Baxter International Inc.

Baxter Healthcare Sa

John Kenneth Leypoldt

Alp Akonur

Ying-Cheng Lo

Baris Ugur Agar

Baris Ugar Agar

Leo Martis

Sujatha Karoor

Rahul Tandon

Clifford J Holmes

Catherine M Hoff

Yin-Cheng Lo

A renal failure blood therapy system includes a renal failure blood therapy machine, concentration levels for each of a plurality of solutes removed from a patient's blood at each of the multiple times, a display device configured to display for selection at least one removed blood solute from the plurality of removed blood solutes, and a device programmed to (i) estimate at least one renal failure blood therapy patient parameter using the determined concentration levels for the at least one selected removed blood solute, (ii) determine a plurality of acceptable renal failure blood therapy treatments that meet a predetermined removed blood solute clearance for the at least one selected removed blood solute using the at least one renal failure blood therapy patient parameter, and (iii) enable selection of at least one of the plurality of acceptable renal failure blood therapy treatments for operation at the renal failure blood therapy machine.

Therapy prediction and optimization for renal failure blood therapy

Therapy prediction and optimization for renal failure blood therapy, especially home hemodialysis

A renal failure blood therapy system includes a renal failure blood therapy machine, a test including multiple blood samples taken at multiple times during a test therapy to determine concentration levels for each of a first solute and a second solute at each of the multiple times, and a device programmed to (i) estimate at least one first patient parameter using the determined concentration levels for the first solute, (ii) estimate at least one second patient parameter using the determined concentration levels for the second solute, (iii) determine a first plurality of acceptable treatments using the at least one first patient parameter, (iv) determine a second plurality of acceptable treatments using the at least one second patient parameter, and (v) merge the first plurality of acceptable treatments with the second plurality of acceptable treatments to determine a plurality of clinically acceptable treatments for both the first solute and the second solute.

A method of predicting serum potassium concentrations in a patient during hemodialysis includes measuring serum potassium concentrations of the patient over a hemodialysis treatment session time and an ultrafiltration rate calculated by a difference between pre- and post-dialytic body weight of the patient during an initial hemodialysis treatment session divided by a total treatment time of the treatment session and estimating a potassium mobilization clearance and a pre-dialysis distribution volume of potassium for the patient. Serum potassium concentrations of the patient can then be predicted at any time during any hemodialysis treatment session with the estimated potassium mobilization clearance and pre-dialysis distribution volume of potassium of the patient.

Therapy prediction and optimization of serum potassium for renal failure blood therapy, especially home hemodialysis

Peritoneal dialysis solutions including a glucose polymer and methods of using the dialysis solutions are disclosed herein. In a general embodiment, the peritoneal dialysis solution includes a glucose polymer in an amount to provide an increased ultrafiltration fluid volume for a given amount of carbohydrate absorbed compared to conventional dialysis solutions containing icodextrin as the active pharmaceutical ingredient. The increased ultrafiltration fluid volume for a given amount of carbohydrate absorbed is obtained by providing specific combinations of weight-average molecular weight, polydispersity index and concentration of the glucose polymer in the dialysis solution.

Peritoneal dialysis solutions comprising glucose polymers

A method of predicting serum phosphorus concentrations in a patient during hemodialysis includes measuring serum phosphorus concentrations of the patient over a hemodialysis treatment session time and an ultrafiltration rate calculated by a difference between pre- and post-dialytic body weight of the patient during an initial hemodialysis treatment session divided by a total treatment time of the treatment session and estimating a phosphorous mobilization clearance and a pre-dialysis distribution volume of phosphorus for the patient. Serum phosphorus concentrations of the patient can then be predicted at any time during any hemodialysis treatment session with the estimated phosphorous mobilization clearance and pre-dialysis distribution volume of phosphorus of the patient.

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Libertyville, IL, United States of America

John Kenneth Leypoldt