Abstract: A system, program product and method continuously optimize an ultrafiltration rate during an extracorporeal renal replacement process by modeling physiological and actual rate data. The system maps the sensed, physiological data to a mathematical model to assess the data in terms of the ultrafiltration rate. The model provides parameters used to predict where the treatment is headed based on current conditions. The system processes the parameters in terms of preset criteria to generate the optimized ultrafiltration rate. Where the system is networked, communication of the data may be accomplished using remote and online communication techniques.

Abstract: A method and apparatus for examining data from a chemical analyzer for artifactual results. A set of rules are established to identify artifactual results based upon experience with the analyzer. Moreover, each rule can be associated with a sample collection or testing problem which potentially caused the artifactual result. Using these rules, output data from the analyzer can be tested to see if any of the rules are satisfied. If a rule is satisfied, then an artifactual result can be indicated, as well as the potential cause of the artifactual result. An output file can be created which indicates the artifactual data samples and the potential artifactual causes. Preferably, the rules are provided in a user-modifiable data file, so that the rules may be modified based upon additional experience. The rules file and output file are also preferably provided in a user-friendly format, such as in a spreadsheet or database application format for example.

Abstract: A multipurpose hemofiltration system and method are disclosed for the removal of fluid and/or soluble waste from the blood of a patient. The system continuously monitors the flow rates of drained fluid, blood, and infusate. When necessary, the pumping rates of the infusate, drained fluid and blood are adjusted to remove a preselected amount of fluid from the blood in a preselected time period. A supervisory controller can monitor patient parameters, such as heart rate and blood pressure, and adjust the pumping rates accordingly. The supervisory controller uses fuzzy logic to make expert decisions, based upon a set of supervisory rules, to control each pumping rate to achieve a desired flow rate and to respond to fault conditions. An adaptive controller corrects temporal variations in the flow rate based upon an adaptive law and a control law.