Changes of Dissociative Properties of Hemoglobin in Patients with Chronic Kidney Disease.

Background: The ability of hemoglobin to bind and dissociate oxygen is crucial in delivering oxygen to tissues and is influenced by a range of physiological states, compensatory mechanisms, and pathological conditions. This may be illustrated by the oxyhemoglobin dissociation curve (ODC). The key parameter for evaluating the oxygen affinity to hemoglobin is p50. The aim of this study was to evaluate the impact of hemodialysis on p50 in a group of patients with chronic kidney disease (CKD). An additional goal was to assess the correlation between p50 and the parameters of erythropoiesis, point-of-care testing (POCT), and other laboratory parameters. Methods: One hundred and eighty patients (106 male, 74 female), mean age 62.5 ± 17 years, with CKD stage G4 and G5 were enrolled in this cross-sectional study. Patients were divided into two groups, including 65 hemodialysis (HD) patients and 115 patients not receiving dialysis (non-HD). During the standard procedure of arteriovenous fistula creation, blood samples from the artery (A) and the vein (V) were taken for POCT. The causes of CKD, as well as demographic and comorbidity data, were obtained from medical records and direct interviews. Results: The weekly dose of erythropoietin was higher in HD patients than in non-HD patients (4914 ± 2253 UI vs. 403 ± 798 UI, p < 0.01), but hemoglobin levels did not differ between these groups. In the group of non-HD patients, more advanced metabolic acidosis (MA) was found, compared to the group with HD. In arterial and venosus blood samples, the non-HD group had significantly lower pH, pCO2 and HCO3-. This group had a higher proportion of individuals with MA with HCO3- < 22 mmol/L (42% vs. 24%, p < 0.01). The absolute difference of p50 in arterial and venous blood was determined using the formula Δp50 = (p50-A) - (p50-V). Δp50 was significantly higher in the HD group in comparison to non-HD (0.08 ± 2.05 mmHg vs. -0.66 ± 1.93 mmHg, p = 0,02). There was a negative correlation between pH and the p50 value in arterial (pH-A vs. p50-A, r = -0.56, p < 0.01) and venous blood (pH-V vs. p50-V, r = -0.45, p < 0.01). In non-HD patients, hemoglobin levels correlated negatively with p50 (r = -0.29, p < 0.01), whereas no significant relation was found in HD patients. Conclusions: The ODC in pre-dialysis CKD (non-HD) patients is shifted to the right due to MA, and this is an additional factor influencing erythropoiesis. Hemodialysis restores the natural differences in hemoglobin's dissociation characteristics in the arterial and venous circulation.

Point-of-Care Testing to Differentiate Various Acid-Base Disorders in Chronic Kidney Disease.

BACKGROUND: Normal-anion-gap metabolic acidosis (AGMA) and high-anion-gap metabolic acidosis (HAGMA) are two forms of metabolic acidosis, which is a common complication in patients with chronic kidney disease (CKD). The aim of this study is to identify the prevalence of various acid-base disorders in patients with advanced CKD using point-of-care testing (POCT) and to determine the relationship between POCT parameters. METHODS: In a group of 116 patients with CKD in stages G4 and G5, with a mean age of 62.5 ± 17 years, a sample of arterial blood was taken during the arteriovenous fistula procedure for POCT, which enables an assessment of the most important parameters of acid-base balance, including: pH, base excess (BE), bicarbonate (HCO3-), chloride(Cl-), anion gap (AG), creatinine and urea concentration. Based on this test, patients were categorized according to the type of acidosis-base disorder. RESULTS: Decompensate acidosis with a pH < 7.35 was found in 68 (59%) patients. Metabolic acidosis (MA), defined as the concentration of HCO3- ≤ 22 mmol/L, was found in 92 (79%) patients. In this group, significantly lower pH, BE, HCO3- and Cl- concentrations were found. In group of MA patients, AGMA and HAGMA was observed in 48 (52%) and 44 (48%) of patients, respectively. The mean creatinine was significantly lower in the AGMA group compared to the HAGMA group (4.91 vs. 5.87 mg/dL, p < 0.05). The AG correlated positively with creatinine (r = 0.44, p < 0.01) and urea (r = 0.53, p < 0.01), but there was no correlation between HCO3- and both creatinine (r = -0.015, p > 0.05) and urea (r = -0.07, p > 0.05). The Cl- concentrations correlated negatively with HCO3- (r = -0.8, p < 0.01). CONCLUSIONS: The most common type of acid-base disturbance in CKD patients in stages 4 and 5 is AGMA, which is observed in patients with better kidney function and is associated with compensatory hyperchloremia. The initiation of renal replacement therapy was significantly earlier for patients diagnosed with HAGMA compared to those diagnosed with AGMA. The more advanced the CKD, the higher the AG.

Radial Artery Deviation and Reimplantation (RADAR) to Accelerate the Maturation of Radial-Cephalic Fistulas for Hemodialysis in Patients with End-Stage Renal Disease.

BACKGROUND: The most common form of vascular access for hemodialysis is a native arteriovenous fistula, which connects the site of the artery to the end of the vein. The maturation process of the fistula plays a crucial role in the establishment of a functional vascular access. Radial artery stenosis is among the potential causes of maturation failure. In these cases, improving the fistula's blood flow may be difficult, as traditional surgical reanastomosis and endovascular intervention frequently fail. Radial artery deviation and reimplantation (RADAR) is a novel and effective technique for creating primary fistulas with a high patency rate. The main disadvantage of this procedure is the ligation of the radial artery and the subsequent known consequences. METHODS: To accelerate maturation, we used RADAR as a secondary approach in three patients with radial artery stenosis and maturation failure. RESULTS: In all patients after surgery, we observed a significant increase in fistula blood flow. Two patients used fistulas for hemodialysis after surgery. We describe the image diagnosis, procedure, and benefits of this method. CONCLUSIONS: The RADAR technique may be successfully used as a secondary access in patients with maturation failure due to RA stenosis to accelerate fistula maturation.

The Artificial Neural Network as a Diagnostic Tool of the Risk of Clostridioides difficile Infection among Patients with Chronic Kidney Disease.

The majority of recently published studies indicate a greater incidence and mortality due to Clostridioides difficile infection (CDI) in patients with chronic kidney disease (CKD). Hospitalization, older age, the use of antibiotics, immunosuppression, proton pump inhibitors (PPI), and chronic diseases such as CKD are responsible for the increased prevalence of infections. The aim of the study is to identify clinical indicators allowing, in combination with artificial intelligence (AI) techniques, the most accurate assessment of the patients being at elevated risk of CDI.

Secondary IgA Nephropathy and IgA-Associated Nephropathy: A Systematic Review of Case Reports.

Primary (pIgAN), secondary IgA nephropathy (sIgAN), and IgA-associated nephropathy can be distinguished. While pIgAN has been thoroughly studied, information about the etiology of sIgAN remains scarce. As concerns sIgAN, several studies suggest that different etiologic factors play a role and ultimately lead to a pathophysiologic process similar to that of pIgAN. In this article, we review a vast number of cases in order to determine the novel putative underlying diseases of sIgAN. Moreover, updates on the common pathophysiology of primary disorders and sIgAN are presented. We identified liver, gastrointestinal, oncological, dermatological, autoimmune, and respiratory diseases, as well as infectious, iatrogenic, and environmental factors, as triggers of sIgAN. As novel biological therapies for listed underlying diseases emerge, we suggest implementing drug-induced sIgAN as a new significant category. Clinicians should acknowledge the possibility of sIgAN progression in patients treated with TNF-α inhibitors, IL-12/IL-23-inhibitors, immune checkpoint inhibitors, CTLA-4, oral anticoagulants, thioureylene derivatives, and anti-vascular endothelial growth factor drugs.

Baseline Proteinuria and Serum Creatinine Concentration as Clinical Predictors of Complete Renal Response in Patients with Lupus Nephritis: A Single-Center Experience.

The aim of the study was to identify robust predictors of complete renal response (CRR), within 36 months, in a single-center cohort of lupus nephritis (LN) patients. Patients with biopsy-confirmed LN who underwent kidney biopsy between 1 January 2010 and 31 December 2020 were included and followed up for at least 6 months. CRR was defined as a reduction of urinary protein-to-creatinine ratio (UPCR) below 0.50 g/g. We evaluated baseline demographic, laboratory, and biopsy characteristics as potential predictors of CRR, and selected the variables further evaluated with Kaplan−Meier curves and log-rank tests. The traits with a p-value < 0.1 were later tested with both uni- and multivariable Cox proportional hazard models. Our sample consisted of 57 patients (84% females, median age 32 years), out of which 63.2% reached CRR within 36 months. The initial UPCR and estimated glomerular filtration rate (eGFR) were the only variables in multivariable Cox regression model, which were selected through backward elimination, with a significance threshold <0.05 (HR = 0.77, p = 0.01 and HR = 1.02, p = 0.001). Our results confirmed the role of initial UPCR and serum creatinine concentration (sCr) as predictors of CRR in LN.

Artificial neural network - an effective tool for predicting the lupus nephritis outcome.

BACKGROUND: Lupus nephropathy (LN) occurs in approximately 50% of patients with systemic lupus erythematosus (SLE), and 20% of them will eventually progress into end-stage renal disease (ESRD). A clinical tool predicting remission of proteinuria might be of utmost importance. In our work, we focused on predicting the chance of complete remission achievement in LN patients, using artificial intelligence models, especially an artificial neural network, called the multi-layer perceptron. METHODS: It was a single centre retrospective study, including 58 individuals, with diagnosed systemic lupus erythematous and biopsy proven lupus nephritis. Patients were assigned into the study cohort, between 1st January 2010 and 31st December 2020, and eventually randomly allocated either to the training set (N = 46) or testing set (N = 12). The end point was remission achievement. We have selected an array of variables, subsequently reduced to the optimal minimum set, providing the best performance. RESULTS: We have obtained satisfactory results creating predictive models allowing to assess, with accuracy of 91.67%, a chance of achieving a complete remission, with a high discriminant ability (AUROC 0.9375). CONCLUSION: Our solution allows an accurate assessment of complete remission achievement and monitoring of patients from the group with a lower probability of complete remission. The obtained models are scalable and can be improved by introducing new patient records.

The Clinical Significance of Urinary Retinol-Binding Protein 4: A Review.

Effective biomarkers for early diagnosis, prognostication, and monitoring in renal diseases (in general) comprise an unmet need. Urinary retinol-binding protein 4, which is the most sensitive indicator of renal tubular damage, holds great promise as a universal biomarker for renal pathologies, in which tubular injury is the driving force. Here, we summarize the most important existing data on the associations between urinary retinol-binding protein 4 and renal diseases and highlight the untapped potential of retinol-binding protein 4 in clinical use.

Clinical Determinants Predicting Clostridioides difficile Infection among Patients with Chronic Kidney Disease.

The majority of recently published studies indicate a greater incidence rate and mortality due to Clostridioides difficile infection (CDI) in patients with chronic kidney disease (CKD). The aim of this study was to assess the clinical determinants predicting CDI among hospitalized patients with CKD and refine methods of prevention. We evaluated the medical records of 279 patients treated at a nephrological department with symptoms suggesting CDI, of whom 93 tested positive for CDI. The survey showed that age, poor kidney function, high Padua prediction score (PPS) and patients' classification of care at admission, treatment with antibiotics, and time of its duration were significantly higher or more frequent among patients who suffered CDI. Whereas BMI, Norton scale (ANSS) and serum albumin concentration were significantly lowered among CDI patients. In a multivariate analysis we proved the stage of CKD and length of antibiotics use increased the risk of CDI, whereas higher serum albumin concentration and ANSS have a protective impact.

Prone Position Facilitates Creation of Ulnar-Basilic Arteriovenous Fistula.

BACKGROUND: The distal ulnar-basilic arteriovenous fistula (UBAVF) is a rarely used alternative type of vascular access for haemodialysis. The location of the vein on the back aspect of the forearm forces an extremely uncomfortable external rotation of the upper limb during surgery when the patient is in a supine position. METHODS: We present a new approach towards creating UBAVF, which involves placing the patient in the prone position, thus eliminating the aforementioned inconvenience. The procedure was performed and described in a 46-year-old patient with chronic kidney disease (CKD) due to diabetic nephropathy. In the period from September 2021 to December 2021, we created an additional three UBAVFs with such modifications. RESULTS: All fistulas were patent both immediately after the procedure and 2 weeks after surgery. CONCLUSIONS: The prone position may improve the comfort of both the operator and the patient during the procedure. On top of this, it may have a positive impact on the quality of the arteriovenous anastomosis.

Multisystem Amyloidosis in a Coal Miner with Silicosis: Is Exposure to Silica Dust a Cause of Amyloid Deposition?

The over-secretion of monoclonal immunoglobulin light chains by clonal B cells followed by the aggregation and extracellular deposition of fibrillar deposits are responsible forthe clinical course AL amyloidosis. It is well documented that silica significantly increases the number of immunoglobulin-secreting cells. In the present paper, we report on a coal miner with silicosis and fast progressing primary amyloidosis with predominantly heart, kidney, and lung manifestations. Severeheart failure due to myocardial hypertrophy resulted in the patient's death. We conclude that long-term environmental silica exposure and silica deposition may contribute to the development of monoclonal gammopathy and amyloidosis due to chronic stimulus and the dysregulation of the immune system.

Unintentional puncture of thyroid cyst during insertion of dialysis catheter.

Central venous catheter (CVC) for hemodialysis are frequently implanted to the internal jugular vein. Thyroid cysts are commonly shown in ultrasound examination and their recognition should not pose a problem. Herby we present an uncommon case of the thyroid cyst unintended puncture, during an attempt of CVC insertion. No further clinical consequences were observed. For all practitioners, involved in interventional nephrology, such complication may be of the utmost importance.

Peptide Charge Derivatization as a Tool for Early Detection of Preeclampsia by Mass Spectrometry-A Comparison with the ELISA Test.

Early detection of any preeclampsia biomarkers may lower the risk of mortality, both for a mother and a child. Our study focuses on techniques for preeclampsia biomarker identification by comparing the results of a method using liquid chromatography mass spectrometry in multiple reaction monitoring mode (LC-MS/MS) with those by the enzyme-linked immunosorbent assay (ELISA) test, as well as by comparing the obtained results with clinical data. In the proposed LC-MS/MS method a tryptic digest peptide charge derivatization strategy was used as a tool for sensitive detection of podocin, i.e., a previously discovered preeclampsia biomarker present in urine samples from pregnant women. Urine samples from pregnant women with diagnosed preeclampsia were collected at different stages of pregnancy and from healthy subjects, and then were analyzed by ELISA test and the proposed method with LC-MS/MS. Charge derivatization of the ε amino group of C-terminal lysine residues in tryptic digests by 2,4,6-triphenylpyrylium salt was performed to increase the ionization efficiency in the LC-MS/MS mode. Podocin was identified at the early stage of pregnancy, while its detection using an ELISA test was not possible. The protocol for urine sample preparation was optimized. Our results show that the proposed method by LC-MS/MS in combination with peptide charge derivatization, provides an ultrasensitive tool for diagnosis of preeclampsia, and provides earlier detection than a clinical diagnosis or ELISA test. The proposed solution may revolutionize medical diagnostics.

Artificial Intelligence-A Tool for Risk Assessment of Delayed-Graft Function in Kidney Transplant.

Delayed-graft function (DGF) might be responsible for shorter graft survival. Therefore, a clinical tool predicting its occurrence is vital for the risk assessment of transplant outcomes. In a single-center study, we conducted data mining and machine learning experiments, resulting in DGF predictive models based on random forest classifiers (RF) and an artificial neural network called multi-layer perceptron (MLP). All designed models had four common input parameters, determining the best accuracy and discriminant ability: donor's eGFR, recipient's BMI, donor's BMI, and recipient-donor weight difference. RF and MLP designs, using these parameters, achieved an accuracy of 84.38% and an area under curve (AUC) 0.84. The model additionally implementing a donor's age, gender, and Kidney Donor Profile Index (KDPI) accomplished an accuracy of 93.75% and an AUC of 0.91. The other configuration with the estimated post-transplant survival (EPTS) and the kidney donor risk profile (KDRI) achieved an accuracy of 93.75% and an AUC of 0.92. Using machine learning, we were able to assess the risk of DGF in recipients after kidney transplant from a deceased donor. Our solution is scalable and can be improved during subsequent transplants. Based on the new data, the models can achieve better outcomes.

Antibodies specific to SARS-CoV-2 proteins N, S and E in COVID-19 patients in the normal population and in historical samples.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally; recognition of immune responses to this virus will be crucial for coronavirus disease 2019 (COVID-19) control, prevention and treatment. We comprehensively analysed IgG and IgA antibody responses to the SARS-CoV-2 nucleocapsid protein (N), spike protein domain 1 (S1) and envelope protein (E) in: SARS-CoV-2-infected patient, healthy, historical and pre-epidemic samples, including patients' medical, epidemiological and diagnostic data, virus-neutralizing capability and kinetics. N-specific IgG and IgA are the most reliable diagnostic targets for infection. Serum IgG levels correlate to IgA levels. Half a year after infection, anti-N and anti-S1 IgG decreased, but sera preserved virus-inhibitory potency; thus, testing for IgG may underestimate the protective potential of antibodies. Historical and pre-epidemic sera did not inhibit SARS-CoV-2, thus its circulation before the pandemic and a protective role from antibodies pre-induced by other coronaviruses cannot be confirmed by this study.

Clinical and Histopathological Factors Influencing IgA Nephropathy Outcome.

IgA nephropathy (IgAN) is the most frequent primary glomerulonephritis worldwide. Due to its heterogenicity, there is a need to establish robust biomarkers for IgAN, to support treatment decisions and evaluate the risk of progression to end-stage renal disease. Using both clinical and histopathological data, derived from renal biopsies, we aimed to find predictors of renal function deterioration and proteinuria reduction. Clinical and histopathological data of 80 patients with biopsy proven IgAN were analyzed. In a multivariate logarithmic regression model, the presence of endocapillary hypercellularity (E1) predicted a decline in estimated glomerular filtration rate (eGFR)of at least 50% with an odds ratio (OR) of 15.2, whereas serum albumin concentration had a negative influence on eGFR deterioration (OR 0.2). In the second multivariate model, the extent of interstitial fibrosis predicted the worsening of eGFR by 50% (OR 1.1) and serum albumin concentration had a protective impact (OR 0.1). In the univariate logarithmic regression, both the extent of interstitial fibrosis and the presence of endocapillary hypercellularity negatively correlated with the reduction in proteinuria below 1.0 g/24 h with an OR of 0.2 and 0.9, respectively. In our paper, we confirmed the utility of histopathological variables, especially endocapillary hypercellularity and interstitial fibrosis, and clinical parameters, particularly serum albumin concentration, in the prediction of both a decline in eGFR and a reduction in proteinuria in IgA nephropathy.

The European bison (Bison bonasus) as an indicatory species for the circulation of tick-borne encephalitis virus (TBEV) in natural foci in Poland.

Tick-borne encephalitis (TBE) is one of the most common zoonotic diseases in Europe transmitted by Ixodidae vectors. While small mammals such as bank voles and ticks constitute the main reservoirs for virus transmission, large sylvatic species act as a food source for ticks. Cervids such as roe deer and red deer are considered sentinel species for TBE in natural foci. In addition, an increase of the population size and density of large wild mammals in an area corresponds to an increase in the tick burden and may potentially increase the prevalence of TBE virus (TBEV) in ticks and tick hosts and further exposure risk in humans. Humans are considered accidental hosts. The prevalence of TBE relies on interactions between host, vector and environment. The present study examines the exposure of the largest European herbivore, the European bison (Bison bonasus) to TBEV infection. Assessed using the IMMUNOZYM FSME ELISA (PROGEN), the overall TBEV seroprevalence was 62.7% in the 335 European bison that were studied. ELISA results were confirmed by the gold-standard virus neutralization test (VNT) with 98.7% sensitivity and thus giving a true prevalence of 63.5%. TBEV seroprevalence was significantly correlated to the origin, age group, sex, population type (free living/captive) and sanitary status (healthy/selectively eliminated/found dead/killed in accident) of the European bison in the univariable analysis. The highest seroprevalences were observed in the three largest north-eastern wild populations (Bialowieska, Borecka and Knyszynska forests), which corresponded with the highest incidence of human cases reported in the country. The risk of TBEV seropositivity increased with age and was higher in female and free-ranging European bison. Additionally, to the epidemiological investigation, the continuous detection of TBEV antibodies was studied by repetitive testing of animals over the course of 34 months. Two of six seropositive animals remained seropositive throughout the study. The presence of antibodies was followed throughout the study in seropositive European bison and for at least a year in animals that seroconverted during the observation period.

Selective ESI-MS detection of carbonyl containing compounds by aminooxyacetic acid immobilized on a resin.

There are numerous examples of bioactive compounds containing carbonyl groups including modified proteins with oxidation of side chain of amino acid residues to aldehyde/ketone groups which are frequently considered as markers of oxidative stress. The carbonyl unit can be also distinguished as a substructure in many illegal drugs including anabolic steroids as well as cations derivatives. Based on chemoselective formation of oximes by solid phase immobilized hydroxylamine derivatives we proposed the protocol for derivatization and selective detection of carbonylated compounds in human serum albumin hydrolysate as a complex peptide mixture and of testosterone in urine samples. This allowed for the removal of the matrix and the qualitative and quantitative analysis of the derivatized analyte by LC-MS/MS (or LC-MRM). Herein we report the preparation and chemical characterization of a novel, ChemMatrix - based resin functionalized with aminooxyacetic acid (AOA). The hydroxylamine moiety in this resin is combined with a peptide linker (GRG) containing an arginine residue to enhance the ionization efficiency. Application of an isotopically labeled carbonylated peptide ((H-Leu-Val-Thr(O)-Asp-Leu-Thr-Lys [13C6,15N2]-OH and testosterone-d3 allowed us to carry out quantitative analyses of detected compounds. Our method is general and may be applied for analysis of carbonylated compounds in biological samples. Our method based on application of functionalized resin allowed to quantify the level of free testosterone in small sample (0.5 mL) of urine, while the non-derivatized testosterone from urine sample was not detected during direct LC-MRM analysis.

Machine Learning in Prediction of IgA Nephropathy Outcome: A Comparative Approach.

We are overwhelmed by a deluge of data and, although its interpretation is challenging, fortunately, information technology comes to the rescue. One of the tools is artificial intelligence, allowing the identification of relationships between variables and their arbitrary classification. We focused on the assessment of both the remission of proteinuria and the deterioration of kidney function in patients with IgA nephropathy, comparing several methods of machine learning. It is of utmost importance to respond to subtle changes in kidney function, which will lead to a deceleration of the disease. This goal has been achieved by analyzing regression techniques, predicting the difference in serum creatinine concentration. We obtained the performance of the tested models which classified patients with high accuracy (Random Forest Classifier showed an accuracy of 0.8-1.0, Multi-Layer Perceptron an Area Under Curve of 0.8842-0.9035 and an accuracy of 0.7527-1.0) and regressors with a low estimation error (Decision Tree Regressor showed MAE 0.2059, RMSE 0.2645). We have demonstrated the impact of both model selection and input features on performance. Application of machine learning methods requires careful selection of models and assessed parameters. The computing power of modern computers allows searching for the models most effective in terms of accuracy.