While the causes of acute kidney injury (AKI) are diverse, sepsis has been found to be an important contributing factor to its development in critically ill patients (1). A study of AKI in 54 hospitals from 23 countries demonstrated that approximately 50% of AKIs are secondary to sepsis (2). Moreover, sepsis-induced AKI is independently associated with clinically poor outcomes and significantly increases mortality (3). Among patients with severe sepsis or septic shock admitted to the emergency department (ED), the acute aggravation of normal kidney function to severe kidney injury initially occurs very quickly (4). In such patients, the mortality is significantly increased, compared with that of patients without AKI (4). Therefore, early prediction and timely aggressive treatment for AKI such as continuous renal replacement therapy (CRRT) in patients with severe sepsis or septic shock may be necessary to improve clinical outcomes (5). The high mortality associated with septic AKI may partially be explained by the absence of therapeutic methods of kidney restoration and delays in risk stratification (6). Currently, the diagnosis of AKI is based on either an elevation in serum creatinine levels or the detection of oliguria (7). These criteria, however, do not adequately reflect kidney cell damage and have limited sensitivity and specificity for the early recognition of renal dysfunction (6). The introduction of new early biomarkers that easily predict the development of kidney dysfunction in sepsis may improve patients’ prognoses by allowing for the application of preventive methods and innovative therapeutic options (1, 8). The delta neutrophil index (DNI) represents the proportion of circulating immature granulocytes (IGs) and is obtained by subtracting the fraction of mature polymorphonuclear leukocytes from the proportion of myeloperoxidase reactive cells (9). The pathophysiological association between IGs and septic AKI is still not fully understood; therefore, further molecular studies are needed to validate the direct role of IGs in the development of AKI over time in severe sepsis and septic shock. To compensate for the destruction of mature cells, and massive consumption resulting from neutrophil infiltration, inappropriate migration of infected sites, and sequestration in remote organs under severe sepsis or septic shock, the hematopoietic system may rapidly switch to emergency granulopoiesis (10, 11). The alteration of innate immunity increases the release of myeloid-derived suppressor cells (MDSCs) including the progenitors or precursors of neutrophils from the bone marrow after sepsis (10, 12). The important role these MDSCs and immature neutrophils play in sepsis-induced immunosuppression results in a decreased first-line response against infection and inflammation (12, 13). The effects of this inappropriate response to infection lead to cellular dysfunction and, ultimately, organ failure including renal dysfunction (14). IGs may reflect the dysregulated immune response of the host. IGs are known to increase the risk of developing systemic inflammatory response syndrome (10, 15). However, it is difficult to precisely detect IGs and their diagnostic capacity still remains controversial (16). Despite the partial data analysis, the present study also indicates a strong correlation between the DNI and manual IG counting (r = 0.789, P < 0.001) and that the use of this automated analyzer in calculating the DNI allows for time delays and the poor accuracy of the manual assessment of IGs to be overcome (9, 11, 17). Several meaningful studies have shown that higher DNI values are significantly associated with poor prognoses in inflammatory diseases (9, 11, 15, 18). The DNI, in particular, is a more useful serum index for predicting mortality and disease severity in patients with sepsis (19). To the best of our knowledge, there are no studies focusing on the advantages of using the DNI to predict acute progression to severe kidney injury in patients with sepsis. The pathophysiology of the acute deterioration of kidney function in sepsis not only involves volume depletion but also dysregulated inflammation reactions (20). Thus, we hypothesized that the application of DNI values could predict the acute exacerbation of kidney injury and eventually death during the treatment of sepsis patients. The aim of the present study was to evaluate whether an increased DNI can predict several clinical end-points, including the acute development of severe kidney injury, need for renal replacement therapy (RRT) within 7 days and 30-day mortality in sepsis patients with normal kidney function or stage 1 disease, as per the Acute Kidney Injury Network (AKIN; mildly reduced kidney function) at the time of ED admission.
PATIENTS AND METHODS
We conducted this retrospective observational cohort study with a prospective registry in the ED of Yonsei University College of Medicine Severance Hospital, a university-affiliated, tertiary-level referral hospital with an annual census of approximately 85,000 visits. The study was approved by the Institutional Review Board of the Yonsei University Health System clinical trial center (No. 3-2017-0336). Although we analyzed the prospective early goal-directed therapy (EGDT)/SEPSIS registry in the ED, we retrospectively performed this study based on medical records and the de-identification of subjects. Therefore, the requirement for written consent from the patients was waived. Since November 2007, the “EGDT” as a critical pathway (CP)—which was revised to “SEPSIS” in June 2015 according to changes observed in studies on EGDT—has been implemented in our institutions as part of a quality improvement initiative. This CP was designed to provide standard treatment by bundle management and rapid decision-making by specialists and decrease unnecessary in-hospital time delays (10). We classified patients with suspicions of infection admitted to the ED as presenting with systemic inflammatory response syndrome (SIRS) (A) (10). As a result of infection, we defined SIRS by the presence of two or more of the following criteria (21). We prepared CP activation; [A] temperature > 38°C, heart rate > 90 beats/min, respiratory rate > 20 breaths/min or PaCO2 < 32 mm Hg, and white blood cell (WBC) count >12,000 cells/μL or < 4,000 cells/μL, or band neutrophil count > 10% (10). We assessed patient's eligibility for CP activation. Those who presented with SIRS [A] as well as those who met least one inclusion criterion [B1 or B2] on ED admission were finally included in the CP: [B1] systolic blood pressure <90 mm Hg, despite a 20 mL/kg to 30 mL/kg intravenous crystalloid fluid challenge; or [B2] serum lactate level ≥4 mmol/L on ED admission (10). We excluded or deactivated the following cases from the CP: age < 18 years; pregnancy; acute cerebrovascular or coronary syndrome; active gastrointestinal bleeding; contraindication to central venous catheter; trauma; a requirement for immediate surgery; transfer to another hospital within 6 h after ED admission; do-not-resuscitate status. The present study included consecutive patients who were prospectively integrated into the EGDT/SEPSIS CP program according to predetermined protocols (10). To investigate the acute development of severe kidney injury, we analyzed sepsis patients who had normal renal function or stage 1 disease as per the AKIN between January 1, 2014 and September 30, 2017 and were admitted to the ED. Figure 1 shows the enrollment, exclusion, and clinical outcome data of the patients with severe sepsis or septic shock. We excluded all patients who met any of the following exclusion criteria: requirement for immediate surgery, history of end-stage renal disease, history of renal allograft, initial estimated glomerular filtration rate (eGFR) < 30 mL/min per 1.73 m2, AKIN stage 2 or 3 disease at ED admission (>100% increase in the serum creatinine level from the baseline), evidence of hypovolemic status (bleeding or dehydration), history of hematologic malignancy, chemotherapy within 7 days before admission transfer out within 7 days (Fig. 1) (10).
We collected data on demographic characteristics (age; sex; body weight; and medical history, including chronic kidney disease, hypertension, diabetes mellitus, heart failure, and liver cirrhosis); use of nephrotoxic medication; hemodynamic parameters; laboratory results, including serum creatinine, eGFR, complete blood count (CBC), C-reactive protein (CRP), severity of shock, procalcitonin, and results of blood culture; in-hospital course including time of RRT initiation; clinical outcomes and period of follow-up. Hourly fluid input and urine output data were extracted from clinical observation records documented by a nurse. The eGFR was automatically and routinely calculated using the Modification of Diet in Renal Disease equation, along with standardized serum creatinine values and patient information, from the electronic health record in our institution. The severity of shock was defined in supplement (Supplemental Digital Content 1, https://links.lww.com/SHK/A848). Our study used this automatically calculated value for eGFR. The Acute Physiology and Chronic Health Evaluation (APACHE) II score was determined using the worst values obtained during the initial 24 h of ED admission to evaluate the clinical severity of each patient. The DNI for each patient was determined using venous blood in ethylenediaminetetraacetic containing vacutainers on presentation to the ED (Time-0; within 15 min after ED admission), Time-12 (12 ± 6 h after admission), and Time-24 (24 ± 6 h after admission). To assess the DNI, we used the same type of hematology analyzer (ADVIA 2120; Siemens, Forchheim, Germany) used for the analysis of the CBC.
Outcomes and definition
AKI severity was evaluated according to the staging system devised by the AKIN. Increases in serum creatinine levels and decreases in urine output were used as markers reflecting AKI severity. The primary outcome was the acute progression to AKIN stage 3 disease (need for RRT, 300% increase in the serum creatinine level from the baseline, a serum creatinine level of 4.0 mg/dL with an acute rise of at least 0.5 mg/dL, urine output of 0.3 mL/kg per h × 24 h or anuria for 12 h) within 7 days after ED admission (22). According to the definition of AKIN stage 3 disease, we calculated changes in the serum creatinine levels and analyzed the medical records. Finally, we confirmed the occurrence of severe AKI. The secondary outcome was all-cause mortality within 30 days. We defined the baseline creatinine level as the lowest outpatient serum creatinine level from the 6 months before the admission. If there was no available serum creatinine value from before the ED admission, the baseline serum creatinine level was defined as the lowest from the ED admission.
The specific analyzers we used comprised an optical system based on a cytochemical myeloperoxidase tungsten-halogen channel (that measures and differentiates neutrophils, eosinophils, lymphocytes, monocytes, and large unstained cells based on size and myeloperoxidase staining intensity) and a laser diode channel (that calculates, classifies, and counts cell types with respect to lobularity/nuclear density and size) (9, 11, 16). The DNI was then calculated by subtracting the fraction of mature PMNs from the sum of the myeloperoxidase-reactive cells, detecting the circulating IGs as the leukocyte sub-fraction (9, 11, 16).
We represented demographic and clinical data as medians (interquartile ranges), means and standard deviations, percentages, or frequencies, as appropriate. Continuous variables and categorical variables were compared using two-sample t tests or Mann–Whitney U tests, and chi-square or Fisher exact tests. We calculated a linear two-factor mixed model with a repeated measures covariance pattern with unstructured covariance within patients to determine the significance of the differences between the groups over time. The model included two fixed effects: the diagnostic effect for clinical outcomes (development and non-development of severe AKI or 30-day mortality) and the time effect (DNI at Time-0, 12, and 24). We performed univariable analyses to determine the relationships among the demographic and clinical data. To highlight the independent diagnostic indicators of severe AKI, we selected variables with a P value <0.05 from our univariable analysis and clarified the independent prognostic factor to be the development of severe AKI in the early stage of sepsis using multivariable logistic regression analysis with a stepwise approach. Considering time-to-event data, we also performed a multivariate Cox proportional hazard regression analysis using a stepwise approach to determine the promising predictors of 30-day mortality. Consequently, the results are shown for forward conditional stepwise selections of clinical markers with P < 0.05 for entry and P < 0.05 for retention. Using receiver operating characteristic (ROC) curves, we identified the area under the curve (AUC) to verify the predictive ability of the DNI for the development of severe AKI. We confirmed the optimal cutoff of the DNI using Youden method for discriminating between the development and non-development of severe AKI. These results were represented as odds ratios (ORs) and hazard ratios (HRs) and 95% confidential intervals (CIs). Considering the development of severe AKI, we compared the diagnostic performance of each marker including the DNI value 12 h after ED admission, and WBC, CRP, lactate, procalcitonin, neutrophil ratio, and DNI values on ED admission with the AUC. In addition, ROC curve analysis was conducted by combining the DNI and the GFR value on admission. We measured the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) values to verify the improvement of the prediction model by adding the DNI for the prediction of severe AKI. To determine the statistical significance of the IDI and NRI indices, we performed resampling 1,000 times using a standard bootstrap method.
We performed multivariable logistic regression analysis to validate the independent association of the DNI with severe AKI development in septic shock patients, according to Sepsis 3 criteria and three outcomes, including severe AKI development according to urine output, creatinine elevation, and both criteria. Using ROC curves, we evaluated the AUC to verify the predictive ability of the DNI for the development of severe AKI according to the Sepsis 3 criteria and the criteria including urine output and creatinine elevation. We compared the predictability of DNI values for the development of severe AKI with respect to the criteria using ROC curves with the bootstrapping method.
Statistical analyses were performed using SAS, version 9.2 (SAS Institute Inc, Cary, NC) and MedCalc Statistical Software version 16.4.3 (MedCalc Software bvba, Ostend, Belgium). A P value < 0.05 was considered significant.
Study population, clinical evaluation, and treatment
Figure 1 reveals the enrollment and clinical outcome data of the patients with septic shock registered in the EGDT/SEPSIS program (Fig. 1). A total of 349 patients with non- or mildly reduced renal function at ED admission were enrolled in this study. We excluded three patients who died within 7 days without the development of AKI. Fifty-four patients (15.6%) developed severe AKI within 7 days after ED admission (Table 1). The incidence of all-cause 30-day mortality was 14%. Patients who developed severe AKI had a significantly higher 30-day mortality (66.7% vs. 3.4%, respectively, P < 0.001) than those without severe AKI development. The linear-mixed model revealed significant differences in the DNI values between patients grouped according to 30-day survival and development of severe AKI (all; group × time; P < 0.001) from ED admission to 24 h later (Fig. 2, A and B).
DNI as a predictor of severe AKI in sepsis
In the ROC curve analysis for the prediction of the development of severe AKI, the areas under the ROC curves with respect to the DNI at Times-0 and 12 were 0.730 (P < 0.001) and 0.798 (P < 0.001), respectively (Fig. 2, C and D). The univariable logistic regression analysis revealed significant differences in the DNI values at different time-points between patients who did and did not develop severe AKI (Supplemental Digital Content 2, https://links.lww.com/SHK/A848). Multivariable logistic regression analysis demonstrated that increases in the DNI values at Time-0 (OR, 1.060; 95% CI, 1.028–1.093; P < 0.001) and Time-12 (OR, 1.086; 95% CI, 1.049–1.125; P < 0.001) were strong independent predicting factors for the development of severe AKI (Table 2). The optimal DNI cut-off values at Time-0 and 12 were 14.0% (sensitivity: 55.6 [42.3–68.8]; specificity: 85.4 [81.2–89.3]; positive predictive value: 41.1 [29.8–52.4]; negative predictive value: 91.2 [87.9–94.6]; likelihood ratio: 3.773 [2.619–5.434]) and 13.3% (sensitivity: 72.9 [60.3–85.5]; specificity: 87.1 [82.9–91.2]; positive predictive value: 52.2 [40.3–64.2]; negative predictive value: 94.3 [91.3–97.3]; likelihood ratio: 5.628 [3.902–8.119]) (Fig. 2, C and D). The increasing predictability of severe AKI development in patients with severe sepsis or septic shock was closely associated with a DNI ≥14.0% at Time-0 (OR, 7.238; 95% CI: 3.867–13.547; P < 0.001) and ≥13.3% at Time-12 (OR, 18.089; 95% CI: 8.656–37.800; P < 0.001).
DNI as a predictor of 30-day mortality in sepsis
Further multivariable Cox regression analyses demonstrated that higher DNI values at Time-0 and Time-12 were strong independent predictors of 30-day mortality (Supplemental Digital Content 3, https://links.lww.com/SHK/A848). The C-statistics of DNI Time-0 and DNI Time-12 were 0.648 and 0.768, respectively. A log-rank test also showed the development of severe AKI to be an independent predictor of 30-day mortality HR: 25.2, 95% CI: 13.24–47.95; P < 0.001) in sepsis patients with normal or mildly reduced renal function (Fig. 3). The increasing predictability of 30-day mortality in the present study was closely associated with a DNI ≥6.0% at Time-0 (OR, 2.757; 95% CI: 1.517–5.010; P < 0.001) and ≥13.3% at Time-12 (HR, 9.244; 95% CI: 4.676–18.275; P < 0.001) (Supplemental Digital Content 4, https://links.lww.com/SHK/A848).
Comparison of the DNI and conventional clinical markers as predictors of AKI development in patients with sepsis
To predict the development of severe AKI, comparisons of the ROC curves showed that the area under the ROC (AUROC) for the DNI at ED admission was significantly superior to those of other markers (CRP, WBC, and neutrophil levels). The AUROC for DNI Time-12 was significantly superior to that for procalcitonin. Moreover, the DNI value at ED admission was not significantly inferior to those for lactate and procalcitonin at ED admission, and the DNI value at Time-12 also had no significant inferiority to lactate (Fig. 4 and Supplemental Digital Content 5, https://links.lww.com/SHK/A848). When comparing the C-statistics of the DNI to those of other markers, the C-statistics of the DNI at Time-12 was statistically superior to those of CRP, WBC, procalcitonin, and neutrophils in predicting 30-day mortality. The DNI value at Time-12 was similar to that for lactate in the predictability of 30-day mortality (Supplemental Digital Content 6 and 7, https://links.lww.com/SHK/A848).
Prognostic value of the DNI in combination with conventional risk factors
The IDI and NRI indices are indicators used in the verification of improving reclassification in a nested model, thus demonstrating how the predictive power is improved when the DNI is added to traditional risk factors. The addition of the DNI yielded a significantly positive IDI and NRI for DNI values in predicting severe AKI at Time-0 (Table 3 and supplemental Digital Content 8, https://links.lww.com/SHK/A848). Furthermore, the addition of the DNI resulted in a significantly positive IDI for DNI values in predicting 30-day mortality at Time-0 and 12. The addition of the DNI at Time-0 or 12 to the GFR (0.724) on ED admission significantly improved the AUC compared with that of the GFR alone (0.819; P = 0.025 and 0.855; P = 0.004) (Supplemental Digital Content 9, https://links.lww.com/SHK/A848).
Predictive ability of the DNI for the development of severe AKI according to Sepsis 2 and 3 criteria
Patients enrolled in the present study all met the definition of septic shock using the Sepsis 2 criteria. Of all patients included in this study, 168 were in agreement with the definition of septic shock according to the Sepsis 3 criteria. We excluded two patients who died without AKI development within 7 days after ED admission. Among the 166 patients, 46 patients (27.7%) developed severe AKI within 7 days. In the ROC curve analysis for the prediction of the development of severe AKI, the AUROC curves, with respect to the DNI at Times-0 and 12, were 0.713 (95% CI, 0.620–0.807; P < 0.001) and 0.849 (95% CI, 0.780–0.919; P < 0.001), respectively. There were no significant differences in the predictability of DNI values at Time-0 and 12 for the development of severe AKI between septic shock patients using the Sepsis 2 criteria (0.730; 95% CI, 0.649–0.812 and 0.819; 95% CI, 0.740–0.898, respectively) and patients who met the Sepsis 3 criteria (0.713; 95% CI, 0.620–0.807 and 0.849; 95% CI, 0.780–0.919, respectively) (P = 0.505 and 0.418, respectively) (Supplemental Digital Content 10 and 11, https://links.lww.com/SHK/A848).
Predictive ability of the DNI for the development of severe AKI according to urine output and creatinine elevation criteria
According to the urine output and the elevated creatinine criteria, 47 and 30 patients developed severe AKI, respectively. Twenty-three patients met both criteria. In the ROC curve analysis for the prediction of the severe AKI according to each criterion, the AUROC curves with respect to the DNI were statistically significant. There was no significant difference in the predictability of DNI values at Time-0 and 12 for the development of severe AKI between urine output (0.724; 95% CI, 0.636–0.813 and 0.821; 95% CI, 0.824–0.900, respectively) and creatinine elevation (0.711; 95% CI, 0.602–0.820 and 0.803; 0.695–0.912; P = 0.673 and P = 0.838, respectively) criteria (Supplemental Digital Content 12 and 13, https://links.lww.com/SHK/A848).
Sepsis is a clinically complex condition, and is a systemic inflammatory response accompanying an infection (23). Sepsis-induced AKI is one of the most common and life-threatening complications of sepsis (23). Hemodynamic instability caused by a decrease in renal blood flow leads to AKI by severe sepsis or septic shock for a long time (24). Currently, sepsis-induced AKI develops under conditions of renal vasodilatation and increased renal blood flow (23). Therefore, four pathophysiological mechanisms that differ from the traditional paradigm of ischemia as tubular necrosis were proposed in sepsis-induced AKI (23). First, the progressive and systemic deterioration of hemodynamics in sepsis may lead to oxidative stress and renal microvascular dysfunction (1, 23). Second, the excessive production of NO and ROS by the systemic inflammatory process directly damages respiration and the protein of mitochondria (23). Third, microvascular dysfunction induces the release of microparticles that aggravate inflammation and coagulation during cellular activation and apoptosis (23). Finally, cytokine and chemokine-mediated inflammatory responses progress as systemic effects of sepsis (1, 23).
The creation of a vicious cycle by leukocyte activation in progressive and systemic inflammatory response is induced by increased levels of endothelial adhesion molecules as a result of activated endothelium by circulating inflammatory cytokines (23, 25). In severe sepsis and septic shock cases, inflammatory responses including leukocyte activation are believed to be among the most important factors for the pathophysiology of septic AKI (23, 26). The present study demonstrated that a higher DNI value at ED admission and Time-12 could independently predict the acute development of severe kidney injury including the need for CRRT or defining stage 3 disease in patients with severe sepsis or septic shock who have normal or mildly decreased renal function at the time of ED admission. Furthermore, the DNI can also be an independent predictor of 30-day mortality risk. Therefore, it is plausible that early DNI values reflecting dysregulated host systemic immune response can predict the severe deterioration of kidney function in patients with sepsis.
Considering the decreased kidney function due to sterile inflammation, a previous study by Kong et al. (16) demonstrated that increased DNI values within 2 h (OR, 1.632; 95% CI, 1.357–1.964; P < 0.001) after ED admission were strong independent predictors of contrast-induced nephropathy (CIN) among patients with ST elevation myocardial infarction who underwent percutaneous coronary intervention (16). DNI values ≥1.8% within 2 h after ED admission significantly increased the predictability of the development of CIN (OR, 12.494; 95% CI, 6.540–23.87; P < 0.001) (16). Although patients with suspected sepsis show normal or mildly reduced kidney function, physicians should pay more attention to kidney injury progression in the ED. To improve clinical outcomes, our study also suggested the practical advantage of the DNI in predicting the deterioration of renal function and establishing treatment and/or preventive strategies including optimal fluid management, avoidance of nephrotoxic agents and CRRT as aggressive treatment in patients with severe sepsis or septic shock at the time of ED presentation.
The APACHE II score calculation used a number of laboratory values and indicators of both acute and chronic diseases to estimate mortality in the ICU (27). These scoring systems have disadvantages associated with difficulties in simply and serially calculating scores in the ED, in which the early prediction of clinical outcomes may be important. Nie et al. (28) determined that procalcitonin (PCT) was a predictive marker for AKI development during 3 consecutive days in patients with suspected infection because PCT is well known to be a useful and accurate biomarker for infection and sepsis. The present study showed the AUROC for DNI Time-12 was significantly superior to that for PCT, without significant inferiority to lactate and PCT at ED admission in predicting the development of severe AKI. Neutrophil gelatinase-associated lipocalin (NGAL) and presepsin were also evaluated as biomarkers for predicting septic AKI (29, 30). Although NGAL can detect the development of AKI before the elevation of S-Cr levels, in two recently conducted systemic reviews and meta-analyses the clinical utility of NGAL in predicting AKI occurrence in septic patients was not shown, and could be limited by its low specificity and positive predictive value (31, 32). Furthermore, pre-existing kidney disease may interfere with NGAL concentrations (36). Presepsin may not be a reliable index in sepsis patients with a more advanced form of AKI (26). A recent study reported that pro-inflammatory and endothelial activation mediators including TNF-α, IL-1ß, and IL-6, soluble endothelium selectin, and the urinary albumin-to-creatinine ratio are significantly associated with mortality in sepsis patients (33). Intra-patient variability over time should be considered because circulating cytokines have short half-lives (34). The DNI can be automatically measured along with the CBC, and routinely and rapidly determines the fraction of circulating IGs in critically ill patients without additional cost, time and equipment, unlike in the case of CRP, proinflammatory cytokines, lactate, NGAL, and procalcitonin (11). In the initial period of AKI in sepsis, early accurate prediction, and timely intervention play a critical role in the improvement of prognoses (31). Despite the absence of the reflection of renal damage, the diagnosis of AKI relies on serum creatinine or GFR as a late biomarker of damaged renal function according to guidelines (31). The present study identified that the addition of the DNI at Time-0 or 12 to the GFR value on ED admission significantly improved the predictability in the early stages after ED admission compared with the use of the GFR alone.
Our present study has several limitations. Although we used a prospective CP using a standardized and predetermined protocol, this study was retrospectively performed in a cohort derived from a single, tertiary, academic hospital. Therefore, it was difficult to control for confounding factors, leading to an increased risk of selection bias. Second, the EGDT as a CP was revised to SEPSIS according to changes in the results of clinical studies on EGDT. This revised CP protocol included some changes pertaining to standard treatment by bundle management. However, as some changes have been validated by several studies, it may not affect clinical outcomes including the development of AKI and mortality. Lastly, sepsis frequently progresses to septic shock and multiple organ dysfunction (23). Several studies have revealed that elevated troponin and plasma brain natriuretic peptide on admission are associated with higher systolic myocardial dysfunction and mortality in patients with severe sepsis and septic shock (35). Despite the use of a prospective registry as a CP, we could not investigate the presence of known predictors of septic AKI development and other organ dysfunctions, such as proinflammatory cytokines, presepsin, troponin, brain natriuretic peptide, and NGAL, in our EGDT/SEPSIS protocol. Therefore, we were unable to compare the degree of predictability of all indicators of septic AKI to identify the usefulness of the DNI. Further studies are required to validate and compare the usefulness of these indicators as prognostic markers in patients with severe sepsis or septic shock. In summary, we found that an elevated DNI value was an independent predictor of some clinical end-points, including the development of severe AKI and 30-day mortality in patients with severe sepsis and septic shock. The DNI can be used to determine the initial treatment strategies for sepsis-induced AKI as it can be quickly measured without additional costs and effort.
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