Prognostic value of fibrinogen to albumin ratios among critically ill patients with acute kidney injury

Serum Nostrin-A risk factor of death, kidney replacement therapy and acute kidney disease in acute kidney injury

BACKGROUND

The prediction of Acute Kidney Injury (AKI)-related outcomes remains challenging. Persistent kidney excretory dysfunction for longer than 7 days has been defined as Acute Kidney Disease (AKD). In this study, we prospectively quantified serum Nostrin, an essential regulator of endothelial NO metabolism, in hospitalized patients with AKI.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

In-hospital subjects with AKI of various etiology were identified through the in-hospital AKI alert system of the Brandenburg University Hospital. Serum Nostrin, and serum NGAL and KIM-1 were measured within a maximum of 48 hours from the timepoint of initial diagnosis of AKI. The following endpoints were defined: in-hospital death, need of kidney replacement therapy (KRT), recovery of kidney function (ROKF) until discharge.

RESULTS

AKI patients had significantly higher serum Nostrin levels compared to Controls. The level of serum Nostrin increased significantly with the severity of AKI. Within the group of AKI patients (n = 150) the in-hospital mortality was 16.7%, KRT was performed in 39.3%, no ROKF occurred in 28%. Patients who required KRT had significantly higher levels of serum Nostrin compared to patients who did not require KRT. Significantly higher levels of serum Nostrin were also detected in AKI patients without ROKF compared to patients with ROKF. In addition, low serum Nostrin levels at the timepoint of AKI diagnosis were predictive of in-hospital survival. For comparison, the serum concentrations of NGAL and KIM-1 were determined in parallel to the Nostrin concentrations and the results confirm the prognostic properties of serum Nostrin in AKI.

CONCLUSIONS

The current study suggests serum Nostrin as novel biomarker of AKI-associated mortality, KRT and Acute Kidney Disease.

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.

Biomarker-Based Prediction of Survival and Recovery of Kidney Function in Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) affects increasing numbers of hospitalized patients; the prognosis remains poor. The diagnosis is still based on the 2012 published KDIGO criteria. Numerous new AKI biomarkers have been identified in recent years; they either reflect impaired excretory function or structural damage. The majority of markers are useful for AKI recognition under certain circumstances. Fewer data are available on the role of biomarkers in the prediction of in-hospital survival and renal recovery post-AKI. The current article is intended to provide information about these two aspects.

SUMMARY

The following databases were screened: PubMed, Web of Science, Cochrane Library, Scopus. The period lasted from 2000 until 2022. The following terms were applied: "AKI" AND "biomarker" AND "survival" OR "mortality" OR "recovery of kidney function" OR "renal recovery" OR "kidney recovery". The following terms were used for additional literature search: "TIMP-2" AND "IGFBP7" and "RNA biomarker" AND "hematology". Regarding mortality, exclusively those studies were selected that addressed the in-hospital mortality. Nine (9) studies were identified that evaluated biomarker-based prediction of in-hospital mortality and/or of recovery of kidney function (ROKF). A homogenous definition of ROKF is however missing yet. Currently, some biomarkers, measured early during the course of the disease, are associated with increased mortality risk and/or with a higher chance of renal recovery.

KEY MESSAGES

The literature provides only a few biomarker-related studies that address the issues of mortality and recovery. The definition of ROKF needs to be homogenized.

Stratification of Acute Kidney Injury Risk, Disease Severity, and Outcomes by Electrolyte Disturbances

Acute kidney injury (AKI) affects up to 30% of all hospitalized patients in Central Europe and the USA. New biomarker molecules have been identified in recent years; most studies performed so far however aimed to identify markers for diagnostic purposes. Serum electrolytes such as sodium and potassium are quantified in more or less all hospitalized patients. Aim of the article is to review the literature on the AKI predictive role of four distinct serum electrolytes in evolving/progressing AKI. The following databases were searched for references: PubMed, Web of Science, Cochrane Library, and Scopus. The period lasted from 2010 until 2022. The following terms were utilized: "AKI" AND "sodium" OR "potassium" OR "calcium" OR "phosphate" AND "risk" OR "dialysis" OR "recovery of kidney function" OR "renal recovery" OR "kidney recovery" OR "outcome". Finally, 17 references were selected. The included studies were mostly retrospective in nature. Particularly, hyponatremia has been shown to be associated with an overall poor clinical outcome. The association between dysnatremia and AKI is anything but consistent. Hyperkalemia and potassium variability are most likely AKI predictive. Serum calcium and AKI risk are associated in a U-shaped manner. Higher phosphate levels potentially predict AKI in non-coronavirus disease 2019 (COVID-19) patients. The literature suggests that admission electrolytes can offer valuable information about AKI onset during follow-up. Limited data are however available on follow-up characteristics such as the need for dialysis or the chance of renal recovery. These aspects are of particular interest from the nephrologist's perspective.

Increased Serum Sodium at Acute Kidney Injury Onset Predicts In-Hospital Death

Background

Over the last decades, acute kidney injury (AKI) has been identified as a potentially fatal diagnosis which substantially increases in-hospital mortality in the short term and morbidity/mortality in the long term. However, reliable biomarkers for predicting AKI-associated outcomes are still missing. In this study, we assessed whether serum sodium, measured at different time points during the in-hospital treatment period, provided prognostic information in AKI.

Methods

This was a retrospective, observational cohort study. AKI subjects were identified via the in-hospital AKI alert system. Serum sodium and potassium levels were documented at five pre-defined time points: hospital admission, AKI onset, minimum estimated glomerular filtration rate, minimum and maximum of the respective electrolyte during the treatment period. In-hospital death, the need for kidney replacement therapy (KRT) and recovery of kidney function were defined as endpoints.

Results

Patients who suffered in-hospital death (n = 37, 23.1%) showed significantly higher serum sodium levels at diagnosis of AKI (survivors: 145.7 ± 2.13 vs. non-survivors: 138.8 ± 0.636 mmol/L, P = 0.003). A logistic regression model was significant for serum sodium levels in patients with in-hospital death (X², P = 0.003; odds ratio = 1.08 (1.022 - 1.141); R² = 0.082; d = 0.089). This suggests an increase of the relative risk for in-hospital death by 8% with every unit of serum sodium increase. Patients with a sodium above the upper normal range at AKI diagnosis were also more likely to suffer in-hospital death (P = 0.001).

Conclusion

In summary, we present evidence that serum sodium, measured at time of AKI diagnosis, potentially serves as a predictor for in-hospital death in patients with AKI.

Fibrinogen-to-Albumin Ratio Predicts Postcontrast Acute Kidney Injury in Patients with Non-ST Elevation Acute Coronary Syndrome after Implantation of Drug-Eluting Stents

Background

Postcontrast acute kidney injury (PC-AKI) is an adverse reaction to iodinated contrast agents. In this study, we investigated the use of fibrinogen-to-albumin ratio (FAR) as a novel inflammatory marker to track the development and progression of PC-AKI in patients with non-ST elevation acute coronary syndrome (NSTE-ACS) after the implantation of drug-eluting stents (DESs).

Methods

A total of 872 patients with NSTE-ACS were enrolled in this study. PC-AKI was identified when serum creatinine (SCr) levels increased >26.5 mol/L (0.3 mg/dL) or was 1.5 times the baseline level within 48-72 h of exposure to an iodinated contrast agent. The effects of different variables on PC-AKI were evaluated using univariate regression analysis. Multivariate logistic regression analysis was used to determine the independent predictors of PC-AKI. The predictive value of FAR was assessed by estimating the area under the receiver operating characteristic (ROC) curve.

Results

In total, 114 (13.1%) patients developed PC-AKI. The patients with PC-AKI had lower albumin levels (40.5 ± 3.4 vs. 39.0 ± 3.5, P < 0.001), higher fibrinogen levels (3.7 ± 0.6 vs. 4.1 ± 0.5, P < 0.001), and higher FAR levels (9.2 ± 1.7 vs. 10.5 ± 1.7, P < 0.001) than those with non-PC-AKI. There were no significant differences in the preoperative SCr levels between the two groups. After adjusting for confounding factors, FAR was found to be an independent predictor of PC-AKI (OR = 1.478, 95% CI = 1.298-1.684, P < 0.001). ROC analysis revealed that for PC-AKI prediction, the area under the curve for FAR was 0.702. The optimum cut-off value of FAR was 10.0, with a sensitivity of 64.9% and a specificity of 69.8%. Moreover, FAR had a higher predictive value for PC-AKI than the Mehran score (0.702 vs. 0.645).

Conclusion

Our study showed that elevated preoperative FAR was closely associated with the development of PC-AKI in patients with NSTE-ACS after implantation of DESs. Therefore, it may be worth monitoring FAR as a guide for using preventive measures to avoid the development of PC-AKI.

The predictive value of fibrinogen‐to‐albumin ratio in the active, severe active, and poor prognosis of systemic lupus erythematosus: A single‐center retrospective study

Objective

To evaluate the prediction and effect of fibrinogen‐to‐albumin ratio (FAR) on active, severe active, and poor prognosis of systemic lupus erythematosus (SLE).

Methods

One hundred and sixty‐eight patients with SLE who were treated in our hospital were enrolled, the clinical data, laboratory indexes, and disease prognosis of all patients were collected and analyzed.

Results

Triglyceride (TG), FAR, ESR, and anti‐dsDNA (+) were the influencing factors, while complement 3 (C3) was the protective factor of active SLE, the odds ratio (OR) values were 2.968, 3.698, 2.114, 2.727, and 0.652, respectively (p < 0.05). FAR, ESR, and anti‐dsDNA (+) were the influencing factors, while C3 was the protective factor of severe active SLE, the OR values were 3.791, 1.953, 2.187, and 0.742, respectively (p < 0.05). SLE disease activity index (SLEDAI), TG, FAR, and anti‐dsDNA (+) were the influencing factors, while C3 was the protective factor of poor prognosis SLE, the OR values were 3.024, 2.293, 3.012, 2.323, and 0.801, respectively (p < 0.05). FAR and FIB were positively correlated with SLEDAI, while ALB was negatively correlated with SLEDAI, the related coefficient (r) were 0.398, 0.267, −0.270, respectively. The receiver operating curve (ROC) analysis showed that the predictive values of FAR for active, severe active and poor prognosis SLE were 0.769, 0.769, and 0.734, respectively, were significant higher than FIB and ALB (p < 0.05).

Conclusion

Fibrinogen‐to‐albumin ratio was an influencing factor of active, severe active, and poor prognosis SLE had higher predictive value than FIB and ALB for the activity and prognosis of SLE.

Prognostic significance of albumin to alkaline phosphatase ratio in critically ill patients with acute kidney injury

OBJECTIVE

No epidemiological evidence has investigated the effect of albumin to alkaline phosphatase ratio (AAPR) on the prognosis among critically ill patients with acute kidney injury (AKI). We aimed to explore the prognostic value of AAPR in these patients.

METHODS

We extracted all clinical data from MIMIC III. ROC curve analysis was used to evaluate the discrimination of AAPR for predicting in-hospital mortality. A generalized additive model was applied to identify a nonlinear association between AAPR and in-hospital mortality. The Cox proportional hazards models were used to determine the association between AAPR and in-hospital and 30-day mortality.

RESULTS

A total of 6894 eligible subjects were enrolled in this study. The relationship between AAPR and in-hospital mortality was nonlinear. Multivariate analysis demonstrated that lower AAPR (AAPR < 0.35) was an independent predictor of in-hospital and 30-day mortality after adjusting for potential confounders (HR 1.74, 95% CI 1.72-2.20, P < 0.001; HR 1.89, 95% CI 1.66-2.14, P < 0.001, respectively).

CONCLUSIONS

AAPR may serve as a potential prognostic biomarker in critically ill patients with AKI and lower AAPR was associated with increased risk of in-hospital and 30-day mortality among these patients.