Neurological complications of renal dialysis and transplantation

Multimodal Classification Framework Based on Hypergraph Latent Relation for End-Stage Renal Disease Associated with Mild Cognitive Impairment

Combined arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI) can reveal more comprehensive properties of the spatiotemporal and quantitative properties of brain networks. Imaging markers of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI) will be sought from these properties. The current multimodal classification methods often neglect to collect high-order relationships of brain regions and remove noise from the feature matrix. A multimodal classification framework is proposed to address this issue using hypergraph latent relation (HLR). A brain functional network with hypergraph structural information is constructed by fMRI data. The feature matrix is obtained through graph theory (GT). The cerebral blood flow (CBF) from ASL is selected as the second modal feature matrix. Then, the adaptive similarity matrix is constructed by learning the latent relation between feature matrices. Latent relation adaptive similarity learning (LRAS) is introduced to multi-task feature learning to construct a multimodal feature selection method based on latent relation (LRMFS). The experimental results show that the best classification accuracy (ACC) reaches 88.67%, at least 2.84% better than the state-of-the-art methods. The proposed framework preserves more valuable information between brain regions and reduces noise among feature matrixes. It provides an essential reference value for ESRDaMCI recognition.

Characterizing Topological Properties of Brain Functional Networks Using Multi-Threshold Derivative for End-Stage Renal Disease with Mild Cognitive Impairment

Patients with end-stage renal disease (ESRD) experience changes in both the structure and function of their brain networks. In the past, cognitive impairment was often classified based on connectivity features, which only reflected the characteristics of the binary brain network or weighted brain network. It exhibited limited interpretability and stability. This study aims to quantitatively characterize the topological properties of brain functional networks (BFNs) using multi-threshold derivative (MTD), and to establish a new classification framework for end-stage renal disease with mild cognitive impairment (ESRDaMCI). The dynamic BFNs (DBFNs) were constructed and binarized with multiple thresholds, and then their topological properties were extracted from each binary brain network. These properties were then quantified by calculating their derivative curves and expressing them as multi-threshold derivative (MTD) features. The classification results of MTD features were compared with several commonly used DBFN features, and the effectiveness of MTD features in the classification of ESRDaMCI was evaluated based on the classification performance test. The results indicated that the linear fusion of MTD features improved classification performance and outperformed individual MTD features. Its accuracy, sensitivity, and specificity were 85.98 ± 2.92%, 86.10 ± 4.11%, and 81.54 ± 4.27%, respectively. Finally, the feature weights of MTD were analyzed, and MTD-cc had the highest weight percentage of 28.32% in the fused features. The MTD features effectively supplemented traditional feature quantification by addressing the issue of indistinct classification differentiation. It improved the quantification of topological properties and provided more detailed features for diagnosing cognitive disorders.

Blood-brain barrier perturbations by uremic toxins: key contributors in chronic kidney disease-induced neurological disorders?

Chronic kidney disease is multifactorial and estimated to affect more than 840 million people worldwide constituting a major global health crisis. The number of patients will continue to rise mostly because of the ageing population and the increased prevalence of comorbidities such as diabetes and hypertension. Patients with advanced stages display a loss of kidney function leading to an accumulation of, a.o. protein-bound uremic toxins that are poorly eliminated by renal replacement therapies. This systemic retention of toxic metabolites, known as the uremic syndrome, affects other organs. Indeed, neurological complications such as cognitive impairment, uremic encephalopathy, and anxiety have been reported in chronic kidney disease patients. Several factors are involved, including hemodynamic disorders and blood-brain barrier (BBB) impairment. The BBB guarantees the exchange of solutes between the blood and the brain through a complex cellular organization and a diverse range of transport proteins. We hypothesize that the increased exposure of the brain to protein-bound uremic toxins is involved in BBB disruption and induces a perturbation in the activity of endothelial membrane transporters. This phenomenon could play a part in the evolution of neurological disorders driven by this kidney-brain crosstalk impairment. In this review, we present chronic kidney disease-induced neurological complications by focusing on the pathological relationship between the BBB and protein-bound uremic toxins. The importance of mechanistically delineating the impact of protein-bound uremic toxins on BBB integrity and membrane drug transporter expression and function in brain endothelial capillary cells is highlighted. Additionally, we put forward current knowledge gaps in the literature.

Hypergraph representation of multimodal brain networks for patients with end-stage renal disease associated with mild cognitive impairment

The structure and function of brain networks (BN) may be altered in patients with end-stage renal disease (ESRD). However, there are relatively few attentions on ESRD associated with mild cognitive impairment (ESRDaMCI). Most studies focus on the pairwise relationships between brain regions, without taking into account the complementary information of functional connectivity (FC) and structural connectivity (SC). To address the problem, a hypergraph representation method is proposed to construct a multimodal BN for ESRDaMCI. First, the activity of nodes is determined by connection features extracted from functional magnetic resonance imaging (fMRI) (i.e., FC), and the presence of edges is determined by physical connections of nerve fibers extracted from diffusion kurtosis imaging (DKI) (i.e., SC). Then, the connection features are generated through bilinear pooling and transformed into an optimization model. Next, a hypergraph is constructed according to the generated node representation and connection features, and the node degree and edge degree of the hypergraph are calculated to obtain the hypergraph manifold regularization (HMR) term. The HMR and L₁ norm regularization terms are introduced into the optimization model to achieve the final hypergraph representation of multimodal BN (HRMBN). Experimental results show that the classification performance of HRMBN is significantly better than that of several state-of-the-art multimodal BN construction methods. Its best classification accuracy is 91.0891%, at least 4.3452% higher than that of other methods, verifying the effectiveness of our method. The HRMBN not only achieves better results in ESRDaMCI classification, but also identifies the discriminative brain regions of ESRDaMCI, which provides a reference for the auxiliary diagnosis of ESRD.

Ultrasound Versus Magnetic Resonance Imaging in the Evaluation of Shoulder Pain in End Stage Renal Disease Patients on Chronic Hemodialysis

BACKGROUND

Musculoskeletal pain is common in hemodialysis (HD) patients and may be related to articular or periarticular amyloid deposition. The shoulder is one of the most common afflicted joints, but not all causes of shoulder pain are detectable on radiography, and magnetic resonance imaging (MRI) is not always available. The aim of this study was to evaluate the validity of musculoskeletal ultrasound (MSUS) to properly detect shoulder disorders in HD patients by identifying US abnormalities in the shoulder and comparing them to those identified on MRI, with MRI serving as the gold standard test.

METHODS

This cross-sectional observational study was conducted on 28 HD patients (16 males and 12 females, mean age 46.89) with either unilateral or bilateral shoulder pain. Demographic data and clinical characteristics were recruited. All patients were subjected to clinical assessment, MSUS and MRI of both shoulders.

RESULTS

US abnormalities were prevalent in almost all patients. Supraspinatus tendinopathy was the most common abnormality in symptomatic shoulders (92.1%), followed by subacromial-subdeltoid (SASD) bursitis (65.8%), humoral erosions (57.9%), and acromioclavicular joint (ACJ) osteoarthritis (52.6%). MSUS shows high sensitivity and specificity when compared to MRI in all the studied shoulder pathologies except glenohumeral joint (GHJ) effusion (sensitivity, 33.3%) and infraspinatus tendinopathy (sensitivity, 58.3%). The percentage of agreement between MSUS and MRI in detecting biceps tenosynovitis was 82.14% (kappa, 0.64), subscapularis tendinopathy 83.93% (kappa, 0.654), supraspinatus tendinopathy 91.07% (kappa, 0.617), infraspinatus tendinopathy 82.14% (kappa, 0.470), SASD bursitis 80.36% (kappa, 0.569), humeral head erosions 82.14% (kappa, 0.635), GHJ effusion 82.14% (kappa, 0.352), and ACJ osteoarthritis 76.79% (kappa, 0.539).

CONCLUSIONS

Shoulder problems are common in HD patients, even in people who do not have obvious shoulder complaints. MSUS is a valuable imaging technique that assists in the diagnosis of HD patients who report shoulder pain.

Investigating the Effect of Cold Water Bags on the Severity of Restless Leg Syndrome and Sleep Quality in Hemodialysis Patients

Background: Restless legs syndrome is a neurological disorder in hemodialysis patients that causes disturbance and disability in rest, discomfort, sleep disturbance, fatigue, and stress. Objectives: This study was done to evaluate the effect of cold water bags on the severity of restless leg syndrome and sleep quality in hemodialysis patients. Methods: This is a quasi-experimental study (before and after) performed on patients referring to three hospitals in Yazd province. In this study, 40 patients with restless legs syndrome were selected from all patients who were referred to the hemodialysis ward by simple random sampling. The samples completed the Restless Legs Syndrome Symptoms Severity Questionnaire before and after using the cold water bag. Data were analyzed by SPSS 20 software and descriptive statistics and paired t-test at the significance level of < 0.05. Results: This study showed a significant difference between the mean score of restless leg syndrome and sleep quality before and after the interventions (P = 0.000). Furthermore, the mean scores of restless leg syndrome and sleep quality were different between the two intervention groups and statistically significant (P = 0.000). Conclusions: Based on the results, using a water bag reduces the symptoms of restless leg syndrome. Therefore, it is suggested that cold water bags should be used as an effective, safe, low-cost method.

Median Nerve and Ulnar Nerve Entrapment with Cubital Tunnel Syndrome in a Hemodialysis Patient Following Creation of an Arteriovenous Fistula

Neurological and vascular complications associated with creation of arteriovenous access need to be recognized promptly to deliver appropriate interventions for relief of symptoms and avoid loss of function of the involved extremity. We present here a 55-year-old female with end-stage renal disease on hemodialysis secondary to diabetic nephropathy who had a surgical creation of first stage of the brachial artery-basilic vein fistula in the left arm. She subsequently developed pain and weakness of the left arm which was diagnosed as median and ulnar nerve entrapment. She was treated with surgical nerve release and neurolysis and her symptoms improved.

Imaging findings of neurologic complications in lung transplantation: Review of a 9-year cohort

Background

Lung transplantation (LT) requires complex multidisciplinary organization and constitutes a therapeutic option and a life-saving procedure. Although the number of lung recipients continues to increase, neurological complications and death rates following lung transplantation are still higher than desirable.

Purpose

This study aims to analyse the neuroimaging findings in a cohort of adult patients with LT.

Material and Methods

A retrospective cohort study of all lung transplant recipients (344 patients: 205 men and 139 women) at a single institution from January 2011 to January 2020. The collected data included demographic features, clinical data and evaluation of the imaging findings. We also recorded the date of neurological complication(s) and the underlying disease motivating lung transplantation.

Results

We found an elevated rate of neuroimaging findings in patients following LT with 32.6% of positive studies. In our cohort, the average time after LT to a neurological complication was 4.9 months post-transplant. Encephalopathy, critical illness polyneuropathy and stroke, in that order, were the most frequent neurological complications. Structural abnormalities in brain imaging were more often detected using MRI than CT for indications of encephalopathy and seizures.

Conclusions

LT recipients constitute an especially vulnerable group that needs close surveillance, mainly during the early post-transplant period.

End-stage renal disease reduces the expression of drug-metabolizing cytochrome P450s

BACKGROUND

End-stage renal disease is an irreversible status of kidney dysfunction that reduces both renal and non-renal drug clearance. Accumulation of uremic toxins seems to modify the activities of drug-metabolizing cytochrome P450 (CYP) enzymes. The aim of the present work was to refine gene expression analysis for efficient and accurate quantification of CYP mRNAs in patients' leukocytes.

METHODS

We compared six liquid-liquid extraction reagents for RNA isolation and five reverse transcriptase kits for RNA-to-cDNA conversion, and developed quantitative polymerase chain reaction methods for duplex measurements of CYP target genes and the reference gene. The expression of CYP1A2, CYP2C9, CYP2C19 and CYP3A4 in patients with end-stage kidney disease (N = 105) and in organ donors with healthy kidney function (N = 110) was compared.

RESULTS

Regarding the RNA yield and purity, TRIzol, Trizolate and TRI reagents were equal; however, TRI reagent was the most advantageous in terms of financial cost. Reverse transcription using Maxima First Strand cDNA Synthesis kit appeared to be the most efficient with the widest range for quantification of the target transcript. The refined method with the detection of various CYPs and the reference gene in duplex PCR efficiently quantified even the low-level CYP expression. In leukocytes of patients with end-stage renal disease, all four CYPs were expressed at significantly lower level than in organ donors with normal kidney function (p < 0.0001).

CONCLUSIONS

Reduced CYP expression was a direct evidence of transcriptional down-regulation of CYP genes in patients with impaired kidney function.