Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment

Stroke-Induced Renal Dysfunction: Underlying Mechanisms and Challenges of the Brain-Kidney Axis

Stroke, a major neurological disorder and a leading cause of disability and death, often inflicts damage upon other organs, particularly the kidneys. While chronic kidney disease (CKD) has long been established as a significant risk factor for cerebrovascular disease, stroke can induce renal dysfunction, manifesting as acute kidney injury (AKI) or CKD. Mounting clinical and basic research evidence supports the existence of a bidirectional brain-kidney crosstalk following stroke, implicating specific mechanisms and pathways in stroke-related renal dysfunction. This review analyzes pertinent experimental studies, elucidating the underlying mechanisms of this cerebro-renal interaction following stroke. Additionally, we summarize the current landscape of clinical research investigating brain-kidney interplay and discuss potential challenges in the future. By enhancing our understanding of the scientific underpinnings of brain-kidney crosstalk, this review paves the way for improved treatment strategies and outcomes for stroke patients. Recognizing the intricate interplay between the brain and kidneys after stroke holds profound clinical implications.

Intraprocedural continuous saline infusion lines significantly reduce the incidence of acute kidney injury during endovascular procedures for stroke and myocardial infarction: evidence from a systematic review and meta-regression

BACKGROUND

Contrast media used in mechanical therapies for stroke and myocardial infarction represent a significant cause of acute kidney injury (AKI) in acute medical scenarios. Although the continuous saline infusion line (CSIL) is a standard procedure to prevent thrombus formation within the catheter during neurovascular interventions of mechanical thrombectomy (MT), it is not utilized in percutaneous coronary interventions (PCI).

METHODS

A systematic review of the incidence of AKI after MT for stroke treatment was performed. These data were compared with those reported in the literature regarding the incidence of AKI after PCI for acute myocardial infarction. A random-effect model meta-regression was performed to explore the effects of CSIL on AKI incidence, using clinical details as covariates.

RESULTS

A total of 18 and 33 studies on MT and PCI were included, respectively, with 69,464 patients (30,138 [43.4%] for MT and 39,326 [56.6%] for PCI). The mean age was 63.6 years±5.8 with male 66.6%±12.8. Chronic kidney disease ranged 2.0-50.3%. Diabetes prevalence spanned 11.1% to 53.0%. Smoking status had a prevalence of 7.5-72.0%. Incidence of AKI proved highly variable (I2=98%, Cochrane's Q 2985), and appeared significantly lower in the MT subgroup than in the PCI subgroups (respectively 8.3% [95% confidence interval: 4.7-11.9%] vs. 14.7 [12.6-16.8%], P<0.05). Meta-regression showed that CSIL was significantly associated with a decreased incidence of AKI (OR=0.93 [1.001-1.16]; P=0.03).

CONCLUSIONS

Implementation of CSIL during endovascular procedures in acute settings was associated with a significant decrease in the risk of AKI, and its safety should be routinely considered in such interventions.

The Roles of Liver Fibrosis Scores and Modified Stress Hyperglycemia Ratio Values in Predicting Contrast-Induced Nephropathy after Elective Endovascular Infrarenal Abdominal Aortic Aneurysm Repair

Endovascular aortic repair (EVAR) methods are higher preferred for the treatment of patients with abdominal aortic aneurysms (AAAs). Various markers, including the neutrophil-lymphocyte ratio, have been used to predict the risk of contrast-induced nephropathy (CIN). In this study, we aimed to investigate the role of fibrosis-4 score (FIB-4), aspartate transaminase to platelet ratio index (APRI), and modified stress hyperglycemia ratio (mSHR) values in predicting CIN. Patients who had undergone elective endovascular infrarenal abdominal aortic aneurysm repair in our clinic between January 2015 and January 2022 were included in this retrospective study. Patients who did not develop contrast-induced nephropathy after the procedure were identified as Group 1, and those who did were referred to as Group 2. A total of 276 patients were included in the study. The two groups were similar in terms of age, gender, body mass index, hypertension, diabetes mellitus, chronic obstructive pulmonary disease, hyperlipidemia, and left ventricular ejection fraction. In Group 2, the FIB-4 score, APRI, and mSHR values were significantly higher (p = 0.008, p < 0.001, and p < 0.001, respectively). In Group 2, the contrast volume and number of packed blood products used (median 1 (1–4) vs. 2 (1–5)) were significantly higher (p = 0.003 and p = 0.012, respectively). In this study, we demonstrated that we may predict the risk of CIN development with preoperatively calculated, noninvasive liver fibrosis scores and mSHR.

Cardiovascular and Neuronal Consequences of Thyroid Hormones Alterations in the Ischemic Stroke

Ischemic stroke is one of the leading global causes of neurological morbidity and decease. Its etiology depends on multiple events such as cardiac embolism, brain capillaries occlusion and atherosclerosis, which ultimately culminate in blood flow interruption, incurring hypoxia and nutrient deprivation. Thyroid hormones (THs) are pleiotropic modulators of several metabolic pathways, and critically influence different aspects of tissues development. The brain is a key TH target tissue and both hypo- and hyperthyroidism, during embryonic and adult life, are associated with deranged neuronal formation and cognitive functions. Accordingly, increasing pieces of evidence are drawing attention on the consistent relationship between the THs status and the acute cerebral and cardiac diseases. However, the concrete contribution of THs systemic or local alteration to the pathology outcome still needs to be fully addressed. In this review, we aim to summarize the multiple influences that THs exert on the brain and heart patho-physiology, to deepen the reasons for the harmful effects of hypo- and hyperthyroidism on these organs and to provide insights on the intricate relationship between the THs variations and the pathological alterations that take place after the ischemic injury.

Dynamic nomogram for predicting acute kidney injury in patients with acute ischemic stroke: A retrospective study

Background

This study sought to develop and validate a dynamic nomogram chart to assess the risk of acute kidney injury (AKI) in patients with acute ischemic stroke (AIS).

Methods

These data were drawn from the Medical Information Mart for Intensive Care III (MIMIC-III) database, which collects 47 clinical indicators of patients after admission to the hospital. The primary outcome indicator was the occurrence of AKI within 48 h of intensive care unit (ICU) admission. Independent risk factors for AKI were screened from the training set using univariate and multifactorial logistic regression analyses. Multiple logistic regression models were developed, and nomograms were plotted and validated in an internal validation set. Based on the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) to estimate the performance of this nomogram.

Results

Nomogram indicators include blood urea nitrogen (BUN), creatinine, red blood cell distribution width (RDW), heart rate (HR), Oxford Acute Severity of Illness Score (OASIS), the history of congestive heart failure (CHF), the use of vancomycin, contrast agent, and mannitol. The predictive model displayed well discrimination with the area under the ROC curve values of 0.8529 and 0.8598 for the training set and the validator, respectively. Calibration curves revealed favorable concordance between the actual and predicted incidence of AKI (p > 0.05). DCA indicates the excellent net clinical benefit of nomogram in predicting AKI.

Conclusion

In summary, we explored the incidence of AKI in patients with AIS during ICU stay and developed a predictive model to help clinical decision-making.