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We induced metabolic alkalosis and acidosis in 10 healthy volunteers in order to analyse in vivo relation between pH and ionized calcium (cCa2+). In the alkalinization test, 2.7 mol/kg NaHCO3 was injected. In the acidification test, volunteers took 4 mmol/kg NH4Cl. Blood pH and cCa2+ (mmol/l) mean values (SD) baseline, after alkalinization and acidification tests, were: 7.363 (0.018), 7.456 (0.031), 7.244 (0.031), 1.27 (0.03), 1.14 (0.03) and 1.38 (0.04). Mean slope of regression log cCa2+/pH was -0.39 (SD 0.11). Such a slope differs after in vivo or in vitro changes, due to the in vivo rapid restoration of equilibrium between the plasmatic and interstitial compartments following changes in water and electrolyte concentrations. The type of acid-base alteration-respiratory or metabolic-influences pH changes, and consequently the regression slope. The in vivo slope for log cCa2+/pH in normal subjects (-0.21) is much the same as in acute respiratory alterations (-0.17), whereas it differs in acute metabolic alterations (present study). Bicarbonates play different roles: the same changes in pH cause greater changes in cCa2+ after acute metabolic rather than respiratory alterations. Ca2+ homeostasis is maintained in acute respiratory acid-base imbalance, despite wide shifts in pH, whereas in acute metabolic alterations even small pH changes have striking repercussions on cCa2+. The experimental angular coefficient for in vivo acute metabolic acid-base alterations differs from the theoretical one calculated by Thode's differential equation (-0.25).

The aim of clinical risk management is to improve the quality of care provided by health care organizations and to assure patients' safety. Failure mode and effect analysis (FMEA) is a tool employed for clinical risk reduction. We applied FMEA to chronic hemodialysis outpatients.FMEA steps: (i) process study: we recorded phases and activities. (ii) Hazard analysis: we listed activity-related failure modes and their effects; described control measures; assigned severity, occurrence and detection scores for each failure mode and calculated the risk priority numbers (RPNs) by multiplying the 3 scores. Total RPN is calculated by adding single failure mode RPN. (iii) Planning: we performed a RPNs prioritization on a priority matrix taking into account the 3 scores, and we analyzed failure modes causes, made recommendations and planned new control measures. (iv) Monitoring: after failure mode elimination or reduction, we compared the resulting RPN with the previous one.Our failure modes with the highest RPN came from communication and organization problems. Two tools have been created to ameliorate information flow: "dialysis agenda" software and nursing datasheets. We scheduled nephrological examinations, and we changed both medical and nursing organization. Total RPN value decreased from 892 to 815 (8.6%) after reorganization.Employing FMEA, we worked on a few critical activities, and we reduced patients' clinical risk. A priority matrix also takes into account the weight of the control measures: we believe this evaluation is quick, because of simple priority selection, and that it decreases action times.

Assuming/= 75 years old as the age limit to define dialysis in the elderly, the incidence in this group of patients is progressively increasing in most dialysis units, with an annual growth of 8 to 16%, and represents 20 to 33% of the overall population being affected. The prevalence of the elderly dialysis group is also high, 14 to 20%, in the main literature casistics. Vascular nephropathies, 13 to 50%, represent the major cause of end-stage renal disease, followed by diabetes, 11 to 37%. First year survival rate is an acceptable 52 to 82%, whereas the fifth year value is on average 20 %, also due to the high baseline mortality in these patients. The death causes are mainly cardiac related and represent 45% of the overall mortality. The main prognostic factors are frequency and severity of comorbid factors, in addition to nutritional indexes that are particularly important in this age group. Dialysis dose and treatment time are not related to mortality. Haemodialysis and peritoneal dialysis complement each other to allow the best results. The survival rate, however, is usually better with haemodialysis, especially in old diabetic patients and after some years of treatment. Vascular access, intradialytic hypotension, cardiopathy, intestinal bleeding and amyloidotic arthropathy represent the more critical aspects of dialysis in the elderly, while the quality of life is sometimes unexpectedly good.

Whether to use peritoneal dialysis (PD) or hemodialysis (HD) is a major decision in terms of clinical outcome and management implications; the final choice is difficult because of the conflicting results of comparisons reported in the literature. A review of studies comparing survival shows either superiority of HD, or superiority of PD, or equivalence of the two techniques, but an analysis of the comparisons as a whole brings to light two clear phases in the survival curves. In the first, residual renal function (RRF) gives PD an advantage, or at least puts it on the same level as HD. In the second phase, the reduction in Kt/V as RRF declines gives PD a potential risk. After a few years of PD treatment a sharp watch is therefore necessary to detect signs of under-dialysis promptly and to shift the patient to HD. In patients without RRF it is more difficult to control hypertension with PD and they are more prone to hyperhydration. Despite a widespread belief in the Eighties that PD was the treatment modality of election for diabetics, HD is in fact preferable in these patients, except younger ones. High-turnover and low-turnover bone lesions are more frequent respectively in HD and PD patients. Anemia is better controlled with PD. Blood lipids and nutritional indices are less well controlled with PD. Despite poor technical survival, the "pool" of patients treated with PD frequently reaches 20-30% because it is indicated as first treatment in a large proportion. PD preserves renal function better than HD and is useful while awaiting renal transplantation, with faster postoperative restoration of diuresis. The quality of life with PD as home treatment is usually better than with HD. In conclusion, dialytic centers should establish an integrated PD/HD programme as the two methods are not competitive but are different tools for the treatment and rehabilitation of uremic patients.

We propose a four step flow-chart to define ANCA positivity and antigenic target. 1st step: indirect immunofluorescence test on ethanol-fixed human granulocytes (IIF-E), as screening test. Different staining patterns can be observed: a granular cytoplasmic fluorescence (C-ANCA), a smooth or fine granular perinuclear fluorescence (P-ANCA) and an intermediate pattern (X-ANCA). Antinuclear antibodies (ANA) may mimic P-ANCA. 2nd step: IIF test on formalin-fixed human granulocytes (IIF-F) differentiates true P-ANCA from ANA: most of P-ANCA show cytoplasmic pattern, whereas ANA are negative. 3rd step: IIF test on monkey liver sections (IIF-M) investigates simultaneous ANA and P-ANCA positiveness. P-ANCA positive sera show an exclusive reactivity with neutrophils infiltrating the portal tract, whereas ANA react with hepatocytes nuclei. 4th step: to characterize antigenic target, a solid phase assay, using purified proteins as substrates, is performed. We found 17 C-ANCA (6 PR3, 3 MPO, 1 Lys, 1 Cat G and 6 unknown antigens) out of 173 patients screened with IIF-E. 21 P-ANCA positive sera have been investigated by IIF-F test: 15 showed a cytoplasmic pattern; EIA test gave the following results: 6 MPO, 2 LF, 5 unknown antigens; 2 cases were positive for two antigens, MPOLF. Using IIF-M on the 6 IIF-F negative sera, we observed: 2 false positives (ANCA-/ANA-), one ANCA+/ANA+ (antigen LF), 3 ANCA+/ANA- (unknown antigens). The flow chart suggested allows to analyse in detail ANCA, using easily available commercial kits.

The existence of an intraerythrocytic binding between haemoglobin and urea is known; it determines, in normals, a higher erythrocyte than plasma urea concentration; this binding, in vitro, is progressive for an urea concentration range of 10-400 mg/dl. The only data found relating to dialysis patients, are reported by Nolph et al.; they indicate a decrease in the plasma-blood urea ratio during the blood transit through the dialyzer and a different ratio in comparison with normals, but in our opinion the method used to measure urea concentration was unsuitable. We determined urea distribution ratios by measuring, in blood and plasma, water and urea concentration in uremic inflow and outflow blood samples during dialysis. Our data indicate 1) an increase in outflow erythrocyte water (H2Oe inflow: 0.659, H2Oe outflow: 0.671 P less than 0.01) induced by a different erythrocyte osmotic gradient; 2) a not different ratio between urea of erythrocyte water and urea of plasma water in inflow and outflow samples of dialysed patients and in normals (respectively 1.06, 1.16, 1.13 p = n.s.). Our data from normal and uremic patients are like those found by MurdaughDoyle and by ColtonLowrie in normals.

A literature review allows us to distinguish two types of high efficiency therapy: HED (high efficiency dialysis), with low ultrafiltration coefficient membranes, and HFD (high flux dialysis), with high ultrafiltration coefficient membranes. Data reported show an unchanged hematochemical with the same, or better, treatment tolerance, but there are few data on hydrosaline balance (and correlate hypertension) and middle moleculas removal. Finally we report the experience of our centre in 59 months of treatment in four patients.

To elucidate the limits of single-pool models as regard aberrations induced by urea transcompartmental disequilibrium during urea kinetics, mass balances and fractional clearances were studied, and original formulas developed to calculate urea clearance and distribution volume. In the early dialytic phases, aberrations were more evident, with low kinetic volume (VK) values and kinetic clearance (KK) values double those obtained by dialysate collection (KDC). Over the whole session, both VDC and VK were underestimated (9.9 and 8.2%), compared with anthropometric data (VA). In 3 patients, the comparison of VA and VDC, and the behavior of effective body water clearance (KE), agreed with the hypothesis of dialysis-induced catabolism. Both disequilibrium and hypercatabolism can affect the reliability of the single-pool urea kinetic model; because of overlap, their effects are difficult to separate, and became particularly important in high-efficiency dialysis. A modified model, using V and CtET as input is suggested in order to establish the most appropriate dialysis prescription for uremia therapy.