The potential utility of urinary biomarkers for risk prediction in combat casualties: a prospective observational cohort study

Multiple blood gas variables predict AKI survival in an independent manner

BACKGROUND AND AIM

Acute kidney injury (AKI) is becoming increasingly prevalent among hospitalized patients and carries a poor prognosis. While new biomarkers show promise in identifying early stages of AKI, accurately predicting severe outcomes such as the need for kidney replacement therapy (KRT) or death remains a challenge. However, blood gas analyses (BGA) can be used to diagnose life-threatening complications associated with AKI. The objective of this study was to assess the role of BGA as a biomarker panel in both emerging and established cases of AKI.

METHODS

Retrospective observational study examining subjects with newly developed acute kidney injury (AKI). The study will document venous and arterial pH, pCO2, and actual bicarbonate levels upon hospital admission and at the onset of AKI. The primary endpoints include in-hospital mortality, the need for kidney replacement therapy (KRT), and the recovery of kidney function (ROKF).

RESULTS

A total of 202 individuals were included in the study. Three variables were found to be independent predictors of in-hospital survival: admission arterial pH, arterial pH at acute kidney injury (AKI) onset, and arterial pCO2 at AKI onset. Additionally, venous pCO2 at AKI onset was identified as an independent predictor for the need of kidney replacement therapy (KRT).

CONCLUSIONS

Our study suggests that blood gas analysis may have a potential role in predicting severe outcome variables in acute kidney injury (AKI). The associated costs are minimal.

Metabolomics in Acute Kidney Injury: The Clinical Perspective

BACKGROUND

Acute kidney injury (AKI) affects increasing numbers of hospitalized patients worldwide. The diagnosis of AKI is made too late in most individuals since it is still based on dynamic changes in serum creatinine. In recent years, new AKI biomarkers have been identified; however, none of these can reliably replace serum creatinine yet. Metabolomic profiling (metabolomics) allows the concomitant detection and quantification of large numbers of metabolites from biological specimens. The current article aims to summarize clinical studies on metabolomics in AKI diagnosis and risk prediction.

METHODS

The following databases were searched for references: PubMed, Web of Science, Cochrane Library, and Scopus, and the period lasted from 1940 until 2022. The following terms were utilized: 'AKI' OR 'Acute Kidney Injury' OR 'Acute Renal Failure' AND 'metabolomics' OR 'metabolic profiling' OR 'omics' AND 'risk' OR 'death' OR 'survival' OR 'dialysis' OR 'KRT' OR 'kidney replacement therapy' OR 'RRT' OR 'renal replacement therapy' OR 'recovery of kidney function' OR 'renal recovery' OR 'kidney recovery' OR 'outcome'. Studies on AKI risk prediction were only selected if metabolomic profiling allowed differentiation between subjects that fulfilled a risk category (death or KRT or recovery of kidney function) and those who did not. Experimental (animal-based) studies were not included.

RESULTS

In total, eight studies were identified. Six studies were related to the diagnosis of AKI; two studies were performed on metabolic analysis in AKI risk (death) prediction. Metabolomics studies in AKI already helped to identify new biomarkers for AKI diagnosis. The data on metabolomics for AKI risk prediction (death, KRT, recovery of kidney function), however, are very limited.

CONCLUSIONS

Both the heterogenous etiology and the high degree of pathogenetic complexity of AKI most likely require integrated approaches such as metabolomics and/or additional types of '-omics' studies to improve clinical outcomes in AKI.

Neutrophil Gelatinase-associated Lipocalin Predicts Post-traumatic Acute Kidney Injury in Severely Injured Patients

BACKGROUND

Early detection of acute kidney injury (AKI) is crucial in the management of multiple-organ dysfunction syndrome in severely injured patients. Standard laboratory parameters usually increase with temporal delay. Therefore, we evaluated neutrophil gelatinase-associated lipocalin (NGAL) as an early marker for acute kidney injury.

PATIENTS AND METHODS

We retrospectively evaluated patients admitted to a level 1 trauma center. We collected clinicodemographic data and measured kidney-related factors and plasma cytokines.

RESULTS

A total of 39 patients were included. Patients with AKI had significantly higher levels not only of serum creatinine and urea, but also of NGAL (all p<0.001) than patients without AKI. The optimal NGAL cut-off value was determined to be 177 ng/ml, showing significant correlation with imminent or manifest AKI (p<0.001). Other independent markers correlated with AKI included pre-existing chronic kidney disease, use of catecholamines, and severe injury (p<0.001).

CONCLUSION

The serum level of NGAL is feasible early predictor of AKI.

Neutrophil gelatinase-associated lipocalin as a biomarker for short-term outcomes among trauma patients: A single-center observational study

BACKGROUND

Urinary biomarkers for organ dysfunction could predict the outcomes of severe trauma patients. However, the use of neutrophil gelatinase-associated lipocalin (NGAL) as a biomarker of trauma is not well studied.

OBJECTIVES

To evaluate the association between the short-term prognosis of trauma patients and NGAL levels.

METHODS

We conducted a single center study and compared predictive performances between NGAL levels and the trauma severity.

RESULTS

A total of 104 patients were included in the study. Patients were divided into two groups based on ISS score of 16. There was no significant difference in patient characteristics based on trauma severity. However, the lactate level was significantly higher in the more severe group. There was a significant association between urinary NGAL levels and trauma severity indicators, such as intensive care unit stay (ICU) (p = 0.005) and emergency care unit (ECU) stay (p = 0.049). In addition, receiver operating curve analysis showed that as a predictor, NGAL could be used for detecting severity with moderate precision, especially for short-term outcomes (specificity 70.6 for ICU and 69.0 for ECU stay).

CONCLUSION

In this study, we revealed that the level of NGAL could predict the degree of invasiveness in trauma patients with moderate precision and estimate the duration of treatment during the acute phase. It is necessary to examine the validity of the findings of this study using a prospective, cohort, and multi-center collaborative study design.

Urinary metabolites predict mortality or need for renal replacement therapy after combat injury

BACKGROUND

Traditionally, patient risk scoring is done by evaluating vital signs and clinical severity scores with clinical intuition. Urinary biomarkers can add objectivity to these models to make risk prediction more accurate. We used metabolomics to identify prognostic urinary biomarkers of mortality or need for renal replacement therapy (RRT). Additionally, we assessed acute kidney injury (AKI) diagnosis, injury severity score (ISS), and AKI stage.

METHODS

Urine samples (n = 82) from a previous study of combat casualties were evaluated using proton nuclear magnetic resonance (¹H-NMR) spectroscopy. Chenomx software was used to identify and quantify urinary metabolites. Metabolite concentrations were normalized by urine output, autoscaled, and log-transformed. Partial least squares discriminant analysis (PLS-DA) and statistical analysis were performed. Receiver operating characteristic (ROC) curves were used to assess prognostic utility of biomarkers for mortality and RRT.

RESULTS

Eighty-four (84) metabolites were identified and quantified in each urine sample. Of these, 11 were identified as drugs or drug metabolites and excluded. The PLS-DA models for ISS and AKI diagnosis did not have acceptable model statistics. Therefore, only mortality/RRT and AKI stage were analyzed further. Of 73 analyzed metabolites, 9 were significantly associated with mortality/RRT (p < 0.05) and 11 were significantly associated with AKI stage (p < 0.05). 1-Methylnicotinamide was the only metabolite to be significantly associated (p < 0.05) with all outcomes and was significantly higher (p < 0.05) in patients with adverse outcomes. Elevated lactate and 1-methylnicotinamide levels were associated with higher AKI stage and mortality and RRT, whereas elevated glycine levels were associated with patients who survived and did not require RRT, or had less severe AKI. ROC curves for each of these metabolites and the combined panel had good predictive value (lactate AUC = 0.901, 1-methylnicotinamide AUC = 0.864, glycine AUC = 0.735, panel AUC = 0.858).

CONCLUSIONS

We identified urinary metabolites associated with AKI stage and the primary outcome of mortality or need for RRT. Lactate, 1-methylnicotinamide, and glycine may be used as a panel of predictive biomarkers for mortality and RRT. 1-Methylnicotinamide is a novel biomarker associated with adverse outcomes. Additional studies are necessary to determine how these metabolites can be utilized in clinically-relevant risk prediction models.

Acute Kidney Injury in Active Wars and Other Man-Made Disasters

Acute kidney injury (AKI) is frequent during wars and other man-made disasters, and contributes significantly to the overall death toll. War-related AKI may develop as a result of polytrauma, traumatic bleeding and hypovolemia, chemical and airborne toxin exposure, and crush syndrome. Thus, prerenal, intrinsic renal, or postrenal AKI may develop at the battlefield, in field hospitals, or tertiary care centers, resulting not only from traumatic, but also nontraumatic, etiologies. The prognosis usually is unfavorable because of systemic and polytrauma-related complications and suboptimal therapeutic interventions. Measures for decreasing the risk of AKI include making preparations for foreseeable disasters, and early management of polytrauma-related complications, hypovolemia, and other pathogenetic mechanisms. Transporting casualties initially to field hospitals, and afterward to higher-level health care facilities at the earliest convenience, is critical. Other man-made disasters also may cause AKI; however, the number of patients is mostly lower and treatment possibilities are broader than in war. If there is no alternative other than prolonged field care, the medical community must be prepared to offer health care and even perform dialysis in austere conditions, which in that case, is the only option to decrease the death toll resulting from AKI.

Assessing the NephroCheck® Test System in Predicting the Risk of Death or Dialysis in Burn Patients

Acute kidney injury (AKI) is associated with high mortality in burn patients. Urinary biomarkers can aid in the prediction of AKI and its consequences, such as death and the need for renal replacement therapy (RRT). The purpose of this study was to investigate a novel methodology for detecting urinary biomarkers, the NephroCheck® Test System, and assess its ability to predict death or the need for RRT in burn patients. Burn patients admitted to the United States Army Institute of Surgical Research (USAISR) burn intensive care unit were prospectively enrolled between March 2016 and April 2018. A urine sample was obtained from all study participants using the NephroCheck® system. Patient and injury characteristics were gathered, and descriptive statistics were calculated and multivariable logistic regression analyses were performed using these data. Of the 69 patients in this study, 15 patients (21.7%) attained the composite outcome of death or needing RRT within 30 days of urine collection. NephroCheck® scores were higher for patients with the composite outcome, with P = 0.06 for centrifuged scores and P = 0.04 for noncentrifuged scores. Centrifuged and noncentrifuged scores were in high agreement and correlation (R2 = 0.97, P < 0.0001). Noncentrifuged scores were significant in the unadjusted analysis, but they were not significant in the adjusted analysis. Although these scores had a lower sensitivity and negative predictive value compared with other parameters, they had the second highest specificity and positive predictive value. NephroCheck® scores were higher in burn patients with the composite outcome of death or needing RRT, and they demonstrated comparable sensitivity and specificity to creatinine and TBSA.

Predictive Value of Osteoprotegerin and Neutrophil Gelatinase-associated Lipocalin on Multiple Organ Failure in Multiple Trauma

BACKGROUND/AIM

Multiple organ dysfunction syndrome (MODS) is the leading cause of late posttraumatic mortality. This study analyzed the prognostic values of osteoprotegerin (OPG) and neutrophil gelatinase-associated lipocalin (NGAL/lipocalin 2) compared to interleukin-6 (IL-6) in multiply injured patients.

PATIENTS AND METHODS

A retrospective observational cohort study on multiply injured patients with an injury severity score (ISS) of ≥16 was performed. OPG, NGAL and IL-6 blood concentrations were measured. Statistical analysis comprised receiver-operating-characteristic (ROC) analysis with the corresponding area under the curve (AUC).

RESULTS

Thirty-nine patients with a mean ISS of 34±11 were included. Fourteen patients (36%) developed MODS and 8 patients (21%) died. Plasma levels of NGAL, OPG, and IL-6 were significantly elevated in the MODS+ group. Each biomarker positively correlated with MODS score and diagnosis of MODS.

CONCLUSION

NGAL and OPG might be indicative of MODS and could have the potential to be biomarkers in the early detection of patients at risk of posttraumatic MODS.

Urinary Biomarkers are Associated with Severity and Mechanism of Injury

Combat-related blast trauma results in massive tissue injury and tends to involve multiple systems. Further, an acute measure of injury severity based on underlying biological mechanisms may be important for the triage and treatment of these types of patients. We hypothesized that urinary biomarkers (UBs) would reflect severity of injury and that they would be elevated for blast injuries compared with gunshot wounds (GSW) in a cohort of combat casualties. We also postulated that UBs would be higher in patients with burns compared with patients with non-burn trauma in a civilian cohort. Among 80 service members who sustained combat-related injuries, we performed generalized estimating equations to compare differences in log-transformed concentrations of the UBs by both injury severity and injury mechanism. Among 22 civilian patients, we performed Kruskal-Wallis tests to compare differences for the UBs stratified by burn and non-burn trauma. In the military cohort, with the exception of IL-18, all UBs were significantly (P <0.05) higher for patients with a severe combat-related injury (Injury Severity Score ≥25). In addition, all crude UBs concentrations were significantly higher for blast versus GSW patients (P < 0.05). After adjusting for injury severity score and time of UB draw, KIM-1 (2.80 vs. 2.31; P = 0.03) and LFABP (-1.11 vs. -1.92; P = 0.02) were significantly higher for patients with a blast mechanism of injury. There were no significant differences in UBs between burn and non-burn civilian trauma patients. Future studies are needed to understand the physiologic response to trauma and the extent that UBs reflect these underlying processes.

Predictive value of cystatin C for the identification of illness severity in adult patients in a mixed intensive care unit

OBJECTIVES

This study compared serum cystatin C (CysC) with conventional biomarkers of renal function in terms of their ability to predict illness severity in patients in a mixed intensive care unit (ICU). The present study also tested the hypothesis that increased CysC could predict illness severity in different clinical conditions in adult patients admitted to the ICU.

DESIGN AND METHODS

The performance of serum creatinine, urea and CysC, as well as the Glomerular Filtration Rate (GFR) estimates (Cockcroft-Gault/MDRD/Larsson and CKD-EPI Equations) in predicting illness severity was compared in 60 critically ill patients. Adult patients admitted to the hospital were screened for eligibility in this prospective and observational study. The mean patient age was 52±19years. The average APACHE II score was 9.5±6 for the entire sample. The patients were assigned to two different degrees of severity, and the internally derived cut off value was an APACHE II score<10 or ≥10.

RESULTS

Both serum CysC and urea showed significant correlations with APACHE II, even after controlling for age. Urea and CysC levels, as well as the GFR estimated by the method of Larsson and Cockcroft-Gault, remained significantly increased in patients in the APACHEII ≥10 group. The ROC curve analyses indicated that both urea and CysC levels have high sensitivity and specificity in the prediction of illness severity using the APACHE II as a gold standard prognostic stratification system. Furthermore, CysC was more accurate than the Larsson, CKD-EPI CysC, CKD-EPI Cr-CysC, Cockcroft-Gault and CKD-EPI Cr CFR estimation methods compared with the MDRD method. Additionally, CysC was a good predictor in both young and old patients, whereas urea was not predictive of illness severity.

CONCLUSIONS

Our findings suggest that CysC and GFR estimates (Larsson or CKD-EPI CysC methods) are good predictors of illness severity in adult patients hospitalized in a mixed ICU.

Dynamic Assessment of Functional Lipidomic Analysis in Human Urine

The development of enabling mass spectrometry platforms for the quantification of diverse lipid species in human urine is of paramount importance for understanding metabolic homeostasis in normal and pathophysiological conditions. Urine represents a non-invasive biofluid that can capture distinct differences in an individual's physiological status. However, currently there is a lack of quantitative workflows to engage in high throughput lipidomic analysis. This study describes the development of a MS/MS(ALL) shotgun lipidomic workflow and a micro liquid chromatography-high resolution tandem mass spectrometry (LC-MS/MS) workflow for urine structural and mediator lipid analysis, respectively. This workflow was deployed to understand biofluid sample handling and collection, extraction efficiency, and natural human variation over time. Utilization of 0.5 mL of urine for structural lipidomic analysis resulted in reproducible quantification of more than 600 lipid molecular species from over 20 lipid classes. Analysis of 1 mL of urine routinely quantified in excess of 55 mediator lipid metabolites comprised of octadecanoids, eicosanoids, and docosanoids generated by lipoxygenase, cyclooxygenase, and cytochrome P450 activities. In summary, the high-throughput functional lipidomics workflow described in this study demonstrates an impressive robustness and reproducibility that can be utilized for population health and precision medicine applications.