title: Personal dialysis capacity (PDC(TM)) test: a multicentre clinical study.
abstract: BACKGROUND
  The assessment of the peritoneal membrane capacity and physiology of the individual patient is becoming increasingly important. It allows the prescription of an individualized peritoneal dialysis (PD)-regimen, and the monitoring of peritoneal membrane function over time. The PDC(TM) program offers the possibility to evaluate the peritoneal membrane characteristics and to predict solute and water removal by simulation of different treatment regimens.
  
  
  METHODS
  This study evaluates the relevance of the PDC(TM) program when routinely used. The PDC(TM) data of 336 patients from nine different centres in Europe were evaluated.
  
  
  RESULTS
  The area parameter was 20 985+/-7578 cm/1.73 m(2) (mean+/-SD). The reabsorption of fluid after dissipation of glucose, Jv(AR), was 1.97+/-1.00 ml/min/1.73 m(2). The large pore fluid flux, Jv(L), was 0.11+/-0.07 ml/min/1.73 m(2). A multivariate model for prediction of serum albumin included dialysate protein loss, Jv(L), Jv(AR), nPCR, A(0)/deltaX, BMI and gender (R(2)=0.81, P<0.001). Total clearance fell with increasing PD duration (P<0.001). A negative relation between A(0)/deltaX and ultrafiltration (rho=-0.26, P<0.05), a positive relation between A(0)/deltaX and peritoneal creatinine clearance (rho=0.52, P<0.05) and urea clearance (rho=0.36, P<0.05), and a positive relation between measured peritoneal creatinine and urea clearance (rho=0.64, P<0.01) was observed.
  
  
  CONCLUSIONS
  In summary, the present study shows that the PDC(TM) program is a robust, accurate method to describe the peritoneal membrane transport characteristics. Analysis of PDC(TM) data of large groups of patients, especially if followed up over time, can give interesting information on the physiology of the peritoneal membrane and the impact of different parameters on it.
authors.affiliation: Department of Internal Medicine, University Hospital Gent, Belgium. wim.vanbiesen@rug.ac.be
authors.forename: Wim
authors.initials: W
authors.lastname: Van Biesen
authors.forename: Ola
authors.initials: O
authors.lastname: Carlsson
authors.forename: Roberto
authors.initials: R
authors.lastname: Bergia
authors.forename: Michael
authors.initials: M
authors.lastname: Brauner
authors.forename: Anders
authors.initials: A
authors.lastname: Christensson
authors.forename: Sandrine
authors.initials: S
authors.lastname: Genestier
authors.forename: Marianne
authors.initials: M
authors.lastname: Haag-Weber
authors.forename: James
authors.initials: J
authors.lastname: Heaf
authors.forename: Preben
authors.initials: P
authors.lastname: Joffe
authors.forename: Ann-Cathrine
authors.initials: AC
authors.lastname: Johansson
authors.forename: Bertrand
authors.initials: B
authors.lastname: Morel
authors.forename: Friedrich
authors.initials: F
authors.lastname: Prischl
authors.forename: Dirk
authors.initials: D
authors.lastname: Verbeelen
authors.forename: Andreas
authors.initials: A
authors.lastname: Vychytil
mesh_terms: D000368:Aged; D001692:Biological Transport; D001806:Blood Urea Nitrogen; D003404:Creatinine / Q000097:blood; D003430:Cross-Sectional Studies; D015314:Dialysis Solutions / Q000737:chemistry / Q000493:pharmacokinetics*; D005260:Female; D005500:Follow-Up Studies; D005919:Glomerular Filtration Rate; D006801:Humans; D007676:Kidney Failure, Chronic / Q000175:diagnosis / Q000628:therapy*; D007677:Kidney Function Tests; D016014:Linear Models; D008297:Male; D008567:Membranes, Artificial; D008875:Middle Aged; D015999:Multivariate Analysis; D010347:Patient Care Planning; D010531:Peritoneal Dialysis, Continuous Ambulatory / Q000009:adverse effects / Q000295:instrumentation* / Q000379:methods*; D010537:Peritoneum / Q000378:metabolism; D010539:Permeability; D011237:Predictive Value of Tests; D011336:Probability; D018570:Risk Assessment; D016896:Treatment Outcome
chemical_list: D015314:Dialysis Solutions; D008567:Membranes, Artificial; D003404:Creatinine