RATIONALE: To measure adequacy in patients dialyzed other than three times per week, guidelines recommend the use of 'standard' Kt/V, which commonly is estimated from treatment Kt/V, time and frequency; however, the accuracy of equations that predict treatment Kt/V in patients being dialyzed other than three times per week has not been evaluated. METHODS: In patients enrolled in the Frequent Hemodialysis Network (FHN) Daily and Nocturnal Trials who were being dialyzed three, four or six times per week, we tested the accuracy of the following Kt/V prediction equation: Kt/V = -ln(R - GFAC × T_hours) + (4-3.5 × R) × 0.55 × weight loss/V, where R = post-dialysis/pre-dialysis blood urea nitrogen and GFAC, originally set to 0.008 for a 3/week schedule (Daugirdas, J Am Soc Nephrol 1993), is a factor that adjusts for urea generation. RESULTS: With the above equation, there was <0.1% mean error in predicted treatment Kt/V for 3/week patients, but mean errors were -5, -9 and -13% for the 6/week daily, 4/week nocturnal and 6/week nocturnal patients. Modeling simulations were performed to optimize the GFAC term for dialysis schedule and length of the preceding interdialysis interval (PIDI). After substituting schedule- and interval-optimized GFAC terms, the treatment Kt/V prediction errors were reduced to -0.81, +0.1 and -1.3% for the three frequent dialysis schedules tested. CONCLUSION: For frequent dialysis schedules, the urea generation factor (GFAC) of one commonly used Kt/V prediction equation should be adjusted based on length in days of the PIDI and number of treatments per week.
RATIONALE: To measure adequacy in patients dialyzed other than three times per week, guidelines recommend the use of 'standard' Kt/V, which commonly is estimated from treatment Kt/V, time and frequency; however, the accuracy of equations that predict treatment Kt/V in patients being dialyzed other than three times per week has not been evaluated. METHODS: In patients enrolled in the Frequent Hemodialysis Network (FHN) Daily and Nocturnal Trials who were being dialyzed three, four or six times per week, we tested the accuracy of the following Kt/V prediction equation: Kt/V = -ln(R - GFAC × T_hours) + (4-3.5 × R) × 0.55 × weight loss/V, where R = post-dialysis/pre-dialysis blood urea nitrogen and GFAC, originally set to 0.008 for a 3/week schedule (Daugirdas, J Am Soc Nephrol 1993), is a factor that adjusts for urea generation. RESULTS: With the above equation, there was <0.1% mean error in predicted treatment Kt/V for 3/week patients, but mean errors were -5, -9 and -13% for the 6/week daily, 4/week nocturnal and 6/week nocturnal patients. Modeling simulations were performed to optimize the GFAC term for dialysis schedule and length of the preceding interdialysis interval (PIDI). After substituting schedule- and interval-optimized GFAC terms, the treatment Kt/V prediction errors were reduced to -0.81, +0.1 and -1.3% for the three frequent dialysis schedules tested. CONCLUSION: For frequent dialysis schedules, the urea generation factor (GFAC) of one commonly used Kt/V prediction equation should be adjusted based on length in days of the PIDI and number of treatments per week.
Authors: Glenn M Chertow; Nathan W Levin; Gerald J Beck; Thomas A Depner; Paul W Eggers; Jennifer J Gassman; Irina Gorodetskaya; Tom Greene; Sam James; Brett Larive; Robert M Lindsay; Ravindra L Mehta; Brent Miller; Daniel B Ornt; Sanjay Rajagopalan; Anjay Rastogi; Michael V Rocco; Brigitte Schiller; Olga Sergeyeva; Gerald Schulman; George O Ting; Mark L Unruh; Robert A Star; Alan S Kliger Journal: N Engl J Med Date: 2010-11-20 Impact factor: 91.245
Authors: John T Daugirdas; Thomas A Depner; Tom Greene; Nathan W Levin; Glenn M Chertow; Michael V Rocco Journal: Kidney Int Date: 2010-01-27 Impact factor: 10.612
Authors: Michael V Rocco; Robert S Lockridge; Gerald J Beck; Paul W Eggers; Jennifer J Gassman; Tom Greene; Brett Larive; Christopher T Chan; Glenn M Chertow; Michael Copland; Christopher D Hoy; Robert M Lindsay; Nathan W Levin; Daniel B Ornt; Andreas Pierratos; Mary F Pipkin; Sanjay Rajagopalan; John B Stokes; Mark L Unruh; Robert A Star; Alan S Kliger; A Kliger; P Eggers; J Briggs; T Hostetter; A Narva; R Star; B Augustine; P Mohr; G Beck; Z Fu; J Gassman; T Greene; J Daugirdas; L Hunsicker; B Larive; M Li; J Mackrell; K Wiggins; S Sherer; B Weiss; S Rajagopalan; J Sanz; S Dellagrottaglie; M Kariisa; T Tran; J West; M Unruh; R Keene; J Schlarb; C Chan; M McGrath-Chong; R Frome; H Higgins; S Ke; O Mandaci; C Owens; C Snell; G Eknoyan; L Appel; A Cheung; A Derse; C Kramer; N Geller; R Grimm; L Henderson; S Prichard; E Roecker; M Rocco; B Miller; J Riley; R Schuessler; R Lockridge; M Pipkin; C Peterson; C Hoy; A Fensterer; D Steigerwald; J Stokes; D Somers; A Hilkin; K Lilli; W Wallace; B Franzwa; E Waterman; C Chan; M McGrath-Chong; M Copland; A Levin; L Sioson; E Cabezon; S Kwan; D Roger; R Lindsay; R Suri; J Champagne; R Bullas; A Garg; A Mazzorato; E Spanner; M Rocco; J Burkart; S Moossavi; V Mauck; T Kaufman; A Pierratos; W Chan; K Regozo; S Kwok Journal: Kidney Int Date: 2011-07-20 Impact factor: 10.612
Authors: John T Daugirdas; Tom Greene; Thomas A Depner; John Leypoldt; Frank Gotch; Gerald Schulman; Robert Star Journal: J Am Soc Nephrol Date: 2004-01 Impact factor: 10.121
Authors: Yoshitsugu Obi; Connie M Rhee; Anna T Mathew; Gaurang Shah; Elani Streja; Steven M Brunelli; Csaba P Kovesdy; Rajnish Mehrotra; Kamyar Kalantar-Zadeh Journal: J Am Soc Nephrol Date: 2016-05-11 Impact factor: 10.121
Authors: Francesco Gaetano Casino; Elena Mancini; Giovanni Santarsia; Salvatore Domenico Mostacci; Filomena D'Elia; Maria Di Carlo; Francesco Iannuzzella; Luigi Rossi; Luigi Vernaglione; Daniela Grimaldi; Renato Rapanà; Carlo Basile Journal: J Nephrol Date: 2019-08-07 Impact factor: 3.902