Home Pulse Pressure Predicts Death and Cardiovascular Events in Peritoneal Dialysis Patients.

Increased arterial hypertension represents a prevalent condition in peritoneal dialysis patients that is often related to volume expansion. Pulse pressure is a robust predictor of mortality in dialysis patients, but its association with mortality is unknown in peritoneal patients. We investigated the relationship between home pulse pressure and survival in 140 PD patients. During a mean follow-up of 35 months, 62 patients died, and 66 experienced the combined event death/CV events. In a crude COX regression analysis, a five-unit increase in HPP was associated with a 17% increase in the hazard ratio of mortality (HR: 1.17, 95% CI 1.08-1.26 p < 0.001). This result was confirmed in a multiple Cox model adjusted for age, gender, diabetes, systolic arterial pressure, and dialysis adequacy (HR: 1.31, 95% CI 1.12-1.52, p = 0.001). Similar results were obtained considering the combined event death-CV events as an outcome. Home pulse pressure represents, in part, arterial stiffness, and it is strongly related to all-cause mortality in peritoneal patients. In these high cardiovascular risk populations, it is important to maintain optimal blood pressure control, but it is fundamental to consider all the other cardiovascular risk indicators, such as pulse pressure. Home pulse pressure measurement is easy and feasible and can add important information for the identification and management of high-risk patients.

Cellular and Molecular Signatures of Oxidative Stress in Bronchial Epithelial Cell Models Injured by Cigarette Smoke Extract.

Exposure of the airways epithelium to environmental insults, including cigarette smoke, results in increased oxidative stress due to unbalance between oxidants and antioxidants in favor of oxidants. Oxidative stress is a feature of inflammation and promotes the progression of chronic lung diseases, including Chronic Obstructive Pulmonary Disease (COPD). Increased oxidative stress leads to exhaustion of antioxidant defenses, alterations in autophagy/mitophagy and cell survival regulatory mechanisms, thus promoting cell senescence. All these events are amplified by the increase of inflammation driven by oxidative stress. Several models of bronchial epithelial cells are used to study the molecular mechanisms and the cellular functions altered by cigarette smoke extract (CSE) exposure, and to test the efficacy of molecules with antioxidant properties. This review offers a comprehensive synthesis of human in-vitro and ex-vivo studies published from 2011 to 2021 describing the molecular and cellular mechanisms evoked by CSE exposure in bronchial epithelial cells, the most used experimental models and the mechanisms of action of cellular antioxidants systems as well as natural and synthetic antioxidant compounds.

Electrochemical detection of chloride ions using Ag-based electrodes obtained from compact disc.

In this work electrochemical sensors fabricated from compact disc material (waste or new) are used to quantify chloride ions in different types of samples. All three electrodes, working, counter, and pseudo-reference electrodes, were fabricated from the compact disc and directly used. Different parameters were studied in order to demonstrate the possibility of using this waste material for efficient and low-cost electrochemical sensors. Chloride sensing performance was evaluated using linear scan voltammetry as the detection technique. A sensitivity of 0.174 mA mM-1 cm-2 with a limit of detection of 20 µM and excellent selectivity against many interferents was observed. Selectivity and reproducibility tests were also carried out, showing excellent results. Sensors were also validated with real samples (drinking and sea water, milk, sweat and physiological solutions) with results comparable to conventional techniques. Our results show the applicability and suitability of these low-cost sensors, for detection of those analytes for which, silver, has high sensitivity and selectivity.

Monitoring Risk Factors and Improving Adherence to Therapy in Patients With Chronic Kidney Disease (Smit-CKD Project): Pilot Observational Study.

BACKGROUND: Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors. OBJECTIVE: With this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy. METHODS: The software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform. RESULTS: The Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users. CONCLUSIONS: Our study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population.

Electrochemical detection of dopamine with negligible interference from ascorbic and uric acid by means of reduced graphene oxide and metals-NPs based electrodes.

Dopamine is an important neurotransmitter involved in many human biological processes as well as in different neurodegenerative diseases. Monitoring the concentration of dopamine in biological fluids, i.e., blood and urine is an effective way of accelerating the early diagnosis of these types of diseases. Electrochemical sensors are an ideal choice for real-time screening of dopamine as they can achieve fast, portable inexpensive and accurate measurements. In this work, we present electrochemical dopamine sensors based on reduced graphene oxide coupled with Au or Pt nanoparticles. Sensors were developed by co-electrodeposition onto a flexible substrate, and a systematic investigation concerning the electrodeposition parameters (concentration of precursors, deposition time and potential) was carried out to maximize the sensitivity of the dopamine detection. Square wave voltammetry was used as an electrochemical technique that ensured a high sensitive detection in the nM range. The sensors were challenged against synthetic urine in order to simulate a real sample detection scenario where dopamine concentrations are usually lower than 600 nM. Our sensors show a negligible interference from uric and ascorbic acids which did not affect sensor performance. A wide linear range (0.1-20 µm for gold nanoparticles, 0.1-10 µm for platinum nanoparticles) with high sensitivity (6.02 and 7.19 µA µM-1 cm-2 for gold and platinum, respectively) and a low limit of detection (75 and 62 nM for Au and Pt, respectively) were achieved. Real urine samples were also assayed, where the concentrations of dopamine detected aligned very closely to measurements undertaken using conventional laboratory techniques. Sensor fabrication employed a cost-effective production process with the possibility of also being integrated into flexible substrates, thus allowing for the possible development of wearable sensing devices.

Clinical Epidemiology of Systolic and Diastolic Orthostatic Hypotension in Patients on Peritoneal Dialysis.

Blood pressure changes upon standing reflect a hemodynamic response, which depends on the baroreflex system and euvolemia. Dysautonomia and fluctuations in blood volume are hallmarks in kidney failure requiring replacement therapy. Orthostatic hypotension has been associated with mortality in hemodialysis patients, but neither this relationship nor the impact of changes in blood pressure has been tested in patients on peritoneal dialysis. We investigated both these relationships in a cohort of 137 PD patients. The response to orthostasis was assessed according to a standardized protocol. Twenty-five patients (18%) had systolic orthostatic hypotension, and 17 patients (12%) had diastolic hypotension. The magnitude of systolic and diastolic BP changes was inversely related to the value of the corresponding supine BP component (r = -0.16, p = 0.056 (systolic) and r = -0.25, p = 0.003 (diastolic), respectively). Orthostatic changes in diastolic, but not in systolic, BP were linearly related to the death risk (HR (1 mmHg reduction): 1.04, 95% CI 1.01-1.07, p = 0.006), and this was also true for CV death (HR: 1.08, 95% CI 1.03-1.12, p = 0.001). The strength of this association was not affected by further data adjustment (p ≤ 0.05). These findings suggest that independent of the formal diagnosis of orthostatic hypotension, even minor orthostatic reductions in diastolic BP bear an excess death risk in this population.

Insulin: Trigger and Target of Renal Functions.

Kidney function in metabolism is often underestimated. Although the word "clearance" is associated to "degradation", at nephron level, proper balance between what is truly degraded and what is redirected to de novo utilization is crucial for the maintenance of electrolytic and acid-basic balance and energy conservation. Insulin is probably one of the best examples of how diverse and heterogeneous kidney response can be. Kidney has a primary role in the degradation of insulin released in the bloodstream, but it is also incredibly susceptible to insulin action throughout the nephron. Fluctuations in insulin levels during fast and fed state add another layer of complexity in the understanding of kidney fine-tuning. This review aims at revisiting renal insulin actions and clearance and to address the association of kidney dysmetabolism with hyperinsulinemia and insulin resistance, both highly prevalent phenomena in modern society.

The dominant prognostic value of physical functioning among quality of life domains in end-stage kidney disease.

BACKGROUND: The prognostic relevance of health-related quality of life (HRQoL) has been scarcely studied in the dialysis population and the prognostic power for mortality of the HRQoL domains is unknown. METHODS: We tested the prognostic value for mortality of the HRQoL domains included in the 36-item Short Form Health Survey (SF-36) by Cox's regression analysis and by state-of-the-art prognostic techniques {explained variation in mortality [R2], calibration, discrimination [Harrell's C], risk reclassification [Net Reclassification Index (NRI)], Integrated Discrimination Index [IDI]} in a cohort of 951 patients on chronic haemodialysis. RESULTS: In multivariable Cox models, all but two domains (role limitation due to physical health and due to emotional problems) were independently related with mortality. Physical functioning was the domain adding the highest explanatory power (R2+5.3%) to a basic model including established risk factors for mortality in the dialysis population. The same domain improved risk calibration and showed the highest Harrell's C (+1.7%) and the highest reclassification power (categorical NRI + 8.7%, continuous NRI +46%, P ≤ 0.006) and the highest IDI (+3.4%, P < 0.001). These results were fully confirmed in analyses testing the additional prognostic power of SF-36 domains when combined to a well-validated risk score in dialysis patients. CONCLUSIONS: Physical functioning holds the highest prognostic power for mortality among the domains of SF-36. The gain in prognostic ability by this domain is relevant for clinical practice. Physical functioning has the potential for refining the prognosis and for informing exercise programmes in the dialysis population.

Physical functioning and mortality in very old patients on dialysis.

BACKGROUND: Old patients with end-stage kidney disease (ESKD) represent an increasing segment of the ESKD population maintained on chronic dialysis treatment. Quality of life (QoL) is notoriously poor in ESKD but relationship between QoL and mortality has not been investigated in the old dialysis population. The objective of this study is to investigate the relationship between QoL and mortality in the old dialysis population. METHODS: Quality of Life was measured by the Rand- QoL Short Form 36 questionnaires in a multicentre, perspective cohort study including 253 very old patients (age ≥ 75 years) on chronic dialysis. Prognostic power of QoL was assessed applying C-statistics. RESULTS: In multivariate statistical models including a series of demographic and clinical variable physical function and general health maintained an independent relationship with survival (P ≤ 0.01). In analyses testing the prognostic value of these two SF36 components physical functioning was the component adding the highest explanatory power to standard demographic and clinical risk factors (+5.7%). Furthermore, the same parameter increased by 4.5% the discriminant power by the Harrell's C Index, improved risk reclassification by the 20% (P = 0.003) and model calibration by the 83%. CONCLUSIONS: In the very old dialysis population the physical function component of the SF36 is the QoL component holding the highest predictive power for mortality among the eight components of this instrument. As the discrimination power and risk reclassification ability by physical functioning is of degree relevant for clinical practice, such a measure has potential for refining prognosis and informing exercise programs in this population.

A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis.

BACKGROUND AND OBJECTIVE: Patients with End- Stage Kidney Disease (ESKD) have a unique cardiovascular risk. This study aims at predicting, with a certain precision, death and cardiovascular diseases in dialysis patients. METHODS: To achieve our aim, machine learning techniques have been used. Two datasets have been taken into consideration: the first is an Italian dataset obtained from the Istituto di Fisiologia Clinica of Consiglio Nazionale delle Ricerche of Reggio Calabria; the second is an American dataset provided by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) repository. From each one we obtained 5 datasets, according to the outcome of interest. We tested different types of algorithm (both linear and non-linear), but the final choice was to use Support Vector Machine. In particular, we obtained the best performances using the non-linear SVC with RBF kernel algorithm, optimizing it with GridSearch. The last is an algorithm useful to search the best combination of hyper-parameters (in our case, to find the best couple (C, γ)), in order to improve the accuracy of the algorithm. RESULTS: The use of non-linear SVC with RBF kernel algorithm, optimized with GridSearch, allowed to obtain an accuracy of 95.25% in the Italian dataset and of 92.15% in the American dataset, in a timeframe of 2.5 years,in the prediction of Ischaemic Heart Disease. A worse performance was obtained for the other outcomes. CONCLUSIONS: The machine learning-based approach applied in our study is able to predict, with a high accuracy, the outbreak of cardiovascular diseases in patients on dialysis.

A comparative study of the risk profile of hemodialysis patients in a for profit network and in two regional registries of the Italian Society of Nephrology.

In 2013, the Italian Society of Nephrology joined forces with Nephrocare-Italy to create a clinical research cohort of patients on file in the data-rich clinical management system (EUCLID) of this organization for the performance of observational studies in the hemodialysis (HD) population. To see whether patients in EUCLID are representative of the HD population in Italy, we set out to compare the whole EUCLID population with patients included in the regional HD registries in Emilia-Romagna (Northern Italy) and in Calabria (Southern Italy), the sole regions in Italy which have systematically collected an enlarged clinical data set allowing comparison with the data-rich EUCLID system. An analysis of prevalent and incident patients in 2010 and 2011 showed that EUCLID patients had a lower prevalence of coronary heart disease, peripheral vascular disease, heart failure, valvular heart disease, liver disease, peptic ulcer and other comorbidities and risk factors and a higher fractional urea clearance (Kt/V) than those in the Emilia Romagna and Calabria registries. Accordingly, survival analysis showed a lower mortality risk in the EUCLID 2010 and 2011 cohorts than in the combined two regional registries in the corresponding years: for 2010, hazard ratio (HR) EUCLID vs. Regional registries: 0.80 [95% confidence interval: 0.71-0.90]; for 2011, HR: 0.76 [0.65-0.90]. However, this difference was nullified by statistical adjustment for the difference in comorbidities and risk factors, indicating that the longer survival in the EUCLID database was attributable to the lower risk profile of patients included in that database. This preliminary analysis sets the stage for future observational studies and indicates that appropriate adjustment for difference in comorbidities and risk factors is needed to generalize to the Italian HD population analyses based on the data-rich EUCLID database.

Effect of Vitamin D Receptor Activation on the AGE/RAGE System and Myeloperoxidase in Chronic Kidney Disease Patients.

Vitamin D receptor (VDR) activation has been reported to increase circulating levels of the advanced glycation end products (AGE) and their decoy receptor (RAGE). However, until now, the effect of VDR activation on AGE and RAGE has not been tested in the setting of a randomized, double-blind clinical trial. We have therefore analyzed the effect of VDR activation by paricalcitol on pentosidine, S100A12/ENRAGE, and RAGE and on established biomarkers of oxidative stress like myeloperoxidase in CKD patients in the PENNY trial. At baseline, human S100A12/ENRAGE, RAGE, and myeloperoxidase, but not pentosidine, were intercorrelated, and the association between S100A12/ENRAGE and myeloperoxidase (r = 0.71, P < 0.001) was the strongest among these correlations. Paricalcitol failed to modify biomarkers of the AGE/RAGE system and myeloperoxidase in unadjusted and adjusted analyses by the generalized linear model (GLM). No effect modification by other risk factors was registered. Paricalcitol does not modify biomarkers of the AGE/RAGE system and myeloperoxidase in CKD patients. The apparent increase in RAGE levels by VDR activation reported in previous uncontrolled studies is most likely due to confounding factors rather than to VDR activation per se. This trial is registered with NCT01680198.

Body mass index trend in haemodialysis patients: the shift of nutritional disorders in two Italian regions.

BACKGROUND: In the USA, the increase in the prevalence of obesity in the general population has been accompanied by a marked increase in the prevalence and incidence of obesity in the dialysis population. However, secular trends of body mass index (BMI) have not been investigated in European renal registries. METHODS: We investigated the secular trend of BMI across 18 years (1994-2011) in two haemodialysis (HD) registries (Calabria in southern Italy and Emilia in northern Italy) on a total of 16 201 prevalent HD patients and in a series of 3559 incident HD patients. We compared trends in BMI for HD patients with those in the background general population of the same regions. RESULTS: The average BMI rose from 23.5 kg/m(2) in 1994 to 25.5 (+8.5%) in 2011 in the Calabria registry and from 23.7 in 1998 to 25.4 (+7.1%) in 2011 in the Emilia registry (P < 0.001). The proportion of obese patients (i.e. with BMI >30 kg/m(2)) rose from 6 to 14% in Calabria and from 6 to 16% in Emilia (P < 0.001). These patterns were fully confirmed in incident patients and were mirrored by a substantial decline in the prevalence of underweight-normal and underweight (P < 0.001) patients. Of note, the steepness of the increase in BMI in haemodialysis patients was 3.7 times more pronounced than that in the coeval, age- and sex-matched general population of Calabria and Emilia. CONCLUSIONS: In two regional haemodialysis registries in Italy a steady increase in overweight and obese patients is observed. These patterns are more pronounced than those found in the general population. If further confirmed in other European haemodialysis cohorts, these findings may have relevant public health implications.