Urinary biomarkers of kidney tubule injury, risk of acute kidney injury, and mortality in patients with acute ischaemic stroke treated at a stroke care unit

Predictive Performance of Neutrophil Gelatinase Associated Lipocalin, Liver Type Fatty Acid Binding Protein, and Cystatin C for Acute Kidney Injury and Mortality in Severely Ill Patients

Background

Acute kidney injury (AKI) is a common condition in severely ill patients associated with poor outcomes. We assessed the associations between urinary neutrophil gelatinase-associated lipocalin (uNGAL), urinary liver-type fatty acid-binding protein (uLFABP), and urinary cystatin C (uCysC) concentrations and patient outcomes.

Methods

We assessed the predictive performances of uNGAL, uLFABP, and uCysC measured in the early phase of intensive care unit (ICU) management and at discharge from the ICU in severely ill patients for short- and long-term outcomes. The primary outcome was the occurrence of AKI during ICU stay; secondary outcomes were 28-day and 1-yr allcause mortality.

Results

In total, 1,759 patients were admitted to the ICU, and 728 (41.4%) developed AKI. Median (interquartile range, IQR) uNGAL, uLFABP, and uCysC concentrations on admission were 147.6 (39.9-827.7) ng/mL, 32.4 (10.5-96.0) ng/mL, and 0.33 (0.12-2.05) mg/L, respectively. Biomarker concentrations on admission were higher in patients who developed AKI and associated with AKI severity. Three hundred fifty-six (20.3%) and 647 (37.9%) patients had died by 28 days and 1-yr, respectively. Urinary biomarker concentrations at ICU discharge were higher in non-survivors than in survivors. The areas under the ROC curve (95% confidence interval) of uLFABP for the prediction of AKI, 28-day mortality, and 1-yr mortality (0.70 [0.67-0.72], 0.63 [0.59-0.66], and 0.57 [0.51-0.63], respectively) were inferior to those of the other biomarkers.

Conclusions

uNGAL, uLFABP, and uCysC concentrations on admission were associated with poor outcomes. However, their predictive performance, individually and in combination, was limited. Further studies are required to confirm our results.

Acute kidney injury in neurocritical care

Approximately 20% of patients with acute brain injury (ABI) also experience acute kidney injury (AKI), which worsens their outcomes. The metabolic and inflammatory changes associated with AKI likely contribute to prolonged brain injury and edema. As a result, recognizing its presence is important for effectively managing ABI and its sequelae. This review discusses the occurrence and effects of AKI in critically ill adults with neurological conditions, outlines potential mechanisms connecting AKI and ABI progression, and highlights AKI management principles. Tailored approaches include optimizing blood pressure, managing intracranial pressure, adjusting medication dosages, and assessing the type of administered fluids. Preventive measures include avoiding nephrotoxic drugs, improving hemodynamic and fluid balance, and addressing coexisting AKI syndromes. ABI patients undergoing renal replacement therapy (RRT) are more susceptible to neurological complications. RRT can negatively impact cerebral blood flow, intracranial pressure, and brain tissue oxygenation, with effects tied to specific RRT methods. Continuous RRT is favored for better hemodynamic stability and lower risk of dialysis disequilibrium syndrome. Potential RRT modifications for ABI patients include adjusted dialysate and blood flow rates, osmotherapy, and alternate anticoagulation methods. Future research should explore whether these strategies enhance outcomes and if using novel AKI biomarkers can mitigate AKI-related complications in ABI patients.

Kidney disease and stroke: epidemiology and potential mechanisms of susceptibility

Patients with chronic kidney disease (CKD) have an increased risk of both ischaemic and haemorrhagic stroke compared with the general population. Both acute and chronic kidney impairment are independently associated with poor outcome after the onset of a stroke, after adjustment for confounders. End-stage kidney disease (ESKD) is associated with a 7- and 9-fold increased incidence of both ischaemic and haemorrhagic strokes, respectively, poorer neurological outcome and a 3-fold higher mortality. Acute kidney injury (AKI) occurs in 12% of patients with stroke and is associated with a 4-fold increased mortality and unfavourable functional outcome. CKD patients seem to have less access to revascularisation techniques like thrombolysis and thrombectomy despite their poorer prognosis. Even if CKD patients could benefit from these specific treatments in acute ischaemic stroke, their prognosis remains poor. After thrombolysis, CKD is associated with a 40% increased risk of intracerebral haemorrhage (ICH), a 20% increase in mortality and poorer functional neurological outcomes. After thrombectomy, CKD is not associated with ICH but is still associated with increased mortality, and AKI with unfavourable outcome and mortality. The beneficial impact of gliflozins on the prevention of stroke is still uncertain. Non-traditional risk factors of stroke, like uraemic toxins, can lead to chronic cerebrovascular disease predisposing to stroke in CKD, notably through an increase in the blood-brain barrier permeability and impaired coagulation and thrombosis mechanisms. Preclinical and clinical studies are needed to specifically assess the impact of these non-traditional risk factors on stroke incidence and outcomes, aiming to optimize and identify potential therapeutic targets.

External Validation of the Nelson Equation for Kidney Function Decline in Patients with Acute Ischemic Stroke or Transient Ischemic Attack

Background

There is a close brain-kidney interaction following ischemic cerebrovascular disease. The new-onset kidney injury after stroke leads to severe neurological deficits and poor functional outcomes. We aimed to validate the Nelson equation for predicting the new-onset and long-term kidney function decline in patients with acute ischemic stroke (AIS) or transient ischemic attack (TIA).

Methods

A total of 3169 patients were enrolled in the Third China National Stroke Registry, whose baseline estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73 m². The outcome of interest was the incident eGFR< 60 mL/min/1.73 m² at 3 months. The prediction equation of participants with or without diabetes was validated respectively. The receiver operating characteristic curve (AUC) evaluated prediction performance. The Delong test compared the Nelson equation performance with the O'Seaghdha equation and the Chien equation. Continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were determined to evaluate the incremental effect.

Results

During the 3-mo follow-up period, among 1151 patients with diabetes, there were 31 cases (2.7%) of reduced eGFR. Meanwhile, among 2018 non-diabetic patients, there were 23 cases (1.1%) of reduced eGFR. The Nelson equation showed good discrimination and was well-calibrated in patients with diabetes (AUC 0.82, Hosmer-Lemeshow test p = 0.67) or without diabetes (AUC 0.82, Hosmer-Lemeshow test p = 0.09). The performance of the Nelson equation was superior to other equation, as increased continuous NRI (diabetic, 0.64; non-diabetic, 1.13) and IDI (diabetic, 0.10; non-diabetic, 0.13) to the Chien equation.

Conclusion

The Nelson equation reliably predicted the risks of the new-onset and long-term kidney function decline in patients with AIS or TIA, which could help clinicians screen high-risk patients and improve clinical care.

A novel risk model based on white blood cell-related biomarkers for acute kidney injury prediction in patients with ischemic stroke admitted to the intensive care unit

Background

Conventional systemic inflammatory biomarkers could predict prognosis in patients with ischemic stroke (IS) admitted to the intensive care unit (ICU). Acute kidney injury (AKI) is common in patients with IS admitted to ICU, but few studies have used systemic inflammatory biomarkers to predict AKI in critically ill patients with IS. This study aimed to establish a risk model based on white blood cell (WBC)-related biomarkers to predict AKI in critically ill patients with IS.

Methods

Data were extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) for a training cohort, and data were extracted from the Medical Information Mart for eICU Collaborative Research Database (eICU-CRD) for a validation cohort. Logistic regression analysis was used to determine the significant predictors of WBC-related biomarkers on AKI prediction, and a risk model was established based on those significant indicators in multivariate logistic regression. The receiver operating characteristics (ROC) curve was utilized to obtain the best cut-off value of the risk model. The Kaplan-Meier curve was used to evaluate the prognosis-predictive ability of the risk model.

Results

The overall incidence of AKI was 28.4% in the training cohort and 33.2% in the validation cohort. WBC to lymphocyte ratio (WLR), WBC to basophils ratio (WBR), WBC to hemoglobin ratio (WHR), and neutrophil to lymphocyte ratio (NLR) could independently predict AKI, and a novel risk model was established based on WLR, WBR, WHR, and NLR. This risk model depicted good prediction performance both in AKI and other clinical outcomes including hemorrhage, persistent AKI, AKI progression, ICU mortality, and in-hospital mortality both in the training set and in the validation set.

Conclusion

A risk model based on WBC-related indicators exhibited good AKI prediction performance in critically ill patients with IS which could provide a risk stratification tool for clinicians in the ICU.

The Impact of Post-contrast Acute Kidney Injury on In-hospital Mortality After Endovascular Thrombectomy in Patients With Acute Ischemic Stroke

Background and Purpose: Clinical outcome and mortality after endovascular thrombectomy (EVT) in patients with ischemic stroke are commonly assessed after 3 months. In patients with acute kidney injury (AKI), unfavorable results for 3-month mortality have been reported. However, data on the in-hospital mortality after EVT in this population are sparse. In the present study, we assessed whether AKI impacts in-hospital and 3-month mortality in patients undergoing EVT.

Materials and Methods: From a prospectively recruiting database, consecutive acute ischemic stroke patients receiving EVT between 2010 and 2018 due to acute large vessel occlusion were included. Post-contrast AKI (PC-AKI) was defined as an increase of baseline creatinine of ≥0.5 mg/dL or >25% within 48 h after the first measurement at admission. Adjusting for potential confounders, associations between PC-AKI and mortality after stroke were tested in univariate and multivariate logistic regression models.

Results: One thousand one hundred sixty-nine patients were included; 166 of them (14.2%) died during the acute hospital stay. Criteria for PC-AKI were met by 29 patients (2.5%). Presence of PC-AKI was associated with a significantly higher risk of in-hospital mortality in multivariate analysis [odds ratio (OR) = 2.87, 95% confidence interval (CI) = 1.16–7.13, p = 0.023]. Furthermore, factors associated with in-hospital mortality encompassed higher age (OR = 1.03, 95% CI = 1.01–1.04, p = 0.002), stroke severity (OR = 1.05, 95% CI = 1.03–1.08, p < 0.001), symptomatic intracerebral hemorrhage (OR = 3.20, 95% CI = 1.69–6.04, p < 0.001), posterior circulation stroke (OR = 2.85, 95% CI = 1.72–4.71, p < 0.001), and failed recanalization (OR = 2.00, 95% CI = 1.35–3.00, p = 0.001).

Conclusion: PC-AKI is rare after EVT but represents an important risk factor for in-hospital mortality and for mortality within 3 months after hospital discharge. Preventing PC-AKI after EVT may represent an important and potentially lifesaving effort in future daily clinical practice.