title: Optimized convective transport with automated pressure control in on-line postdilution hemodiafiltration.
abstract: OBJECTIVE
  In a stable patient population we evaluated on-line postdilution hemodiafiltration (HDF) on the incremental improvement in blood purification versus high-flux HD, using the same dialyzer and blood flow rate. For HDF we used a new way of controlling HDF treatments based on the concept of constant pressure control where the trans-membrane pressure is automatically set by the machine using a feedback loop on the achieved filtration (HDF UC).
  
  
  METHODS
  We enrolled 20 patients on on-line HDF treatment and during a 4-week study period recorded key treatment parameters in HDF UC. For one mid-week study treatment performed in HD and one midweek HDF UC treatment we sampled blood and spent dialysate to evaluate the removal of small- and middle-sized solutes.
  
  
  RESULTS
  We achieved 18+/-3 liters of ultrafiltration in four-hour HDF UC treatments, corresponding to 27+/-3% of the treated blood volume. That percentage varied by patient hematocrit level. The ultrafiltration amounted to 49+/-4% of the estimated plasma water volume treated. We noted few machine alarms. For beta2m and factor D the effective reduction in plasma level by HDF (76+/-6% and 43+/-9%, respectively) was significantly greater than in HD, and a similar relation was seen in mass recovered in spent dialysate. Small solute removal was similar in HDF and HD. Albumin loss was low.
  
  
  CONCLUSIONS
  The additional convective transport provided by on-line HDF significantly improved the removal of middle molecules when all other treatment settings were equal. Using the automated pressure control mode in HDF, the convective volume depended on the blood volume processed and the patient hematocrit level.
authors.affiliation: Nephrology Unit, University Hospital Pontchaillou, Rennes - France. lars-goran.nilsson@gambro.com
authors.forename: V
authors.initials: V
authors.lastname: Joyeux
authors.forename: Y
authors.initials: Y
authors.lastname: Sijpkens
authors.forename: A
authors.initials: A
authors.lastname: Haddj-Elmrabet
authors.forename: A J
authors.initials: AJ
authors.lastname: Bijvoet
authors.forename: L-G
authors.initials: LG
authors.lastname: Nilsson
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001331:Automation; D015415:Biomarkers / Q000097:blood; D001794:Blood Pressure; D011416:Complement Factor D / Q000378:metabolism; D005060:Europe; D005260:Female; D017583:Hemodiafiltration / Q000379:methods*; D006801:Humans; D007676:Kidney Failure, Chronic / Q000097:blood / Q000503:physiopathology / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D012709:Serum Albumin / Q000378:metabolism; D013813:Therapy, Computer-Assisted; D013997:Time Factors; D016896:Treatment Outcome; D001613:beta 2-Microglobulin / Q000097:blood
chemical_list: D015415:Biomarkers; D012709:Serum Albumin; D001613:beta 2-Microglobulin; D011416:Complement Factor D