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Background and Aims Control of extracellular volume in peritoneal dialysis (PD) patients requires both removal of sodium and water. Hypervolemia occurs more frequently in PD patients and is associated with greater morbidity and mortality. Dietary salt restriction (Na+ < 2g) is recommended in all PD patients. Most patients do not comply with this recommendation (prevalence difficult to assess). Bioimpedance spectroscopy (BIS) devices can help assess volume overload in patients receiving maintenance PD. The aim of our study was to determine the association between fluid status as measured using BIS to BP and salt consumption in continuous ambulatory peritoneal dialysis (CAPD) patients. Method We performed a retrospective, longitudinal study, that included 60 PD patients followed at our unit. Demographic and clinical characteristics, such as age, gender, chronic kidney disease (CKD) etiology, time on PD program, dialytic efficacy (Kt/V), peritoneal equilibration test results, BIS results and episodes of peritonitis were registered from our unit database. We measured total sodium removal and estimated daily sodium intake using dietary recall for one day, during the assessment of dialysis adequacy. Based on a 2017 study of 87 patients on PD that sought a correlation between effective daily sodium intake (memory recollection) and urinary + peritoneal sodium sieving. It allowed, through logistic regression, the creation of equations for patients with and without renal residual function (RRF) (Pearson's 0.6). Statistical analyses were performed using SPSS statistics version 23.0. The statistical hypothesis tests with p-value <0.05 were considered significant. Results Sixty patients (male: 60%) with a mean age of 55,9 ± 9 years were selected. Mean time on dialysis was 24,8 months ± 11,9 (min. 2, max. 63). The most common etiology of CKD was glomerular diseases (n = 16, 26.7%), followed by uncertain etiology (n = 11, 18.3%) and diabetic kidney disease (n = 9, 15%). In total, 71,7% of patients were on continuous ambulatory peritoneal dialysis (CAPD). Mean Kt/V was 2,2 ± 0,6 and the majority of patients were high-average transporters. Previous comorbidities were arterial hypertension (n = 60, 100%), diabetes (n = 16, 26,7%), heart failure (n = 13, 21,7%), body mass index >30 kg/m2 (n = 22, 36,7%) and dyslipidemia (n = 40, 66,7%). According to European Society of Cardiology we define three stages of hypertension: stage 1 (140–159/90–99 mmHg) with 15 patients (25%), stage 2 (160–179/100–109 mmHg) with 14 patients (23,3%) and stage 3 (≥180/≥110 mmHg) with 4 patients (6,7%). In total, we have 27 patients (45%) with hypertension under control. A statistically significant positive correlation was found between a status of overhydration (≥2liters) with salt consumption (Na+ >2g) (p = 0,01) and also of hypertension stages 2 and 3 (p = 0,03). Conclusion In PD patients, BIS is a reliable method for evaluating volume status. We found that stable CAPD patients with uncontrolled BP had higher overhydration and salt consumption compared to patients whose BP was controlled. Control of hypervolemia and blood pressure is associated with better cardiac condition. Thus, it is important to encourage patients on peritoneal dialysis to significantly restrict salt intake.

BACKGROUND AND AIMS Acute kidney injury (AKI) remains one of the most common complications in hospitalized diabetic patients. The relationship between chronic kidney disease (CKD) and hypoglycaemia is well established: both renal neoglucogenesis and insulin clearance are diminished in this population, increasing the risk for hypoglycaemic episodes. A correlation between AKI and hypoglycaemia remains to be proven. A recent study stated that AKI increases hypoglycaemia risk in critically ill patients; other showed higher risk for hypoglycaemic episodes after hospital discharge. We focused on a correlation between AKI and hypoglycaemia risk in hospitalized diabetic patients. METHOD We performed an observational retrospective analysis of all hospitalized diabetic patients in Internal Medicine's ward between 2018 and 2019. Our sample was divided according to the presence/absence of AKI during hospitalization. We considered AKI as a rise of serum creatinine (SCr) >0.3 mg/dL in 48 h or >50% in a week. Baseline kidney function was calculated using CKD-EPI equation, according to the mean ambulatory SCr from the previous 6 months. All patients with CKD stage ≥4 were excluded. We collected 240 diabetic patients with AKI and, to obtain similar sample sizes, aleatory selected 240 diabetic patients without AKI. Hypoglycaemia was defined as peripheral blood sugar levels <70 mg/dL and stratified according to American Diabetes Association classification. IBM SPSS 23.0 was used to perform all statistical analysis. RESULTS We selected 480 diabetic patients with an average age of 81.2 ± 9.2 years; most were women (59.8%) and 36.0% were treated with insulin. Across both populations, hypoglycaemic episodes were more prevalent in insulin-treated patients, with lower baseline glomerular filtration rates (GFR) and higher age and were associated with longer hospitalizations (16.6 ± 12.4 days) and higher 30-day mortality rate {OR 3.7 [confidence interval (CI) 95% 1.6–8.7], P < 0.001}. Diabetic patients with AKI were older (82.7 versus 80.1 years, P = .001), had lower baseline GFR (59.1 versus 70 mL/min/1.73 m2 P < 0.001), longer hospital stays (13.8 ± 11.3 days, P = 0.007) and higher mortality rate (14.0% versus 7.3%, P = 0.05). Hypoglycaemic episodes were more prevalent in diabetic patients with AKI (40.8% versus 15.8%, P < 0.001); the occurrence of AKI during hospitalization increased hypoglycaemia risk by 4.2 times [OR 4.21 (CI 2.56–6.97), P < 0.001]. This relationship maintained after multivariate analysis, which accounted the differences between both groups. The first hypoglycaemic event occurred, on average, 6.7 ± 6.1 days after AKI; a longer time in AKI, irrespective of the severity, associated with higher hypoglycaemia risk and 30-day mortality rate, with a cut-off of 5.5 days resulting in higher frequency of this adverse event. CONCLUSION We found that AKI constitutes an important risk factor for hypoglycaemic episodes in hospitalized diabetic patients, mainly in elderly patients and those with lower baseline GFR. AKI's duration, irrespective of the severity, was the main contributor to higher hypoglycaemia risk. Our data support the need for individualized risk stratification for hypoglycaemic events—we should adapt our clinical practice to prevent or mitigate the impact of these adverse events during hospitalization and after discharge.

BACKGROUND AND AIMS Cardiovascular disease (CVD) is the leading cause of mortality in haemodialysis (HD) patients (40%), mainly secondary to a coronary event (17%). According to the European Society of Cardiology (ESC), beta-blockers (BBs), anti-platelets, angiotensin-converting enzyme inhibitors (ACEis)/angiotensin receptor blockers (ARBs) and statins are the cornerstones of CVD prevention. However, a great percentage of dialysis patients remain undermedicated. Our aim is to identify the predictors of mortality in HD patients after an acute myocardial infarction (AMI) during hospitalization and 1 year after the cardiac event. Methods We performed an observational retrospective study of all HD patients admitted to the coronary intensive care unit between January 2017 and December 2020 due to a myocardial infarction. Our variables of interest were collected before and after hospital discharge and 1 year after. We assessed patients’ frailty using the clinical frailty scale (CFS) and baseline cardiovascular (CV) risk using ESC’s classification; as we focused in HD patients (very-high risk of CVD), we classified CV risk regardless of the kidney disease. IBM SPSS 23.0 was used to perform statistical analysis; the confidence interval (CI) was set at 95%. RESULTS We collected 70 patients (males: n = 51, 73.2%), with a mean age of 70.9 ± 12.2 years and a median time in HD of 73.2 ± 60 months. Identifiable CV risk factors were: dyslipidaemia (98.6%), arterial hypertension (95.7%), heart failure (74.3%), diabetes (57.1%) and obesity (55.7%); mean total cholesterol and low-density lipoprotein cholesterol (LDL) levels were 151 ± 39.6 and 97.5 ± 34.1 mg/dL,  respectively. As a result, 81.4% of our sample was classified as having a very high baseline CV risk. Before admission, most patients were on statin therapy (87.1%), but only 34.2% were taking the proper statin class/dosage adjusted to their CV risk. In fact, only 7.1% were previously medicated with all prognosis-modifying drugs (ACEis/ARBs, statins, anti-platelets and BBs). The mean hospitalization stay was 10.3 ± 9 days, and the early mortality rate (30 days post-admission) was 18.6%. Mortality was higher in older patients (72.5 ± 10.3 versus 69.1 ± 10.9 years; P = .3), males (21.6 versus 10.5%), with longer HD vintage (82.8 ± 46.8 versus 70.8 ± 48 months; P = 0.41) and higher CV risk (very-high CV risk, 84.6 versus 80%; P = .7); hypoalbuminemia (serum albumin < 3.0 g/dL) (OR 5.4, 95% CI 1.2–25.1; P = .028) and higher frailty score (CFS ≥ 4) (OR 6.1, 95% CI 1.2–30.0; P = .002) prompt a worse short-term prognosis. The mortality rate after 1 year was 30%, with a median time of 5.6 ± 2.4 months since the cardiac event. Mortality was also higher in older patients (71.5 ± 10 versus 69 ± 10 years; P = .34), males (31.3 versus 26.3%; P = 0.70), with longer dialysis vintage (85.2 ± 45.6 versus 67.2 ± 48;  P = .14) and longer hospitalizations (12.8 ± 9.9 versus 9.3 ± 8.3;  P = .12). After discharge, patients prescribed with at least three prognosis-modifying drugs had a lower 1-year mortality rate (3.2 versus 26.9%; OR 11, 95% CI 1.2–97.0; P = .003). Hypoalbuminemia (OR 9.4, 95% CI 2.3–4.3’; P = .002) and higher frailty scores (CFS ≥ 4) (OR 4.1, 95% CI 1.2–14.0; P = .025) were associated with worse outcomes. CONCLUSION We concluded that most HD patients were undermedicated prior to a coronary event given their baseline CV risk. Despite most studies in HD patients did not find a beneficial long-term effect of starting statin therapy after HD initiation, one must always individualize therapy according to the patient's CV risk. In our series, better-nourished patients with at least three prognosis-modifying drugs had a lower mortality rate, which highlights the importance of these drugs on survival together with optimal nutritional care.

BACKGROUND AND AIMS Cardiovascular disease (CVD) is the leading cause of death among patients with end-stage renal disease accounting for 40% of all mortality. Diabetes mellitus, the main cause of chronic kidney disease (CKD) worldwide, together with obesity, hypertension and dyslipidaemia, places patients at higher risk for acute myocardial infarction (AMI). Effective treatment such as coronary revascularization is critical to lowering the subsequent risk of CV events and improving long-term survival. In this study, we aim to compare the cardiovascular outcomes in diabetic versus non-diabetic patients in dialysis following an AMI. Methods We retrospectively enrolled 70 CKD stage 5d patients (4 h/3 times a week) aged ≥ 18 years old who were admitted at the cardiac intensive care unit with AMI between January 2017 and December 2020. Baseline variables and laboratory data were collected at admission and 1 month after discharge for follow-up. Two groups were created: G1 (diabetic) and G2 (non-diabetic). Data were collected by consulting electronic medical records. Statistical analyses were performed using the SPSS statistics version 23.0. RESULTS Seventy patients (male: 72.9%) with a mean age of 70.9 ± 12 years were selected. G1 (n = 33; 47.1%) and G2 (n = 37; 52.1%) had similar distributions of gender (male: 72.7% versus 72.9%; P = 0.081) and age (70.9 ± 9 versus 70.8 ± 10 years; P = 0.076) opposite to dialysis vintage (33 versus 17 months; P = 0.003). The main CKD cause in G2 was hypertensive nephrosclerosis (n = 14, 37.8%), followed by uncertain aetiology (n = 10, 27.1%), obstructive uropathy (n = 6, 16.2%), autosomal dominant polycystic kidney disease (n = 3, 8.1%), IgA nephropathy (n = 2, 5.4%) and small vessel vasculitis (n = 2, 5.4%). Previous comorbidities were (G1 versus G2): arterial hypertension (93.9% versus 97.3%; P = 0.77), smoking habits (9.1% versus 16.2%; P = 0.033), heart failure (78.8% versus 67.6%; P = 0.064), left ventricular hypertrophy (47.9% versus 52.8%; P = 0.082), body mass index > 30 kg/m2 (57.6% versus 56.8%; P = 0.72) and dyslipidaemia (100% versus 99%; P = 0.91). At admission, groups were compared hypoalbuminemia (serum albumin < 3.0 g/dL) [37.9% versus 26.8%, OR 4.1, 95% confidence interval (95% CI) 2.1–24.4; P = 0.0022] and clinical frailty score > 4 points (56 versus 32%, OR 5.4, 95% CI 1.4–25.1, P = 0.0041). Total cholesterol (149 ± 38 versus 146 ± 39 mg/dL) and low-density lipoprotein cholesterol (97 ± 31.6 versus 94 ± 29.9 mg/dL) were also compared with no statistically significant differences. In G1, glycaemic control was satisfactory (HbA1c: 7.4%); 45.5% (n = 15) were taking insulin alone, 9.0% (n = 3) were taking oral antidiabetics (DPP-4 inhibitors) and 45.5% (n = 15) were using a combined therapy. Regarding AMI in G1 and G2, ST segment elevation myocardial infarction (STEMI) was present in 8 (24.2%) versus 11 (29.7%) patients (P = 0.08); all patients underwent coronary revascularization except 3 patients on each group (9% versus 8.1%), who had a NSTEMI. During hospitalization (10.5 ± 6 days versus 10.2 ± 12 days; P = 0.12), 13 patients died (n = 6; 18.2% versus n = 7; 18.9%, P = 0.07); 3 were treated conservatively and all 3 belonged to G1. The main cause of death was cardiogenic shock (n = 10, 83.3%). No deaths or new CV events occurred 30 days post-AMI. Multiple regression analysis showed that dialysis vintage was the only significant predictor for the occurrence of a CV event, regardless of being STEMI/NSTEMI or of any intervention. CONCLUSION Based on our results, G1 and G2 showed no difference in mortality or risk of developing a new CV event in the following month post-AMI. This might be related with several non-traditional risk factors, such as chronic volume overload, anaemia, inflammation, oxidative stress, and chronic kidney disease-mineral bone present in the majority of dialysis patients that were not evaluated or with the size of our sample.