Intradialytic hypotension is the most frequently occurring complication during hemodialysis (HD) treatments. It associates significant morbidity secondary to end-organ hypoperfusion, such as brain and heart. 1,2 During a HD session the fluid is initially removed from circulating blood volume. To compensate for the drop of blood volume, interstitial fluid is shifted from extravascular to intravascular space. This fact is known as vascular refilling (V REF ). 3 The imbalance between ultrafiltration volume (UF) and V REF leads to significant hypovolemia, which is the major cause of intradialytic hypotension. 4 An adequate fluid management could substantially improve patient outcome and is, therefore, an important challenge for the dialysis staff. 5 Modern dialysis devices include biosensors that monitor continuously and noninvasively relative blood volume (RBV) changes during HD, defined as variations in blood volume from initial baseline during treatment. [6][7][8] It is calculated from changes in hemoconcentration, correlating increases in blood density with variations in plasma volume.It has been suggested that keeping RBV between pre-established thresholds could help prevent intradialytic morbid events (IME). 6,7 However the same drop in RBV may translate to different absolute blood volumes (ABVs), depending on individual baseline volume status. 9 Additionally, IME have been observed with wide variations in RBV, ranging from just minimal changes to higher decreases up to 70%. 10 Finally, postural changes, exercise, food intake, and intravenous fluids administration may also influence the RBV level during HD. 11 It is therefore difficult to identify a uniform threshold for a critical RBV.

Background: Vascular refilling occurs to preserve hemodynamic stability during hemodialysis (HD). Recent studies report a feasible and noninvasive method to determine absolute blood volume (ABV), and estimate vascular refilling during HD. The objective of this study is to analyze if lowering dialysate temperature modifies variations in ABV during HD. Methods:The study was performed in 50 patients under HD. During two different sessions, relative blood volume was assessed using dialysate temperatures of 35.5°C (cool dialysate) and 36.5°C (neutral dialysate). ABV and vascular refilling were calculated using Kron et al methodology.Results: Thirty-nine intradialytic morbid events (IMEs) were observed in 30 patients, 14 under cool dialysate and 25 during neutral dialysate. We did not found statistically differences in ABV or in refilling volume between cool and neutral temperature.When analyzing apart only those patients who presented IME, we observed lower drop in ABV in the 35.5°C dialysate treatments (0.57 L) versus 36.5°C dialysate treatments (0.71 L). When cool dialysate was used, the vascular refilling fraction tended to be higher, but data did not turn statistically significant. Conclusions:In selected groups of patients the use of cool dialysate induces lower ABV variations that could improve hemodynamic stability during HD treatments.

<b><i>Background:</i></b> β-Blockers are the most frequently prescribed cardioprotective drugs in hemodialysis (HD) patients, despite their weak evidence. We sought to evaluate the effects of β-blockers on vascular refilling during HD treatments and examine whether carvedilol, for being noncardioselective and poorly dialyzable, associates more impact than others. <b><i>Methods:</i></b> The study was performed in a cohort of maintenance HD patients from a tertiary center. All patients had previous β-blocker prescription. We conducted a prospective crossover study and measured vascular refilling volume (<i>V</i>_ref) and vascular refilling fraction (<i>F</i>_ref) in 2 circumstances: under β-blocker treatment (βb profile) and without β-blocker effect (non-βb profile). <b><i>Results:</i></b> Twenty patients were included, 10 of whom were treated with carvedilol. Predialysis values were comparable between the 2 profiles. Although the βb profile showed lower <i>V</i>_ref and higher ABV drop, these differences did not reach statistical significance. Data showed an increase in <i>F</i>_ref in the non-βb profile (70.01 ± 6.80% vs. 63.14 ± 11.65%; <i>p</i> = 0.015). The βb profile associated a significantly higher risk of intradialytic hypotension (IDH) (risk ratio 2.40; 95% CI: 1.04–5.55). When analyzing separately the carvedilol group, patients dialyzed under drug effect experienced a significant impairment in <i>V</i>_ref, <i>F</i>_ref, and refilling rate. <b><i>Conclusions:</i></b> Administering β-blockers before HD associated a higher risk of IDH and a decrease in <i>F</i>_ref. Patients dialyzed under carvedilol effect showed an impaired refilling, probably related to its noncardioselectivity and lower dializability.

Background CD163 and calprotectin have been proposed as biomarkers of active renal vasculitis. This study aimed to determine whether the combination of serum/urine calprotectin (s/uCalprotectin) and urinary soluble CD163 (suCD163) increases their individual performance as activity biomarkers. Methods We included 138 patients diagnosed with ANCA vasculitis (n = 52 diagnostic phase, n = 86 remission). The study population was divided into the inception (n = 101) and the validation cohort (n = 37). We determined the s/uCalprotectin and suCD163 concentration using ELISA at the diagnostic or at the remission phase. ROC curves were conducted to assess the biomarkers’ classificatory values. We elaborated a combinatorial biomarker model in the inception cohort. The ideal cutoffs were used in the validation cohort to confirm the model's accuracy in the distinction between active disease and remission. We added the classical ANCA vasculitis activity biomarkers to the model to increase the classificatory performance. Results sCalprotectin and suCD163’s concentration was higher in the diagnostic compared to the remission phase, P = 0 013 and P &lt; 0,0001. According to the ROC curves, sCalprotectin and suCD163 were accurate biomarkers to discern activity [AUC 0,73 (0,59–0 806), P = 0 015 and 0,88 (0,79–0,97), P &lt; 0,0001]. The combinatory model with the best performance in terms of sensitivity, specificity, and likelihood ratio included sCalprotectin, suCD163, and haematuria. Regarding the inception and the validation cohort, we obtained a sensibility, specificity, and a likelihood ratio of 97%, 90%, and 9,7 and 78%, 94%, and 13, respectively. Conclusions In patients with ANCA vasculitis, a predictive model combining sCalprotectin, suCD163, and haematuria could be useful in detecting active kidney disease.