in stage 1 AKI was sharp but then plateaued (Figure 1). This is reflective of the fact that more than half of the kidney would be injured before a noticeable rise in sCr is measured, defining AKI stage 1 (19,20).

Figure 1.:
Comparison of urinary neutrophil gelatinase–associated lipocalin (uNGAL) value at intensive care unit (ICU) admission by AKI stage. P<0.001.

Certain aspects of ICU illness were significantly associated with the uNGAL levels. Specifically, there was a correlation with intravenous (iv) fluid administration, leukocytosis, and hypotension, but not the need for iv pressors (Table 3). There was also a significant correlation between the uNGAL values and the ICU LOS (Supplemental Figure 2, Table 3). There was no correlation observed between the uNGAL values and the Charlson Comorbidity Index, which is among the best known and widely used indexes of comorbidities in acute illness. uNGAL values did not predict mortality and were not correlated with sex, ethnicity, or cardiovascular risk factors such as diabetes and hypertension (Table 4).

Table 3. - Correlation of uNGAL at ICU admission with patient morbidity
Patient Factor Correlation P Value
ER SBP −0.199 0.04
iv fluid 0.229 0.02
Presenting WBC 0.227 0.02
LOS 0.401 <0.001
CCI −0.086 0.38
uNGAL, urinary neutrophil gelatinase–associated lipocalin; ICU, intensive care unit; ER, emergency room; SBP, systolic BP; WBC, white blood cells; LOS, length of stay; CCI, Charlson Comorbidity Index.

Table 4. - Association of uNGAL level and patient characteristic
Characteristic uNGAL (ng/ml), Mean (SD) P Value
Sex 0.46
 Men 396 (802)
 Women 468 (1057)
Ethnicity 0.77
 Black 612 (1268)
 White 404 (873)
 Hispanic 14 (20)
 Other 379 (516)
 Unknown 28 (16)
UTI 0.03
 Yes 615 (951)
 No 434 (998)
Diabetes 0.36
 Yes 475 (969)
 No 429 (996)
Hypertension 0.67
 Yes 313 (682)
 No 617 (1250)
Dialysis initiation 0.02
 Yes 1868 (2224)
 No 376 (844)
Hospital mortality 0.83
 Yes 278 (560)
 No 467 (1023)
Statistically significant P values are shown in italic. uNGAL, urinary neutrophil gelatinase–associated lipocalin; UTI, urinary tract infection.

Using a multivariate regression model (model 1), we were able to identify that the ICU admission diagnostic codes were correlated with the uNGAL value upon ICU admission (Supplemental Table 1). These diagnostic codes were divided into septic shock, cardiogenic shock, liver-related illness, gastrointestinal (GI) bleed, respiratory failure, and others (Supplemental Figure 3).

The uNGAL levels on admission to the ICU were reviewed for both the non-AKI and AKI groups according to the admission diagnosis (Supplemental Figure 3). Even in the non-AKI group, uNGAL levels were significantly lower in the group with an admission diagnosis of cardiogenic shock (10.8 ng/ml; 95% confidence interval [CI], 6 to 19.3) compared with sepsis (73.1 ng/ml; 95% CI, 36.7 to 145.6), respiratory failure (48.9 ng/ml; 95% CI, 20–119.7), or GI bleed (73.7 ng/ml; 95% CI, 20.4 to 266.1). As for the group with AKI, uNGAL levels were significantly lower in patients with cardiogenic shock (260.5 ng/ml; 95% CI, 93 to 729.5) compared with sepsis (1768.2 ng/ml; 95% CI, 775.8 to 4030; see Figure 2).

Figure 2.:
uNGAL levels at ICU admission in non-AKI and AKI groups. (A) Non-AKI: (left) uNGAL levels in various ICU admission groups in patients without AKI; (right) logarithmic scale of uNGAL levels. *P<0.05 compared with the admission diagnosis: cardiogenic shock. (B) AKI: (left) uNGAL levels in various ICU admission groups in patients with AKI; (right) logarithmic scale of uNGAL levels. *P<0.05 compared with the admission diagnosis: cardiogenic shock.

The utility of uNGAL levels in predicting ICU diagnostic code persisted across the three stages of AKI (Figure 3) using another multivariate regression model (model 2; Supplemental Table 2).

Figure 3.:
Admission uNGAL values for ICU patients without AKI or with various stages of AKI stratified by admitting diagnosis. ANOVA comparison of the groups. *AKI stage versus no AKI; P<0.01.

uNGAL Predicts Need for RRT

The uNGAL value upon admission to the ICU was significantly higher in patients needing RRT. (Figure 4A, Table 4). In ICU patients who were initiated on RRT, the uNGAL mean value upon admission to the ICU was 670.5±6.6 ng/ml, which is significantly higher than in those who did not need RRT (mean uNGAL value 44.4±10.7 ng/ml; Figure 4A).

Figure 4.:
Differential uNGAL values in patients needing RRT or with UTI. Admission uNGAL value plotted against (A) RRT initiation (*P<0.05) and (B) incidence of urinary tract infection (*P<0.05).

uNGAL Predicts AKI despite Urinary Tract Infection

Similar to other studies (21,22), the uNGAL values upon admission to the ICU directly correlated with urinary tract infection (UTI) where uNGAL value in UTI patients was 188±8.3 ng/ml, which is significantly higher than uNGAL value in non-UTI patients (46±10.7 ng/ml; Figure 4B). Interestingly, adding UTI to our multivariate regression model did not show a significant difference in the model.


Our study, which demonstrated that uNGAL can predict the severity of AKI and its stage upon admission to the ICU, expands on the work of others reported previously (13,23,24). A stepwise increase in the serum NGAL value related to AKI stage was shown by Bergquist et al. (25) Our data showed a similar pattern in uNGAL, in which the rise in uNGAL is highest upon stage 1 and then levels off with stages 2 and 3 AKI. Tescon et al. showed a sharper rise in uNGAL at stage 2 (26), unlike our data showing a shaper rise as early as stage 1. In AKI, the uNGAL kidney injury marker is likely to rise earlier than the commonly used kidney functional marker sCr (27). The study by Stanski et al. clearly showed the rise in uNGAL in patients with normal sCr as a likely sign of subclinical kidney injury preceding AKI as defined by KDIGO (28). In our critically ill patients, the uNGAL values likely started to rise early and rapidly, reflecting tubular injury that does not correspond with the modest rise of sCr at early stages of AKI. The sharp rise in uNGAL at an early stage of AKI reflects our current understanding of AKI whereby the sCr starts to rise when the kidney function is already reduced by >50% (19,20). Patients with uNGAL that is lower but that shows a significant rise, and without a significant rise in the functional marker sCr, likely represents patients with subclinical AKI as proposed by the Acute Dialysis Quality Initiative consensus conference (27). We suggest that the kidney assessment of all newly admitted ICU patients should include both sCr and uNGAL to study the ICU outcome better in patients with subclinical AKI who are at high risk for CKD (29) and other adverse ICU outcomes (30–32). Guidelines on septic shock evaluation and treatment continues to evolve, with emphasis on early identification and appropriate management in the initial hours of sepsis to improve outcome (33). Our data also show that uNGAL can predict ICU patients who are likely to require RRT initiation. This finding is in line with results from a meta-analysis of 15 studies where Zhang et al. concluded that NGAL is not only a good predictor of AKI but can also predict the need for RRT in septic patients (15). Gaudry et al. showed that a delayed approach in initiating RRT in critically ill patients with severe AKI did not affect mortality and averted the need for RRT in half of those patients and markedly reduced catheter-related bloodstream infections (34). However, Gaudry et al. used sCr to determine severity of AKI to study the effect of early RRT intervention. uNGAL is an early marker of kidney tubular injury with likely delayed tissue recovery (35). Elevated uNGAL can better identify patients who might benefit from early RRT due to intrinsic kidney tissue injury. Patients with a rise in sCr due to hemodynamic changes will still be defined as having AKI, despite the lack of intrinsic kidney tissue injury (27,36). These patients with a functional rise in sCr will likely not benefit from early initiation of RRT and would not need RRT. Our data support the latest Acute Disease Quality Initiative consensus conference recommendation to include biomarker data with clinical assessments to identify patients who will need RRT (37). Further studies on initiation strategies for RRT in the ICU should include uNGAL in addition to sCr, where uNGAL’s ability to predict the admission diagnosis can better refine this early goal-directed strategy.

Our data also demonstrate that uNGAL levels can predict the LOS of these ICU patients—a finding similar to those seen in other cohorts (11,17,38). uNGAL can appreciably reduce health care costs by reducing delays in diagnosis of AKI, thus reducing morbidity (12,39,40).

There was no correlation between AKI and in-patient mortality in our cohort, despite the known relationship, which is well demonstrated by a meta-analysis by Coca et al. (41). Moreover, the data on the ability of uNGAL to predict mortality is conflicting. Like others, we show that uNGAL values did not predict mortality (25,28,42). Several studies with larger cohorts of patients showed a correlation between NGAL levels and mortality (14,16,17). It is likely that our relatively small sample size precluded us from establishing a correlation between AKI and in-patient mortality and further limited our study of the relationship between uNGAL values and in-hospital mortality.

One intriguing finding of our study is that the uNGAL values vary by the admitting diagnosis to the ICU, irrespective of AKI. Admissions to the ICU with septic shock and/or GI bleed were associated with higher uNGAL values compared with cardiogenic shock or “other” diagnosis. This corresponds with data from other studies by Bergquist and de Geus (26). In a study by Bergquist et al., serum NGAL was significantly higher in patients with sepsis regardless of AKI incidence (25). In a cohort of critically ill patients, de Geus et al. also showed that the uNGAL levels were significantly higher in patients admitted with sepsis without AKI (12). The correlation between NGAL levels and sepsis is not surprising, given the properties of this ligand. NGAL, an endogenous bacteriostatic protein expressed to large extent by neutrophils and macrophages, plays a crucial role in the innate immunity against bacterial infection (43,44).

Our study showed significant elevation in uNGAL in patients with GI bleed, possibly reflecting the association of GI bleeding and bacterial translocation (45,46). In a transgenic IL-6-deficient mouse model, Skrypnyk et al. showed a reduction in plasma and uNGAL in AKI as a reflection of decreased systemic inflammation (47). On the other hand, uNGAL levels were lower in patients with cardiogenic shock—a condition that is usually not associated with infection and/or bacteremia (48). In our ICU cohort, the uNGAL levels were lower in cardiogenic shock compared with other admission diagnoses regardless of AKI. This supports the pathophysiology of kidney dysfunction in cardiogenic shock as a reflection of a low-flow state that might lead to minimal to mild tubular damage. Au et al. showed that transient AKI due to low-flow state is not associated with an increase in the uNGAL level due to lack of tubular injury (33,49). The symptoms of cardiogenic shock can be subtle early in the ICU course in certain patients (50,51), with occasional absence of pulmonary congestion at initial clinical evaluation (51). Current tools to diagnose cardiogenic shock in the first few hours of ICU admission can be challenging (52), including the utility of an echocardiogram in ventilated patients (53). uNGAL is a promising tool that is inexpensive and readily available to help distinguish septic shock from other admitting diagnoses, especially cardiogenic shock in the first few hours of an ICU admission. The assay to measure uNGAL would cost approximately $20 (personal communication, Bioporto) to be measured once upon ICU admission. The average cost of serum creatinine for every time it is measured is an average of $7.03 (Center for Medicare and Medicaid Services: Clinical Laboratory Fee Schedule and Physician Fee Schedule, Baltimore, Center for Medicare and Medicaid Services, 2018). Parikh et al. showed that measuring uNGAL in the emergency department improved management of AKI and reduced the expected health care costs in a multicenter study (40). The uNGAL assay is commercially available in Europe (14,54,55) and parts of Asia (56). The assay that measures uNGAL can be readily used on machines that are widely used in most US-based clinical laboratories. However, NGAL assays are currently not commercially available in the United States.

We uniquely demonstrate the ability of uNGAL to distinguish septic shock from cardiogenic shock regardless of AKI. Distinguishing between septic and cardiac shock soon after ICU admission is critical because interventions can be quite different, especially in volume management, which is further complicated in the presence of AKI.

Further studies are needed to define uNGAL value intervals better in relation to admission diagnosis, to understand the role of uNGAL in diagnosing and treating AKI in cardiorenal syndrome, and to evaluate further the relationship of longitudinal changes in NGAL levels during congestive heart failure and subsequent need for diuresis and kidney outcome.

As reported in other studies (21,22,57), we show that UTI increases the uNGAL level. However, UTI did not affect the uNGAL as a tool to predict AKI when analyzed in our multivariate model. Our finding is important and adds to the current knowledge of the utility of uNGAL in the ICU as a predictor of AKI regardless of the UTI diagnosis. This expands the patient population in future ICU studies of NGAL and uNGAL specifically.

This study has several limitations. We did not measure plasma NGAL, which might offer an advantage in the diagnosis of patients with rapidly decreasing urine output. It is important to note that plasma NGAL derives from other organs exposed to the same injury in addition to the kidney. A meta-analysis shows that plasma and uNGAL levels similarly predict AKI, and both are better alternatives to sCr (58). Another limitation of our study is that the timing of urinary collection for NGAL in the ICU was within a few hours of the ICU admission. Previous studies show that uNGAL levels that predict AKI remain elevated in the first 1–2 days of insult (12,13,18). Our study replicates a typical clinical setting where a urine sample might not be sent upon admission to the ICU until a few hours later, but still within the window of peak performance of uNGAL (3–12 hours after kidney injury) (59). Another limitation of our study is the lower rate of average events of AKI in an ICU. Despite our lower event rate, the results are robust and similar to those from other studies of NGAL in patients admitted to the ICU (12,18,60). Expanding the study to include more patients might have increased the incidence of AKI but likely would not have changed our observations. Our small cohort also prevented us from studying the outcome of patients admitted with subclinical AKI with elevated uNGAL that do not meet AKI criteria according to the KDIGO definition. We also note the absence of association of the Charlson Comorbidity Index with uNGAL levels, despite a significant correlation with certain aspects of ICU illness such as iv fluids and hypotension in our small cohort of patients. This finding remains quite intriguing and hypothesis generating for larger studies on the utility of a single uNGAL measurement upon admission to the ICU and for comorbidity risk prediction.

In conclusion, a single uNGAL measurement upon admission to the ICU serves multiple essential purposes. First, uNGAL may help delineate the culprit of shock, especially cardiogenic shock, in the first few hours of admission to the ICU, irrespective of the presence of AKI. Second, uNGAL can better define the kidney status of these patients and identify patients with subclinical AKI, which would better inform future ICU studies of outcome and/or intervention. Third, uNGAL predicts RRT, where its early use with sCr can better define the ICU patient population for future early goal-directed interventional studies to improve ICU and kidney outcome. uNGAL measurement upon ICU admission is essential in all patients for its ability to predict admission diagnosis and need for RRT and will serve future studies on early strategies to improve ICU and kidney outcomes.


D.L. Broyles reports being an employer of Dennis Broyles IVD Consulting; consultancy for L3 Healthcare; and ownership interest in Beckman Coulter. M. Malinchoc reports being an employee of L3 Healthcare. D. Oxman reports that his spouse is a full-time employee of Merck working on pediatric vaccines. She works on a number of clinical trials sponsored by Merck. None of these trials have anything to do with the contents of the submitted manuscript. All remaining authors have nothing to disclose.




We express our acknowledgment to Dr. Christopher Bird of BioPorto Diagnostics, Inc. (Needham, MA) who supported this study by supplying the uNGAL measuring kits to our laboratory.

We express our acknowledgment to the efforts of Drs. Fitsum Hailemariam, Rabail Qureshi, Edgar Guzman-Suarez, Azza Abdel-Hak, Xiaoying Deng, and Kavitha Ramaswamy in collecting the samples and entering the patient data. We also thank Dr. Douglas Stickle and the Jefferson Clinical Laboratory for conducting the uNGAL measurements.

Author Contributions

D.L. Broyles, O.H. Maarouf, and M. Malinchoc were responsible for the formal analysis and methodology. S.M. Hamrahian, D.L. Broyles, D. Oxmanand O.H. Maarouf reviewed and edited the manuscript. G. Katz-Greenberg and O.H. Maarouf were responsible for the investigation and wrote the original draft of the manuscript.

Data Sharing Statement

All data are included in the manuscript and/or supporting information.

Supplemental Material

This article contains the following supplemental material online at http://kidney360.asnjournals.org/lookup/suppl/doi:10.34067/KID.0001492022/-/DCSupplemental.

Supplemental Figure 1. Admission urinary neutrophil gelatinase–associated lipocalin stratified by AKI.

Supplemental Figure 2. Plot of length of stay in days to the admission urinary neutrophil gelatinase–associated lipocalin.

Supplemental Figure 3. Admission urinary neutrophil gelatinase–associated lipocalin values for intensive care unit patients with various admitting diagnosis stratified by absence of AKI versus AKI. ANOVA comparison of the groups. *AKI stage versus no AKI, P<1×10–9; #Sepsis versus nonsepsis diagnostic code, P<0.01.

Supplemental Table 1. Association of urinary neutrophil gelatinase–associated lipocalin level at intensive care unit admission with patient factors in AKI.

Supplemental Table 2. Association of urinary neutrophil gelatinase–associated lipocalin level at intensive care unit admission with patient factors in various stages of AKI.


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acute kidney injury and ICU nephrology; acute kidney injury; AKI; cardiogenic shock; ICU nephrology; injury marker; lipocalin-2; NGAL; sepsis; shock; urine biomarker

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